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Case Study – Methods, Examples and Guide

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A case study is a research method that involves an in-depth examination and analysis of a particular phenomenon or case, such as an individual, organization, community, event, or situation.

It is a qualitative research approach that aims to provide a detailed and comprehensive understanding of the case being studied. Case studies typically involve multiple sources of data, including interviews, observations, documents, and artifacts, which are analyzed using various techniques, such as content analysis, thematic analysis, and grounded theory. The findings of a case study are often used to develop theories, inform policy or practice, or generate new research questions.

Types of Case Study

Types and Methods of Case Study are as follows:

Single-Case Study

A single-case study is an in-depth analysis of a single case. This type of case study is useful when the researcher wants to understand a specific phenomenon in detail.

For Example , A researcher might conduct a single-case study on a particular individual to understand their experiences with a particular health condition or a specific organization to explore their management practices. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as content analysis or thematic analysis. The findings of a single-case study are often used to generate new research questions, develop theories, or inform policy or practice.

Multiple-Case Study

A multiple-case study involves the analysis of several cases that are similar in nature. This type of case study is useful when the researcher wants to identify similarities and differences between the cases.

For Example, a researcher might conduct a multiple-case study on several companies to explore the factors that contribute to their success or failure. The researcher collects data from each case, compares and contrasts the findings, and uses various techniques to analyze the data, such as comparative analysis or pattern-matching. The findings of a multiple-case study can be used to develop theories, inform policy or practice, or generate new research questions.

Exploratory Case Study

An exploratory case study is used to explore a new or understudied phenomenon. This type of case study is useful when the researcher wants to generate hypotheses or theories about the phenomenon.

For Example, a researcher might conduct an exploratory case study on a new technology to understand its potential impact on society. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as grounded theory or content analysis. The findings of an exploratory case study can be used to generate new research questions, develop theories, or inform policy or practice.

Descriptive Case Study

A descriptive case study is used to describe a particular phenomenon in detail. This type of case study is useful when the researcher wants to provide a comprehensive account of the phenomenon.

For Example, a researcher might conduct a descriptive case study on a particular community to understand its social and economic characteristics. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as content analysis or thematic analysis. The findings of a descriptive case study can be used to inform policy or practice or generate new research questions.

Instrumental Case Study

An instrumental case study is used to understand a particular phenomenon that is instrumental in achieving a particular goal. This type of case study is useful when the researcher wants to understand the role of the phenomenon in achieving the goal.

For Example, a researcher might conduct an instrumental case study on a particular policy to understand its impact on achieving a particular goal, such as reducing poverty. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as content analysis or thematic analysis. The findings of an instrumental case study can be used to inform policy or practice or generate new research questions.

Case Study Data Collection Methods

Here are some common data collection methods for case studies:

Interviews involve asking questions to individuals who have knowledge or experience relevant to the case study. Interviews can be structured (where the same questions are asked to all participants) or unstructured (where the interviewer follows up on the responses with further questions). Interviews can be conducted in person, over the phone, or through video conferencing.

Observations

Observations involve watching and recording the behavior and activities of individuals or groups relevant to the case study. Observations can be participant (where the researcher actively participates in the activities) or non-participant (where the researcher observes from a distance). Observations can be recorded using notes, audio or video recordings, or photographs.

Documents can be used as a source of information for case studies. Documents can include reports, memos, emails, letters, and other written materials related to the case study. Documents can be collected from the case study participants or from public sources.

Surveys involve asking a set of questions to a sample of individuals relevant to the case study. Surveys can be administered in person, over the phone, through mail or email, or online. Surveys can be used to gather information on attitudes, opinions, or behaviors related to the case study.

Artifacts are physical objects relevant to the case study. Artifacts can include tools, equipment, products, or other objects that provide insights into the case study phenomenon.

How to conduct Case Study Research

Conducting a case study research involves several steps that need to be followed to ensure the quality and rigor of the study. Here are the steps to conduct case study research:

• Define the research questions: The first step in conducting a case study research is to define the research questions. The research questions should be specific, measurable, and relevant to the case study phenomenon under investigation.
• Select the case: The next step is to select the case or cases to be studied. The case should be relevant to the research questions and should provide rich and diverse data that can be used to answer the research questions.
• Collect data: Data can be collected using various methods, such as interviews, observations, documents, surveys, and artifacts. The data collection method should be selected based on the research questions and the nature of the case study phenomenon.
• Analyze the data: The data collected from the case study should be analyzed using various techniques, such as content analysis, thematic analysis, or grounded theory. The analysis should be guided by the research questions and should aim to provide insights and conclusions relevant to the research questions.
• Draw conclusions: The conclusions drawn from the case study should be based on the data analysis and should be relevant to the research questions. The conclusions should be supported by evidence and should be clearly stated.
• Validate the findings: The findings of the case study should be validated by reviewing the data and the analysis with participants or other experts in the field. This helps to ensure the validity and reliability of the findings.
• Write the report: The final step is to write the report of the case study research. The report should provide a clear description of the case study phenomenon, the research questions, the data collection methods, the data analysis, the findings, and the conclusions. The report should be written in a clear and concise manner and should follow the guidelines for academic writing.

Examples of Case Study

Here are some examples of case study research:

• The Hawthorne Studies : Conducted between 1924 and 1932, the Hawthorne Studies were a series of case studies conducted by Elton Mayo and his colleagues to examine the impact of work environment on employee productivity. The studies were conducted at the Hawthorne Works plant of the Western Electric Company in Chicago and included interviews, observations, and experiments.
• The Stanford Prison Experiment: Conducted in 1971, the Stanford Prison Experiment was a case study conducted by Philip Zimbardo to examine the psychological effects of power and authority. The study involved simulating a prison environment and assigning participants to the role of guards or prisoners. The study was controversial due to the ethical issues it raised.
• The Challenger Disaster: The Challenger Disaster was a case study conducted to examine the causes of the Space Shuttle Challenger explosion in 1986. The study included interviews, observations, and analysis of data to identify the technical, organizational, and cultural factors that contributed to the disaster.
• The Enron Scandal: The Enron Scandal was a case study conducted to examine the causes of the Enron Corporation’s bankruptcy in 2001. The study included interviews, analysis of financial data, and review of documents to identify the accounting practices, corporate culture, and ethical issues that led to the company’s downfall.
• The Fukushima Nuclear Disaster : The Fukushima Nuclear Disaster was a case study conducted to examine the causes of the nuclear accident that occurred at the Fukushima Daiichi Nuclear Power Plant in Japan in 2011. The study included interviews, analysis of data, and review of documents to identify the technical, organizational, and cultural factors that contributed to the disaster.

Application of Case Study

Case studies have a wide range of applications across various fields and industries. Here are some examples:

Business and Management

Case studies are widely used in business and management to examine real-life situations and develop problem-solving skills. Case studies can help students and professionals to develop a deep understanding of business concepts, theories, and best practices.

Case studies are used in healthcare to examine patient care, treatment options, and outcomes. Case studies can help healthcare professionals to develop critical thinking skills, diagnose complex medical conditions, and develop effective treatment plans.

Case studies are used in education to examine teaching and learning practices. Case studies can help educators to develop effective teaching strategies, evaluate student progress, and identify areas for improvement.

Social Sciences

Case studies are widely used in social sciences to examine human behavior, social phenomena, and cultural practices. Case studies can help researchers to develop theories, test hypotheses, and gain insights into complex social issues.

Law and Ethics

Case studies are used in law and ethics to examine legal and ethical dilemmas. Case studies can help lawyers, policymakers, and ethical professionals to develop critical thinking skills, analyze complex cases, and make informed decisions.

Purpose of Case Study

The purpose of a case study is to provide a detailed analysis of a specific phenomenon, issue, or problem in its real-life context. A case study is a qualitative research method that involves the in-depth exploration and analysis of a particular case, which can be an individual, group, organization, event, or community.

The primary purpose of a case study is to generate a comprehensive and nuanced understanding of the case, including its history, context, and dynamics. Case studies can help researchers to identify and examine the underlying factors, processes, and mechanisms that contribute to the case and its outcomes. This can help to develop a more accurate and detailed understanding of the case, which can inform future research, practice, or policy.

Case studies can also serve other purposes, including:

• Illustrating a theory or concept: Case studies can be used to illustrate and explain theoretical concepts and frameworks, providing concrete examples of how they can be applied in real-life situations.
• Developing hypotheses: Case studies can help to generate hypotheses about the causal relationships between different factors and outcomes, which can be tested through further research.
• Providing insight into complex issues: Case studies can provide insights into complex and multifaceted issues, which may be difficult to understand through other research methods.
• Informing practice or policy: Case studies can be used to inform practice or policy by identifying best practices, lessons learned, or areas for improvement.

Advantages of Case Study Research

There are several advantages of case study research, including:

• In-depth exploration: Case study research allows for a detailed exploration and analysis of a specific phenomenon, issue, or problem in its real-life context. This can provide a comprehensive understanding of the case and its dynamics, which may not be possible through other research methods.
• Rich data: Case study research can generate rich and detailed data, including qualitative data such as interviews, observations, and documents. This can provide a nuanced understanding of the case and its complexity.
• Holistic perspective: Case study research allows for a holistic perspective of the case, taking into account the various factors, processes, and mechanisms that contribute to the case and its outcomes. This can help to develop a more accurate and comprehensive understanding of the case.
• Theory development: Case study research can help to develop and refine theories and concepts by providing empirical evidence and concrete examples of how they can be applied in real-life situations.
• Practical application: Case study research can inform practice or policy by identifying best practices, lessons learned, or areas for improvement.
• Contextualization: Case study research takes into account the specific context in which the case is situated, which can help to understand how the case is influenced by the social, cultural, and historical factors of its environment.

Limitations of Case Study Research

There are several limitations of case study research, including:

• Limited generalizability : Case studies are typically focused on a single case or a small number of cases, which limits the generalizability of the findings. The unique characteristics of the case may not be applicable to other contexts or populations, which may limit the external validity of the research.
• Biased sampling: Case studies may rely on purposive or convenience sampling, which can introduce bias into the sample selection process. This may limit the representativeness of the sample and the generalizability of the findings.
• Subjectivity: Case studies rely on the interpretation of the researcher, which can introduce subjectivity into the analysis. The researcher’s own biases, assumptions, and perspectives may influence the findings, which may limit the objectivity of the research.
• Limited control: Case studies are typically conducted in naturalistic settings, which limits the control that the researcher has over the environment and the variables being studied. This may limit the ability to establish causal relationships between variables.
• Time-consuming: Case studies can be time-consuming to conduct, as they typically involve a detailed exploration and analysis of a specific case. This may limit the feasibility of conducting multiple case studies or conducting case studies in a timely manner.
• Resource-intensive: Case studies may require significant resources, including time, funding, and expertise. This may limit the ability of researchers to conduct case studies in resource-constrained settings.

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Researcher, Academic Writer, Web developer

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Methodology

• What Is a Case Study? | Definition, Examples & Methods

What Is a Case Study? | Definition, Examples & Methods

Published on May 8, 2019 by Shona McCombes . Revised on November 20, 2023.

A case study is a detailed study of a specific subject, such as a person, group, place, event, organization, or phenomenon. Case studies are commonly used in social, educational, clinical, and business research.

A case study research design usually involves qualitative methods , but quantitative methods are sometimes also used. Case studies are good for describing , comparing, evaluating and understanding different aspects of a research problem .

Table of contents

When to do a case study, step 1: select a case, step 2: build a theoretical framework, step 3: collect your data, step 4: describe and analyze the case, other interesting articles.

A case study is an appropriate research design when you want to gain concrete, contextual, in-depth knowledge about a specific real-world subject. It allows you to explore the key characteristics, meanings, and implications of the case.

Case studies are often a good choice in a thesis or dissertation . They keep your project focused and manageable when you don’t have the time or resources to do large-scale research.

You might use just one complex case study where you explore a single subject in depth, or conduct multiple case studies to compare and illuminate different aspects of your research problem.

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Once you have developed your problem statement and research questions , you should be ready to choose the specific case that you want to focus on. A good case study should have the potential to:

• Provide new or unexpected insights into the subject
• Challenge or complicate existing assumptions and theories
• Propose practical courses of action to resolve a problem
• Open up new directions for future research

TipIf your research is more practical in nature and aims to simultaneously investigate an issue as you solve it, consider conducting action research instead.

Unlike quantitative or experimental research , a strong case study does not require a random or representative sample. In fact, case studies often deliberately focus on unusual, neglected, or outlying cases which may shed new light on the research problem.

Example of an outlying case studyIn the 1960s the town of Roseto, Pennsylvania was discovered to have extremely low rates of heart disease compared to the US average. It became an important case study for understanding previously neglected causes of heart disease.

However, you can also choose a more common or representative case to exemplify a particular category, experience or phenomenon.

Example of a representative case studyIn the 1920s, two sociologists used Muncie, Indiana as a case study of a typical American city that supposedly exemplified the changing culture of the US at the time.

While case studies focus more on concrete details than general theories, they should usually have some connection with theory in the field. This way the case study is not just an isolated description, but is integrated into existing knowledge about the topic. It might aim to:

• Exemplify a theory by showing how it explains the case under investigation
• Expand on a theory by uncovering new concepts and ideas that need to be incorporated
• Challenge a theory by exploring an outlier case that doesn’t fit with established assumptions

To ensure that your analysis of the case has a solid academic grounding, you should conduct a literature review of sources related to the topic and develop a theoretical framework . This means identifying key concepts and theories to guide your analysis and interpretation.

There are many different research methods you can use to collect data on your subject. Case studies tend to focus on qualitative data using methods such as interviews , observations , and analysis of primary and secondary sources (e.g., newspaper articles, photographs, official records). Sometimes a case study will also collect quantitative data.

Example of a mixed methods case studyFor a case study of a wind farm development in a rural area, you could collect quantitative data on employment rates and business revenue, collect qualitative data on local people’s perceptions and experiences, and analyze local and national media coverage of the development.

The aim is to gain as thorough an understanding as possible of the case and its context.

In writing up the case study, you need to bring together all the relevant aspects to give as complete a picture as possible of the subject.

How you report your findings depends on the type of research you are doing. Some case studies are structured like a standard scientific paper or thesis , with separate sections or chapters for the methods , results and discussion .

Others are written in a more narrative style, aiming to explore the case from various angles and analyze its meanings and implications (for example, by using textual analysis or discourse analysis ).

In all cases, though, make sure to give contextual details about the case, connect it back to the literature and theory, and discuss how it fits into wider patterns or debates.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Normal distribution
• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Mixed methods research
• Non-probability sampling
• Quantitative research
• Ecological validity

Research bias

• Rosenthal effect
• Implicit bias
• Cognitive bias
• Selection bias
• Negativity bias
• Status quo bias

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The Ultimate Guide to Qualitative Research - Part 1: The Basics

• Introduction and overview
• What is qualitative research?
• What is qualitative data?
• Examples of qualitative data
• Qualitative vs. quantitative research
• Mixed methods
• Qualitative research preparation
• Theoretical perspective
• Theoretical framework
• Literature reviews

Research question

• Conceptual framework
• Conceptual vs. theoretical framework

Data collection

• Qualitative research methods
• Focus groups
• Observational research

What is a case study?

Applications for case study research, what is a good case study, process of case study design, benefits and limitations of case studies.

• Ethnographical research
• Ethical considerations
• Confidentiality and privacy
• Power dynamics
• Reflexivity

Case studies

Case studies are essential to qualitative research , offering a lens through which researchers can investigate complex phenomena within their real-life contexts. This chapter explores the concept, purpose, applications, examples, and types of case studies and provides guidance on how to conduct case study research effectively.

Whereas quantitative methods look at phenomena at scale, case study research looks at a concept or phenomenon in considerable detail. While analyzing a single case can help understand one perspective regarding the object of research inquiry, analyzing multiple cases can help obtain a more holistic sense of the topic or issue. Let's provide a basic definition of a case study, then explore its characteristics and role in the qualitative research process.

Definition of a case study

A case study in qualitative research is a strategy of inquiry that involves an in-depth investigation of a phenomenon within its real-world context. It provides researchers with the opportunity to acquire an in-depth understanding of intricate details that might not be as apparent or accessible through other methods of research. The specific case or cases being studied can be a single person, group, or organization – demarcating what constitutes a relevant case worth studying depends on the researcher and their research question .

Among qualitative research methods , a case study relies on multiple sources of evidence, such as documents, artifacts, interviews , or observations , to present a complete and nuanced understanding of the phenomenon under investigation. The objective is to illuminate the readers' understanding of the phenomenon beyond its abstract statistical or theoretical explanations.

Characteristics of case studies

Case studies typically possess a number of distinct characteristics that set them apart from other research methods. These characteristics include a focus on holistic description and explanation, flexibility in the design and data collection methods, reliance on multiple sources of evidence, and emphasis on the context in which the phenomenon occurs.

Furthermore, case studies can often involve a longitudinal examination of the case, meaning they study the case over a period of time. These characteristics allow case studies to yield comprehensive, in-depth, and richly contextualized insights about the phenomenon of interest.

The role of case studies in research

Case studies hold a unique position in the broader landscape of research methods aimed at theory development. They are instrumental when the primary research interest is to gain an intensive, detailed understanding of a phenomenon in its real-life context.

In addition, case studies can serve different purposes within research - they can be used for exploratory, descriptive, or explanatory purposes, depending on the research question and objectives. This flexibility and depth make case studies a valuable tool in the toolkit of qualitative researchers.

Remember, a well-conducted case study can offer a rich, insightful contribution to both academic and practical knowledge through theory development or theory verification, thus enhancing our understanding of complex phenomena in their real-world contexts.

What is the purpose of a case study?

Case study research aims for a more comprehensive understanding of phenomena, requiring various research methods to gather information for qualitative analysis . Ultimately, a case study can allow the researcher to gain insight into a particular object of inquiry and develop a theoretical framework relevant to the research inquiry.

Why use case studies in qualitative research?

Using case studies as a research strategy depends mainly on the nature of the research question and the researcher's access to the data.

Conducting case study research provides a level of detail and contextual richness that other research methods might not offer. They are beneficial when there's a need to understand complex social phenomena within their natural contexts.

The explanatory, exploratory, and descriptive roles of case studies

Case studies can take on various roles depending on the research objectives. They can be exploratory when the research aims to discover new phenomena or define new research questions; they are descriptive when the objective is to depict a phenomenon within its context in a detailed manner; and they can be explanatory if the goal is to understand specific relationships within the studied context. Thus, the versatility of case studies allows researchers to approach their topic from different angles, offering multiple ways to uncover and interpret the data .

The impact of case studies on knowledge development

Case studies play a significant role in knowledge development across various disciplines. Analysis of cases provides an avenue for researchers to explore phenomena within their context based on the collected data.

This can result in the production of rich, practical insights that can be instrumental in both theory-building and practice. Case studies allow researchers to delve into the intricacies and complexities of real-life situations, uncovering insights that might otherwise remain hidden.

Types of case studies

In qualitative research , a case study is not a one-size-fits-all approach. Depending on the nature of the research question and the specific objectives of the study, researchers might choose to use different types of case studies. These types differ in their focus, methodology, and the level of detail they provide about the phenomenon under investigation.

Understanding these types is crucial for selecting the most appropriate approach for your research project and effectively achieving your research goals. Let's briefly look at the main types of case studies.

Exploratory case studies

Exploratory case studies are typically conducted to develop a theory or framework around an understudied phenomenon. They can also serve as a precursor to a larger-scale research project. Exploratory case studies are useful when a researcher wants to identify the key issues or questions which can spur more extensive study or be used to develop propositions for further research. These case studies are characterized by flexibility, allowing researchers to explore various aspects of a phenomenon as they emerge, which can also form the foundation for subsequent studies.

Descriptive case studies

Descriptive case studies aim to provide a complete and accurate representation of a phenomenon or event within its context. These case studies are often based on an established theoretical framework, which guides how data is collected and analyzed. The researcher is concerned with describing the phenomenon in detail, as it occurs naturally, without trying to influence or manipulate it.

Explanatory case studies

Explanatory case studies are focused on explanation - they seek to clarify how or why certain phenomena occur. Often used in complex, real-life situations, they can be particularly valuable in clarifying causal relationships among concepts and understanding the interplay between different factors within a specific context.

Intrinsic, instrumental, and collective case studies

These three categories of case studies focus on the nature and purpose of the study. An intrinsic case study is conducted when a researcher has an inherent interest in the case itself. Instrumental case studies are employed when the case is used to provide insight into a particular issue or phenomenon. A collective case study, on the other hand, involves studying multiple cases simultaneously to investigate some general phenomena.

Each type of case study serves a different purpose and has its own strengths and challenges. The selection of the type should be guided by the research question and objectives, as well as the context and constraints of the research.

The flexibility, depth, and contextual richness offered by case studies make this approach an excellent research method for various fields of study. They enable researchers to investigate real-world phenomena within their specific contexts, capturing nuances that other research methods might miss. Across numerous fields, case studies provide valuable insights into complex issues.

Critical information systems research

Case studies provide a detailed understanding of the role and impact of information systems in different contexts. They offer a platform to explore how information systems are designed, implemented, and used and how they interact with various social, economic, and political factors. Case studies in this field often focus on examining the intricate relationship between technology, organizational processes, and user behavior, helping to uncover insights that can inform better system design and implementation.

Health research

Health research is another field where case studies are highly valuable. They offer a way to explore patient experiences, healthcare delivery processes, and the impact of various interventions in a real-world context.

Case studies can provide a deep understanding of a patient's journey, giving insights into the intricacies of disease progression, treatment effects, and the psychosocial aspects of health and illness.

Asthma research studies

Specifically within medical research, studies on asthma often employ case studies to explore the individual and environmental factors that influence asthma development, management, and outcomes. A case study can provide rich, detailed data about individual patients' experiences, from the triggers and symptoms they experience to the effectiveness of various management strategies. This can be crucial for developing patient-centered asthma care approaches.

Other fields

Apart from the fields mentioned, case studies are also extensively used in business and management research, education research, and political sciences, among many others. They provide an opportunity to delve into the intricacies of real-world situations, allowing for a comprehensive understanding of various phenomena.

Case studies, with their depth and contextual focus, offer unique insights across these varied fields. They allow researchers to illuminate the complexities of real-life situations, contributing to both theory and practice.

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Understanding the key elements of case study design is crucial for conducting rigorous and impactful case study research. A well-structured design guides the researcher through the process, ensuring that the study is methodologically sound and its findings are reliable and valid. The main elements of case study design include the research question , propositions, units of analysis, and the logic linking the data to the propositions.

The research question is the foundation of any research study. A good research question guides the direction of the study and informs the selection of the case, the methods of collecting data, and the analysis techniques. A well-formulated research question in case study research is typically clear, focused, and complex enough to merit further detailed examination of the relevant case(s).

Propositions

Propositions, though not necessary in every case study, provide a direction by stating what we might expect to find in the data collected. They guide how data is collected and analyzed by helping researchers focus on specific aspects of the case. They are particularly important in explanatory case studies, which seek to understand the relationships among concepts within the studied phenomenon.

Units of analysis

The unit of analysis refers to the case, or the main entity or entities that are being analyzed in the study. In case study research, the unit of analysis can be an individual, a group, an organization, a decision, an event, or even a time period. It's crucial to clearly define the unit of analysis, as it shapes the qualitative data analysis process by allowing the researcher to analyze a particular case and synthesize analysis across multiple case studies to draw conclusions.

Argumentation

This refers to the inferential model that allows researchers to draw conclusions from the data. The researcher needs to ensure that there is a clear link between the data, the propositions (if any), and the conclusions drawn. This argumentation is what enables the researcher to make valid and credible inferences about the phenomenon under study.

Understanding and carefully considering these elements in the design phase of a case study can significantly enhance the quality of the research. It can help ensure that the study is methodologically sound and its findings contribute meaningful insights about the case.

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Conducting a case study involves several steps, from defining the research question and selecting the case to collecting and analyzing data . This section outlines these key stages, providing a practical guide on how to conduct case study research.

Defining the research question

The first step in case study research is defining a clear, focused research question. This question should guide the entire research process, from case selection to analysis. It's crucial to ensure that the research question is suitable for a case study approach. Typically, such questions are exploratory or descriptive in nature and focus on understanding a phenomenon within its real-life context.

Selecting and defining the case

The selection of the case should be based on the research question and the objectives of the study. It involves choosing a unique example or a set of examples that provide rich, in-depth data about the phenomenon under investigation. After selecting the case, it's crucial to define it clearly, setting the boundaries of the case, including the time period and the specific context.

Previous research can help guide the case study design. When considering a case study, an example of a case could be taken from previous case study research and used to define cases in a new research inquiry. Considering recently published examples can help understand how to select and define cases effectively.

Developing a detailed case study protocol

A case study protocol outlines the procedures and general rules to be followed during the case study. This includes the data collection methods to be used, the sources of data, and the procedures for analysis. Having a detailed case study protocol ensures consistency and reliability in the study.

The protocol should also consider how to work with the people involved in the research context to grant the research team access to collecting data. As mentioned in previous sections of this guide, establishing rapport is an essential component of qualitative research as it shapes the overall potential for collecting and analyzing data.

Collecting data

Gathering data in case study research often involves multiple sources of evidence, including documents, archival records, interviews, observations, and physical artifacts. This allows for a comprehensive understanding of the case. The process for gathering data should be systematic and carefully documented to ensure the reliability and validity of the study.

Analyzing and interpreting data

The next step is analyzing the data. This involves organizing the data , categorizing it into themes or patterns , and interpreting these patterns to answer the research question. The analysis might also involve comparing the findings with prior research or theoretical propositions.

Writing the case study report

The final step is writing the case study report . This should provide a detailed description of the case, the data, the analysis process, and the findings. The report should be clear, organized, and carefully written to ensure that the reader can understand the case and the conclusions drawn from it.

Each of these steps is crucial in ensuring that the case study research is rigorous, reliable, and provides valuable insights about the case.

The type, depth, and quality of data in your study can significantly influence the validity and utility of the study. In case study research, data is usually collected from multiple sources to provide a comprehensive and nuanced understanding of the case. This section will outline the various methods of collecting data used in case study research and discuss considerations for ensuring the quality of the data.

Interviews are a common method of gathering data in case study research. They can provide rich, in-depth data about the perspectives, experiences, and interpretations of the individuals involved in the case. Interviews can be structured , semi-structured , or unstructured , depending on the research question and the degree of flexibility needed.

Observations

Observations involve the researcher observing the case in its natural setting, providing first-hand information about the case and its context. Observations can provide data that might not be revealed in interviews or documents, such as non-verbal cues or contextual information.

Documents and artifacts

Documents and archival records provide a valuable source of data in case study research. They can include reports, letters, memos, meeting minutes, email correspondence, and various public and private documents related to the case.

These records can provide historical context, corroborate evidence from other sources, and offer insights into the case that might not be apparent from interviews or observations.

Physical artifacts refer to any physical evidence related to the case, such as tools, products, or physical environments. These artifacts can provide tangible insights into the case, complementing the data gathered from other sources.

Ensuring the quality of data collection

Determining the quality of data in case study research requires careful planning and execution. It's crucial to ensure that the data is reliable, accurate, and relevant to the research question. This involves selecting appropriate methods of collecting data, properly training interviewers or observers, and systematically recording and storing the data. It also includes considering ethical issues related to collecting and handling data, such as obtaining informed consent and ensuring the privacy and confidentiality of the participants.

Data analysis

Analyzing case study research involves making sense of the rich, detailed data to answer the research question. This process can be challenging due to the volume and complexity of case study data. However, a systematic and rigorous approach to analysis can ensure that the findings are credible and meaningful. This section outlines the main steps and considerations in analyzing data in case study research.

Organizing the data

The first step in the analysis is organizing the data. This involves sorting the data into manageable sections, often according to the data source or the theme. This step can also involve transcribing interviews, digitizing physical artifacts, or organizing observational data.

Categorizing and coding the data

Once the data is organized, the next step is to categorize or code the data. This involves identifying common themes, patterns, or concepts in the data and assigning codes to relevant data segments. Coding can be done manually or with the help of software tools, and in either case, qualitative analysis software can greatly facilitate the entire coding process. Coding helps to reduce the data to a set of themes or categories that can be more easily analyzed.

Identifying patterns and themes

After coding the data, the researcher looks for patterns or themes in the coded data. This involves comparing and contrasting the codes and looking for relationships or patterns among them. The identified patterns and themes should help answer the research question.

Interpreting the data

Once patterns and themes have been identified, the next step is to interpret these findings. This involves explaining what the patterns or themes mean in the context of the research question and the case. This interpretation should be grounded in the data, but it can also involve drawing on theoretical concepts or prior research.

Verification of the data

The last step in the analysis is verification. This involves checking the accuracy and consistency of the analysis process and confirming that the findings are supported by the data. This can involve re-checking the original data, checking the consistency of codes, or seeking feedback from research participants or peers.

Like any research method , case study research has its strengths and limitations. Researchers must be aware of these, as they can influence the design, conduct, and interpretation of the study.

Understanding the strengths and limitations of case study research can also guide researchers in deciding whether this approach is suitable for their research question . This section outlines some of the key strengths and limitations of case study research.

Benefits include the following:

• Rich, detailed data: One of the main strengths of case study research is that it can generate rich, detailed data about the case. This can provide a deep understanding of the case and its context, which can be valuable in exploring complex phenomena.
• Flexibility: Case study research is flexible in terms of design , data collection , and analysis . A sufficient degree of flexibility allows the researcher to adapt the study according to the case and the emerging findings.
• Real-world context: Case study research involves studying the case in its real-world context, which can provide valuable insights into the interplay between the case and its context.
• Multiple sources of evidence: Case study research often involves collecting data from multiple sources , which can enhance the robustness and validity of the findings.

On the other hand, researchers should consider the following limitations:

• Generalizability: A common criticism of case study research is that its findings might not be generalizable to other cases due to the specificity and uniqueness of each case.
• Time and resource intensive: Case study research can be time and resource intensive due to the depth of the investigation and the amount of collected data.
• Complexity of analysis: The rich, detailed data generated in case study research can make analyzing the data challenging.
• Subjectivity: Given the nature of case study research, there may be a higher degree of subjectivity in interpreting the data , so researchers need to reflect on this and transparently convey to audiences how the research was conducted.

Being aware of these strengths and limitations can help researchers design and conduct case study research effectively and interpret and report the findings appropriately.

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• Case Study | Definition, Examples & Methods

Case Study | Definition, Examples & Methods

Published on 5 May 2022 by Shona McCombes . Revised on 30 January 2023.

A case study is a detailed study of a specific subject, such as a person, group, place, event, organisation, or phenomenon. Case studies are commonly used in social, educational, clinical, and business research.

A case study research design usually involves qualitative methods , but quantitative methods are sometimes also used. Case studies are good for describing , comparing, evaluating, and understanding different aspects of a research problem .

Table of contents

When to do a case study, step 1: select a case, step 2: build a theoretical framework, step 3: collect your data, step 4: describe and analyse the case.

A case study is an appropriate research design when you want to gain concrete, contextual, in-depth knowledge about a specific real-world subject. It allows you to explore the key characteristics, meanings, and implications of the case.

Case studies are often a good choice in a thesis or dissertation . They keep your project focused and manageable when you don’t have the time or resources to do large-scale research.

You might use just one complex case study where you explore a single subject in depth, or conduct multiple case studies to compare and illuminate different aspects of your research problem.

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Once you have developed your problem statement and research questions , you should be ready to choose the specific case that you want to focus on. A good case study should have the potential to:

• Provide new or unexpected insights into the subject
• Challenge or complicate existing assumptions and theories
• Propose practical courses of action to resolve a problem
• Open up new directions for future research

Unlike quantitative or experimental research, a strong case study does not require a random or representative sample. In fact, case studies often deliberately focus on unusual, neglected, or outlying cases which may shed new light on the research problem.

If you find yourself aiming to simultaneously investigate and solve an issue, consider conducting action research . As its name suggests, action research conducts research and takes action at the same time, and is highly iterative and flexible. 

However, you can also choose a more common or representative case to exemplify a particular category, experience, or phenomenon.

While case studies focus more on concrete details than general theories, they should usually have some connection with theory in the field. This way the case study is not just an isolated description, but is integrated into existing knowledge about the topic. It might aim to:

• Exemplify a theory by showing how it explains the case under investigation
• Expand on a theory by uncovering new concepts and ideas that need to be incorporated
• Challenge a theory by exploring an outlier case that doesn’t fit with established assumptions

To ensure that your analysis of the case has a solid academic grounding, you should conduct a literature review of sources related to the topic and develop a theoretical framework . This means identifying key concepts and theories to guide your analysis and interpretation.

There are many different research methods you can use to collect data on your subject. Case studies tend to focus on qualitative data using methods such as interviews, observations, and analysis of primary and secondary sources (e.g., newspaper articles, photographs, official records). Sometimes a case study will also collect quantitative data .

The aim is to gain as thorough an understanding as possible of the case and its context.

In writing up the case study, you need to bring together all the relevant aspects to give as complete a picture as possible of the subject.

How you report your findings depends on the type of research you are doing. Some case studies are structured like a standard scientific paper or thesis, with separate sections or chapters for the methods , results , and discussion .

Others are written in a more narrative style, aiming to explore the case from various angles and analyse its meanings and implications (for example, by using textual analysis or discourse analysis ).

In all cases, though, make sure to give contextual details about the case, connect it back to the literature and theory, and discuss how it fits into wider patterns or debates.

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Suppose a company receives a spike in the number of customer complaints, or medical experts discover an outbreak of illness affecting children but are not quite sure of the reason. In both cases, carrying out a case study could be the best way to get answers.

Organization

Case studies can be carried out across different disciplines, including education, medicine, sociology, and business.

Most case studies employ qualitative methods, but quantitative methods can also be used. Researchers can then describe, compare, evaluate, and identify patterns or cause-and-effect relationships between the various variables under study. They can then use this knowledge to decide what action to take. 

Another thing to note is that case studies are generally singular in their focus. This means they narrow focus to a particular area, making them highly subjective. You cannot always generalize the results of a case study and apply them to a larger population. However, they are valuable tools to illustrate a principle or develop a thesis.

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• What are the different types of case study designs?

Researchers can choose from a variety of case study designs. The design they choose is dependent on what questions they need to answer, the context of the research environment, how much data they already have, and what resources are available.

Here are the common types of case study design:

Explanatory

An explanatory case study is an initial explanation of the how or why that is behind something. This design is commonly used when studying a real-life phenomenon or event. Once the organization understands the reasons behind a phenomenon, it can then make changes to enhance or eliminate the variables causing it. 

Here is an example: How is co-teaching implemented in elementary schools? The title for a case study of this subject could be “Case Study of the Implementation of Co-Teaching in Elementary Schools.”

Descriptive

An illustrative or descriptive case study helps researchers shed light on an unfamiliar object or subject after a period of time. The case study provides an in-depth review of the issue at hand and adds real-world examples in the area the researcher wants the audience to understand. 

The researcher makes no inferences or causal statements about the object or subject under review. This type of design is often used to understand cultural shifts.

Here is an example: How did people cope with the 2004 Indian Ocean Tsunami? This case study could be titled "A Case Study of the 2004 Indian Ocean Tsunami and its Effect on the Indonesian Population."

Exploratory

Exploratory research is also called a pilot case study. It is usually the first step within a larger research project, often relying on questionnaires and surveys . Researchers use exploratory research to help narrow down their focus, define parameters, draft a specific research question , and/or identify variables in a larger study. This research design usually covers a wider area than others, and focuses on the ‘what’ and ‘who’ of a topic.

Here is an example: How do nutrition and socialization in early childhood affect learning in children? The title of the exploratory study may be “Case Study of the Effects of Nutrition and Socialization on Learning in Early Childhood.”

An intrinsic case study is specifically designed to look at a unique and special phenomenon. At the start of the study, the researcher defines the phenomenon and the uniqueness that differentiates it from others. 

In this case, researchers do not attempt to generalize, compare, or challenge the existing assumptions. Instead, they explore the unique variables to enhance understanding. Here is an example: “Case Study of Volcanic Lightning.”

This design can also be identified as a cumulative case study. It uses information from past studies or observations of groups of people in certain settings as the foundation of the new study. Given that it takes multiple areas into account, it allows for greater generalization than a single case study. 

The researchers also get an in-depth look at a particular subject from different viewpoints.  Here is an example: “Case Study of how PTSD affected Vietnam and Gulf War Veterans Differently Due to Advances in Military Technology.”

Critical instance

A critical case study incorporates both explanatory and intrinsic study designs. It does not have predetermined purposes beyond an investigation of the said subject. It can be used for a deeper explanation of the cause-and-effect relationship. It can also be used to question a common assumption or myth. 

The findings can then be used further to generalize whether they would also apply in a different environment.  Here is an example: “What Effect Does Prolonged Use of Social Media Have on the Mind of American Youth?”

Instrumental

Instrumental research attempts to achieve goals beyond understanding the object at hand. Researchers explore a larger subject through different, separate studies and use the findings to understand its relationship to another subject. This type of design also provides insight into an issue or helps refine a theory. 

For example, you may want to determine if violent behavior in children predisposes them to crime later in life. The focus is on the relationship between children and violent behavior, and why certain children do become violent. Here is an example: “Violence Breeds Violence: Childhood Exposure and Participation in Adult Crime.”

Evaluation case study design is employed to research the effects of a program, policy, or intervention, and assess its effectiveness and impact on future decision-making. 

For example, you might want to see whether children learn times tables quicker through an educational game on their iPad versus a more teacher-led intervention. Here is an example: “An Investigation of the Impact of an iPad Multiplication Game for Primary School Children.” 

• When do you use case studies?

Case studies are ideal when you want to gain a contextual, concrete, or in-depth understanding of a particular subject. It helps you understand the characteristics, implications, and meanings of the subject.

They are also an excellent choice for those writing a thesis or dissertation, as they help keep the project focused on a particular area when resources or time may be too limited to cover a wider one. You may have to conduct several case studies to explore different aspects of the subject in question and understand the problem.

• What are the steps to follow when conducting a case study?

1. Select a case

Once you identify the problem at hand and come up with questions, identify the case you will focus on. The study can provide insights into the subject at hand, challenge existing assumptions, propose a course of action, and/or open up new areas for further research.

2. Create a theoretical framework

While you will be focusing on a specific detail, the case study design you choose should be linked to existing knowledge on the topic. This prevents it from becoming an isolated description and allows for enhancing the existing information. 

It may expand the current theory by bringing up new ideas or concepts, challenge established assumptions, or exemplify a theory by exploring how it answers the problem at hand. A theoretical framework starts with a literature review of the sources relevant to the topic in focus. This helps in identifying key concepts to guide analysis and interpretation.

3. Collect the data

Case studies are frequently supplemented with qualitative data such as observations, interviews, and a review of both primary and secondary sources such as official records, news articles, and photographs. There may also be quantitative data —this data assists in understanding the case thoroughly.

4. Analyze your case

The results of the research depend on the research design. Most case studies are structured with chapters or topic headings for easy explanation and presentation. Others may be written as narratives to allow researchers to explore various angles of the topic and analyze its meanings and implications.

In all areas, always give a detailed contextual understanding of the case and connect it to the existing theory and literature before discussing how it fits into your problem area.

• What are some case study examples?

What are the best approaches for introducing our product into the Kenyan market?

How does the change in marketing strategy aid in increasing the sales volumes of product Y?

How can teachers enhance student participation in classrooms?

How does poverty affect literacy levels in children?

Case study topics

Case study of product marketing strategies in the Kenyan market

Case study of the effects of a marketing strategy change on product Y sales volumes

Case study of X school teachers that encourage active student participation in the classroom

Case study of the effects of poverty on literacy levels in children

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Research Methods and Design

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a research strategy whose characteristics include

• a focus on the interrelationships that constitute the context of a specific entity (such as an organization, event, phenomenon, or person),
• analysis of the relationship between the contextual factors and the entity being studied, and
• the explicit purpose of using those insights (of the interactions between contextual relationships and the entity in question) to generate theory and/or contribute to extant theory. 

SAGE Research Methods Videos

What is the value of working with case studies.

Professor Todd Landman explains how case studies can be used in research. He discusses the importance of choosing a case study correctly and warns about limitations of case study research.

This is just one segment in a series about case studies. You can find the rest of the series in our SAGE database, Research Methods:

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From David E. Gray \(2014\). Doing Research in the Real World \(3rd ed.\) London, UK: Sage.

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Qualitative Research Designs

Case study design, using case study design in the applied doctoral experience (ade), applicability of case study design to applied problem of practice, case study design references.

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The field of qualitative research there are a number of research designs (also referred to as “traditions” or “genres”), including case study, phenomenology, narrative inquiry, action research, ethnography, grounded theory, as well as a number of critical genres including Feminist theory, indigenous research, critical race theory and cultural studies. The choice of research design is directly tied to and must be aligned with your research problem and purpose. As Bloomberg & Volpe (2019) explain:

Choice of research design is directly tied to research problem and purpose. As the researcher, you actively create the link among problem, purpose, and design through a process of reflecting on problem and purpose, focusing on researchable questions, and considering how to best address these questions. Thinking along these lines affords a research study methodological congruence (p. 38).

Case study is an in-depth exploration from multiple perspectives of a bounded social phenomenon, be this a social system such as a program, event, institution, organization, or community (Stake, 1995, 2005; Yin, 2018). Case study is employed across disciplines, including education, health care, social work, sociology, and organizational studies. The purpose is to generate understanding and deep insights to inform professional practice, policy development, and community or social action (Bloomberg 2018).

Yin (2018) and Stake (1995, 2005), two of the key proponents of case study methodology, use different terms to describe case studies. Yin categorizes case studies as exploratory or descriptive . The former is used to explore those situations in which the intervention being evaluated has no clear single set of outcomes. The latter is used to describe an intervention or phenomenon and the real-life context in which it occurred. Stake identifies case studies as intrinsic or instrumental , and he proposes that a primary distinction in designing case studies is between single and multiple (or collective) case study designs. A single case study may be an instrumental case study (research focuses on an issue or concern in one bounded case) or an intrinsic case study (the focus is on the case itself because the case presents a unique situation). A longitudinal case study design is chosen when the researcher seeks to examine the same single case at two or more different points in time or to capture trends over time. A multiple case study design is used when a researcher seeks to determine the prevalence or frequency of a particular phenomenon. This approach is useful when cases are used for purposes of a cross-case analysis in order to compare, contrast, and synthesize perspectives regarding the same issue. The focus is on the analysis of diverse cases to determine how these confirm the findings within or between cases, or call the findings into question.

Case study affords significant interaction with research participants, providing an in-depth picture of the phenomenon (Bloomberg & Volpe, 2019). Research is extensive, drawing on multiple methods of data collection, and involves multiple data sources. Triangulation is critical in attempting to obtain an in-depth understanding of the phenomenon under study and adds rigor, breadth, and depth to the study and provides corroborative evidence of the data obtained. Analysis of data can be holistic or embedded—that is, dealing with the whole or parts of the case (Yin, 2018). With multiple cases the typical analytic strategy is to provide detailed description of themes within each case (within-case analysis), followed by thematic analysis across cases (cross-case analysis), providing insights regarding how individual cases are comparable along important dimensions. Research culminates in the production of a detailed description of a setting and its participants, accompanied by an analysis of the data for themes or patterns (Stake, 1995, 2005; Yin, 2018). In addition to thick, rich description, the researcher’s interpretations, conclusions, and recommendations contribute to the reader’s overall understanding of the case study.

Analysis of findings should show that the researcher has attended to all the data, should address the most significant aspects of the case, and should demonstrate familiarity with the prevailing thinking and discourse about the topic. The goal of case study design (as with all qualitative designs) is not generalizability but rather transferability —that is, how (if at all) and in what ways understanding and knowledge can be applied in similar contexts and settings. The qualitative researcher attempts to address the issue of transferability by way of thick, rich description that will provide the basis for a case or cases to have relevance and potential application across a broader context.

Qualitative research methods ask the questions of "what" and "how" a phenomenon is understood in a real-life context (Bloomberg & Volpe, 2019). In the education field, qualitative research methods uncover educational experiences and practices because qualitative research allows the researcher to reveal new knowledge and understanding. Moreover, qualitative descriptive case studies describe, analyze and interpret events that explain the reasoning behind specific phenomena (Bloomberg, 2018). As such, case study design can be the foundation for a rigorous study within the Applied Doctoral Experience (ADE).

Case study design is an appropriate research design to consider when conceptualizing and conducting a dissertation research study that is based on an applied problem of practice with inherent real-life educational implications. Case study researchers study current, real-life cases that are in progress so that they can gather accurate information that is current. This fits well with the ADE program, as students are typically exploring a problem of practice. Because of the flexibility of the methods used, a descriptive design provides the researcher with the opportunity to choose data collection methods that are best suited to a practice-based research purpose, and can include individual interviews, focus groups, observation, surveys, and critical incident questionnaires. Methods are triangulated to contribute to the study’s trustworthiness. In selecting the set of data collection methods, it is important that the researcher carefully consider the alignment between research questions and the type of data that is needed to address these. Each data source is one piece of the “puzzle,” that contributes to the researcher’s holistic understanding of a phenomenon. The various strands of data are woven together holistically to promote a deeper understanding of the case and its application to an educationally-based problem of practice.

Research studies within the Applied Doctoral Experience (ADE) will be practical in nature and focus on problems and issues that inform educational practice.  Many of the types of studies that fall within the ADE framework are exploratory, and align with case study design. Case study design fits very well with applied problems related to educational practice, as the following set of examples illustrate:

Elementary Bilingual Education Teachers’ Self-Efficacy in Teaching English Language Learners: A Qualitative Case Study

The problem to be addressed in the proposed study is that some elementary bilingual education teachers’ beliefs about their lack of preparedness to teach the English language may negatively impact the language proficiency skills of Hispanic ELLs (Ernst-Slavit & Wenger, 2016; Fuchs et al., 2018; Hoque, 2016). The purpose of the proposed qualitative descriptive case study was to explore the perspectives and experiences of elementary bilingual education teachers regarding their perceived lack of preparedness to teach the English language and how this may impact the language proficiency of Hispanic ELLs.

Exploring Minority Teachers Experiences Pertaining to their Value in Education: A Single Case Study of Teachers in New York City

The problem is that minority K-12 teachers are underrepresented in the United States, with research indicating that school leaders and teachers in schools that are populated mainly by black students, staffed mostly by white teachers who may be unprepared to deal with biases and stereotypes that are ingrained in schools (Egalite, Kisida, & Winters, 2015; Milligan & Howley, 2015). The purpose of this qualitative exploratory single case study was to develop a clearer understanding of minority teachers’ experiences concerning the under-representation of minority K-12 teachers in urban school districts in the United States since there are so few of them.

Exploring the Impact of an Urban Teacher Residency Program on Teachers’ Cultural Intelligence: A Qualitative Case Study

The problem to be addressed by this case study is that teacher candidates often report being unprepared and ill-equipped to effectively educate culturally diverse students (Skepple, 2015; Beutel, 2018). The purpose of this study was to explore and gain an in-depth understanding of the perceived impact of an urban teacher residency program in urban Iowa on teachers’ cultural competence using the cultural intelligence (CQ) framework (Earley & Ang, 2003).

Qualitative Case Study that Explores Self-Efficacy and Mentorship on Women in Academic Administrative Leadership Roles

The problem was that female school-level administrators might be less likely to experience mentorship, thereby potentially decreasing their self-efficacy (Bing & Smith, 2019; Brown, 2020; Grant, 2021). The purpose of this case study was to determine to what extent female school-level administrators in the United States who had a mentor have a sense of self-efficacy and to examine the relationship between mentorship and self-efficacy.

Suburban Teacher and Administrator Perceptions of Culturally Responsive Teaching to Promote Connectedness in Students of Color: A Qualitative Case Study

The problem to be addressed in this study is the racial discrimination experienced by students of color in suburban schools and the resulting negative school experience (Jara & Bloomsbury, 2020; Jones, 2019; Kohli et al., 2017; Wandix-White, 2020). The purpose of this case study is to explore how culturally responsive practices can counteract systemic racism and discrimination in suburban schools thereby meeting the needs of students of color by creating positive learning experiences. 

As you can see, all of these studies were well suited to qualitative case study design. In each of these studies, the applied research problem and research purpose were clearly grounded in educational practice as well as directly aligned with qualitative case study methodology. In the Applied Doctoral Experience (ADE), you will be focused on addressing or resolving an educationally relevant research problem of practice. As such, your case study, with clear boundaries, will be one that centers on a real-life authentic problem in your field of practice that you believe is in need of resolution or improvement, and that the outcome thereof will be educationally valuable.

Bloomberg, L. D. (2018). Case study method. In B. B. Frey (Ed.), The SAGE Encyclopedia of educational research, measurement, and evaluation (pp. 237–239). SAGE. https://go.openathens.net/redirector/nu.edu?url=https%3A%2F%2Fmethods.sagepub.com%2FReference%2Fthe-sage-encyclopedia-of-educational-research-measurement-and-evaluation%2Fi4294.xml

Bloomberg, L. D. & Volpe, M. (2019). Completing your qualitative dissertation: A road map from beginning to end . (4th Ed.). SAGE.

Stake, R. E. (1995). The art of case study research. SAGE.

Stake, R. E. (2005). Qualitative case studies. In N. K. Denzin and Y. S. Lincoln (Eds.), The SAGE handbook of qualitative research (3rd ed., pp. 443–466). SAGE.

Yin, R. (2018). Case study research and applications: Designs and methods. SAGE.

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Continuing to enhance the quality of case study methodology in health services research

Shannon l. sibbald.

1 Faculty of Health Sciences, Western University, London, Ontario, Canada.

2 Department of Family Medicine, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada.

3 The Schulich Interfaculty Program in Public Health, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada.

Stefan Paciocco

Meghan fournie, rachelle van asseldonk, tiffany scurr.

Case study methodology has grown in popularity within Health Services Research (HSR). However, its use and merit as a methodology are frequently criticized due to its flexible approach and inconsistent application. Nevertheless, case study methodology is well suited to HSR because it can track and examine complex relationships, contexts, and systems as they evolve. Applied appropriately, it can help generate information on how multiple forms of knowledge come together to inform decision-making within healthcare contexts. In this article, we aim to demystify case study methodology by outlining its philosophical underpinnings and three foundational approaches. We provide literature-based guidance to decision-makers, policy-makers, and health leaders on how to engage in and critically appraise case study design. We advocate that researchers work in collaboration with health leaders to detail their research process with an aim of strengthening the validity and integrity of case study for its continued and advanced use in HSR.

Introduction

The popularity of case study research methodology in Health Services Research (HSR) has grown over the past 40 years. 1 This may be attributed to a shift towards the use of implementation research and a newfound appreciation of contextual factors affecting the uptake of evidence-based interventions within diverse settings. 2 Incorporating context-specific information on the delivery and implementation of programs can increase the likelihood of success. 3 , 4 Case study methodology is particularly well suited for implementation research in health services because it can provide insight into the nuances of diverse contexts. 5 , 6 In 1999, Yin 7 published a paper on how to enhance the quality of case study in HSR, which was foundational for the emergence of case study in this field. Yin 7 maintains case study is an appropriate methodology in HSR because health systems are constantly evolving, and the multiple affiliations and diverse motivations are difficult to track and understand with traditional linear methodologies.

Despite its increased popularity, there is debate whether a case study is a methodology (ie, a principle or process that guides research) or a method (ie, a tool to answer research questions). Some criticize case study for its high level of flexibility, perceiving it as less rigorous, and maintain that it generates inadequate results. 8 Others have noted issues with quality and consistency in how case studies are conducted and reported. 9 Reporting is often varied and inconsistent, using a mix of approaches such as case reports, case findings, and/or case study. Authors sometimes use incongruent methods of data collection and analysis or use the case study as a default when other methodologies do not fit. 9 , 10 Despite these criticisms, case study methodology is becoming more common as a viable approach for HSR. 11 An abundance of articles and textbooks are available to guide researchers through case study research, including field-specific resources for business, 12 , 13 nursing, 14 and family medicine. 15 However, there remains confusion and a lack of clarity on the key tenets of case study methodology.

Several common philosophical underpinnings have contributed to the development of case study research 1 which has led to different approaches to planning, data collection, and analysis. This presents challenges in assessing quality and rigour for researchers conducting case studies and stakeholders reading results.

This article discusses the various approaches and philosophical underpinnings to case study methodology. Our goal is to explain it in a way that provides guidance for decision-makers, policy-makers, and health leaders on how to understand, critically appraise, and engage in case study research and design, as such guidance is largely absent in the literature. This article is by no means exhaustive or authoritative. Instead, we aim to provide guidance and encourage dialogue around case study methodology, facilitating critical thinking around the variety of approaches and ways quality and rigour can be bolstered for its use within HSR.

Purpose of case study methodology

Case study methodology is often used to develop an in-depth, holistic understanding of a specific phenomenon within a specified context. 11 It focuses on studying one or multiple cases over time and uses an in-depth analysis of multiple information sources. 16 , 17 It is ideal for situations including, but not limited to, exploring under-researched and real-life phenomena, 18 especially when the contexts are complex and the researcher has little control over the phenomena. 19 , 20 Case studies can be useful when researchers want to understand how interventions are implemented in different contexts, and how context shapes the phenomenon of interest.

In addition to demonstrating coherency with the type of questions case study is suited to answer, there are four key tenets to case study methodologies: (1) be transparent in the paradigmatic and theoretical perspectives influencing study design; (2) clearly define the case and phenomenon of interest; (3) clearly define and justify the type of case study design; and (4) use multiple data collection sources and analysis methods to present the findings in ways that are consistent with the methodology and the study’s paradigmatic base. 9 , 16 The goal is to appropriately match the methods to empirical questions and issues and not to universally advocate any single approach for all problems. 21

Approaches to case study methodology

Three authors propose distinct foundational approaches to case study methodology positioned within different paradigms: Yin, 19 , 22 Stake, 5 , 23 and Merriam 24 , 25 ( Table 1 ). Yin is strongly post-positivist whereas Stake and Merriam are grounded in a constructivist paradigm. Researchers should locate their research within a paradigm that explains the philosophies guiding their research 26 and adhere to the underlying paradigmatic assumptions and key tenets of the appropriate author’s methodology. This will enhance the consistency and coherency of the methods and findings. However, researchers often do not report their paradigmatic position, nor do they adhere to one approach. 9 Although deliberately blending methodologies may be defensible and methodologically appropriate, more often it is done in an ad hoc and haphazard way, without consideration for limitations.

Cross-analysis of three case study approaches, adapted from Yazan 2015

The post-positive paradigm postulates there is one reality that can be objectively described and understood by “bracketing” oneself from the research to remove prejudice or bias. 27 Yin focuses on general explanation and prediction, emphasizing the formulation of propositions, akin to hypothesis testing. This approach is best suited for structured and objective data collection 9 , 11 and is often used for mixed-method studies.

Constructivism assumes that the phenomenon of interest is constructed and influenced by local contexts, including the interaction between researchers, individuals, and their environment. 27 It acknowledges multiple interpretations of reality 24 constructed within the context by the researcher and participants which are unlikely to be replicated, should either change. 5 , 20 Stake and Merriam’s constructivist approaches emphasize a story-like rendering of a problem and an iterative process of constructing the case study. 7 This stance values researcher reflexivity and transparency, 28 acknowledging how researchers’ experiences and disciplinary lenses influence their assumptions and beliefs about the nature of the phenomenon and development of the findings.

Defining a case

A key tenet of case study methodology often underemphasized in literature is the importance of defining the case and phenomenon. Researches should clearly describe the case with sufficient detail to allow readers to fully understand the setting and context and determine applicability. Trying to answer a question that is too broad often leads to an unclear definition of the case and phenomenon. 20 Cases should therefore be bound by time and place to ensure rigor and feasibility. 6

Yin 22 defines a case as “a contemporary phenomenon within its real-life context,” (p13) which may contain a single unit of analysis, including individuals, programs, corporations, or clinics 29 (holistic), or be broken into sub-units of analysis, such as projects, meetings, roles, or locations within the case (embedded). 30 Merriam 24 and Stake 5 similarly define a case as a single unit studied within a bounded system. Stake 5 , 23 suggests bounding cases by contexts and experiences where the phenomenon of interest can be a program, process, or experience. However, the line between the case and phenomenon can become muddy. For guidance, Stake 5 , 23 describes the case as the noun or entity and the phenomenon of interest as the verb, functioning, or activity of the case.

Designing the case study approach

Yin’s approach to a case study is rooted in a formal proposition or theory which guides the case and is used to test the outcome. 1 Stake 5 advocates for a flexible design and explicitly states that data collection and analysis may commence at any point. Merriam’s 24 approach blends both Yin and Stake’s, allowing the necessary flexibility in data collection and analysis to meet the needs.

Yin 30 proposed three types of case study approaches—descriptive, explanatory, and exploratory. Each can be designed around single or multiple cases, creating six basic case study methodologies. Descriptive studies provide a rich description of the phenomenon within its context, which can be helpful in developing theories. To test a theory or determine cause and effect relationships, researchers can use an explanatory design. An exploratory model is typically used in the pilot-test phase to develop propositions (eg, Sibbald et al. 31 used this approach to explore interprofessional network complexity). Despite having distinct characteristics, the boundaries between case study types are flexible with significant overlap. 30 Each has five key components: (1) research question; (2) proposition; (3) unit of analysis; (4) logical linking that connects the theory with proposition; and (5) criteria for analyzing findings.

Contrary to Yin, Stake 5 believes the research process cannot be planned in its entirety because research evolves as it is performed. Consequently, researchers can adjust the design of their methods even after data collection has begun. Stake 5 classifies case studies into three categories: intrinsic, instrumental, and collective/multiple. Intrinsic case studies focus on gaining a better understanding of the case. These are often undertaken when the researcher has an interest in a specific case. Instrumental case study is used when the case itself is not of the utmost importance, and the issue or phenomenon (ie, the research question) being explored becomes the focus instead (eg, Paciocco 32 used an instrumental case study to evaluate the implementation of a chronic disease management program). 5 Collective designs are rooted in an instrumental case study and include multiple cases to gain an in-depth understanding of the complexity and particularity of a phenomenon across diverse contexts. 5 , 23 In collective designs, studying similarities and differences between the cases allows the phenomenon to be understood more intimately (for examples of this in the field, see van Zelm et al. 33 and Burrows et al. 34 In addition, Sibbald et al. 35 present an example where a cross-case analysis method is used to compare instrumental cases).

Merriam’s approach is flexible (similar to Stake) as well as stepwise and linear (similar to Yin). She advocates for conducting a literature review before designing the study to better understand the theoretical underpinnings. 24 , 25 Unlike Stake or Yin, Merriam proposes a step-by-step guide for researchers to design a case study. These steps include performing a literature review, creating a theoretical framework, identifying the problem, creating and refining the research question(s), and selecting a study sample that fits the question(s). 24 , 25 , 36

Data collection and analysis

Using multiple data collection methods is a key characteristic of all case study methodology; it enhances the credibility of the findings by allowing different facets and views of the phenomenon to be explored. 23 Common methods include interviews, focus groups, observation, and document analysis. 5 , 37 By seeking patterns within and across data sources, a thick description of the case can be generated to support a greater understanding and interpretation of the whole phenomenon. 5 , 17 , 20 , 23 This technique is called triangulation and is used to explore cases with greater accuracy. 5 Although Stake 5 maintains case study is most often used in qualitative research, Yin 17 supports a mix of both quantitative and qualitative methods to triangulate data. This deliberate convergence of data sources (or mixed methods) allows researchers to find greater depth in their analysis and develop converging lines of inquiry. For example, case studies evaluating interventions commonly use qualitative interviews to describe the implementation process, barriers, and facilitators paired with a quantitative survey of comparative outcomes and effectiveness. 33 , 38 , 39

Yin 30 describes analysis as dependent on the chosen approach, whether it be (1) deductive and rely on theoretical propositions; (2) inductive and analyze data from the “ground up”; (3) organized to create a case description; or (4) used to examine plausible rival explanations. According to Yin’s 40 approach to descriptive case studies, carefully considering theory development is an important part of study design. “Theory” refers to field-relevant propositions, commonly agreed upon assumptions, or fully developed theories. 40 Stake 5 advocates for using the researcher’s intuition and impression to guide analysis through a categorical aggregation and direct interpretation. Merriam 24 uses six different methods to guide the “process of making meaning” (p178) : (1) ethnographic analysis; (2) narrative analysis; (3) phenomenological analysis; (4) constant comparative method; (5) content analysis; and (6) analytic induction.

Drawing upon a theoretical or conceptual framework to inform analysis improves the quality of case study and avoids the risk of description without meaning. 18 Using Stake’s 5 approach, researchers rely on protocols and previous knowledge to help make sense of new ideas; theory can guide the research and assist researchers in understanding how new information fits into existing knowledge.

Practical applications of case study research

Columbia University has recently demonstrated how case studies can help train future health leaders. 41 Case studies encompass components of systems thinking—considering connections and interactions between components of a system, alongside the implications and consequences of those relationships—to equip health leaders with tools to tackle global health issues. 41 Greenwood 42 evaluated Indigenous peoples’ relationship with the healthcare system in British Columbia and used a case study to challenge and educate health leaders across the country to enhance culturally sensitive health service environments.

An important but often omitted step in case study research is an assessment of quality and rigour. We recommend using a framework or set of criteria to assess the rigour of the qualitative research. Suitable resources include Caelli et al., 43 Houghten et al., 44 Ravenek and Rudman, 45 and Tracy. 46

New directions in case study

Although “pragmatic” case studies (ie, utilizing practical and applicable methods) have existed within psychotherapy for some time, 47 , 48 only recently has the applicability of pragmatism as an underlying paradigmatic perspective been considered in HSR. 49 This is marked by uptake of pragmatism in Randomized Control Trials, recognizing that “gold standard” testing conditions do not reflect the reality of clinical settings 50 , 51 nor do a handful of epistemologically guided methodologies suit every research inquiry.

Pragmatism positions the research question as the basis for methodological choices, rather than a theory or epistemology, allowing researchers to pursue the most practical approach to understanding a problem or discovering an actionable solution. 52 Mixed methods are commonly used to create a deeper understanding of the case through converging qualitative and quantitative data. 52 Pragmatic case study is suited to HSR because its flexibility throughout the research process accommodates complexity, ever-changing systems, and disruptions to research plans. 49 , 50 Much like case study, pragmatism has been criticized for its flexibility and use when other approaches are seemingly ill-fit. 53 , 54 Similarly, authors argue that this results from a lack of investigation and proper application rather than a reflection of validity, legitimizing the need for more exploration and conversation among researchers and practitioners. 55

Although occasionally misunderstood as a less rigourous research methodology, 8 case study research is highly flexible and allows for contextual nuances. 5 , 6 Its use is valuable when the researcher desires a thorough understanding of a phenomenon or case bound by context. 11 If needed, multiple similar cases can be studied simultaneously, or one case within another. 16 , 17 There are currently three main approaches to case study, 5 , 17 , 24 each with their own definitions of a case, ontological and epistemological paradigms, methodologies, and data collection and analysis procedures. 37

Individuals’ experiences within health systems are influenced heavily by contextual factors, participant experience, and intricate relationships between different organizations and actors. 55 Case study research is well suited for HSR because it can track and examine these complex relationships and systems as they evolve over time. 6 , 7 It is important that researchers and health leaders using this methodology understand its key tenets and how to conduct a proper case study. Although there are many examples of case study in action, they are often under-reported and, when reported, not rigorously conducted. 9 Thus, decision-makers and health leaders should use these examples with caution. The proper reporting of case studies is necessary to bolster their credibility in HSR literature and provide readers sufficient information to critically assess the methodology. We also call on health leaders who frequently use case studies 56 – 58 to report them in the primary research literature.

The purpose of this article is to advocate for the continued and advanced use of case study in HSR and to provide literature-based guidance for decision-makers, policy-makers, and health leaders on how to engage in, read, and interpret findings from case study research. As health systems progress and evolve, the application of case study research will continue to increase as researchers and health leaders aim to capture the inherent complexities, nuances, and contextual factors. 7

• Open access
• Published: 27 June 2011

The case study approach

• Sarah Crowe 1 ,
• Kathrin Cresswell 2 ,
• Ann Robertson 2 ,
• Guro Huby 3 ,
• Anthony Avery 1 &
• Aziz Sheikh 2  

BMC Medical Research Methodology volume  11 , Article number:  100 ( 2011 ) Cite this article

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The case study approach allows in-depth, multi-faceted explorations of complex issues in their real-life settings. The value of the case study approach is well recognised in the fields of business, law and policy, but somewhat less so in health services research. Based on our experiences of conducting several health-related case studies, we reflect on the different types of case study design, the specific research questions this approach can help answer, the data sources that tend to be used, and the particular advantages and disadvantages of employing this methodological approach. The paper concludes with key pointers to aid those designing and appraising proposals for conducting case study research, and a checklist to help readers assess the quality of case study reports.

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Introduction

The case study approach is particularly useful to employ when there is a need to obtain an in-depth appreciation of an issue, event or phenomenon of interest, in its natural real-life context. Our aim in writing this piece is to provide insights into when to consider employing this approach and an overview of key methodological considerations in relation to the design, planning, analysis, interpretation and reporting of case studies.

The illustrative 'grand round', 'case report' and 'case series' have a long tradition in clinical practice and research. Presenting detailed critiques, typically of one or more patients, aims to provide insights into aspects of the clinical case and, in doing so, illustrate broader lessons that may be learnt. In research, the conceptually-related case study approach can be used, for example, to describe in detail a patient's episode of care, explore professional attitudes to and experiences of a new policy initiative or service development or more generally to 'investigate contemporary phenomena within its real-life context' [ 1 ]. Based on our experiences of conducting a range of case studies, we reflect on when to consider using this approach, discuss the key steps involved and illustrate, with examples, some of the practical challenges of attaining an in-depth understanding of a 'case' as an integrated whole. In keeping with previously published work, we acknowledge the importance of theory to underpin the design, selection, conduct and interpretation of case studies[ 2 ]. In so doing, we make passing reference to the different epistemological approaches used in case study research by key theoreticians and methodologists in this field of enquiry.

This paper is structured around the following main questions: What is a case study? What are case studies used for? How are case studies conducted? What are the potential pitfalls and how can these be avoided? We draw in particular on four of our own recently published examples of case studies (see Tables 1 , 2 , 3 and 4 ) and those of others to illustrate our discussion[ 3 – 7 ].

What is a case study?

A case study is a research approach that is used to generate an in-depth, multi-faceted understanding of a complex issue in its real-life context. It is an established research design that is used extensively in a wide variety of disciplines, particularly in the social sciences. A case study can be defined in a variety of ways (Table 5 ), the central tenet being the need to explore an event or phenomenon in depth and in its natural context. It is for this reason sometimes referred to as a "naturalistic" design; this is in contrast to an "experimental" design (such as a randomised controlled trial) in which the investigator seeks to exert control over and manipulate the variable(s) of interest.

Stake's work has been particularly influential in defining the case study approach to scientific enquiry. He has helpfully characterised three main types of case study: intrinsic , instrumental and collective [ 8 ]. An intrinsic case study is typically undertaken to learn about a unique phenomenon. The researcher should define the uniqueness of the phenomenon, which distinguishes it from all others. In contrast, the instrumental case study uses a particular case (some of which may be better than others) to gain a broader appreciation of an issue or phenomenon. The collective case study involves studying multiple cases simultaneously or sequentially in an attempt to generate a still broader appreciation of a particular issue.

These are however not necessarily mutually exclusive categories. In the first of our examples (Table 1 ), we undertook an intrinsic case study to investigate the issue of recruitment of minority ethnic people into the specific context of asthma research studies, but it developed into a instrumental case study through seeking to understand the issue of recruitment of these marginalised populations more generally, generating a number of the findings that are potentially transferable to other disease contexts[ 3 ]. In contrast, the other three examples (see Tables 2 , 3 and 4 ) employed collective case study designs to study the introduction of workforce reconfiguration in primary care, the implementation of electronic health records into hospitals, and to understand the ways in which healthcare students learn about patient safety considerations[ 4 – 6 ]. Although our study focusing on the introduction of General Practitioners with Specialist Interests (Table 2 ) was explicitly collective in design (four contrasting primary care organisations were studied), is was also instrumental in that this particular professional group was studied as an exemplar of the more general phenomenon of workforce redesign[ 4 ].

What are case studies used for?

According to Yin, case studies can be used to explain, describe or explore events or phenomena in the everyday contexts in which they occur[ 1 ]. These can, for example, help to understand and explain causal links and pathways resulting from a new policy initiative or service development (see Tables 2 and 3 , for example)[ 1 ]. In contrast to experimental designs, which seek to test a specific hypothesis through deliberately manipulating the environment (like, for example, in a randomised controlled trial giving a new drug to randomly selected individuals and then comparing outcomes with controls),[ 9 ] the case study approach lends itself well to capturing information on more explanatory ' how ', 'what' and ' why ' questions, such as ' how is the intervention being implemented and received on the ground?'. The case study approach can offer additional insights into what gaps exist in its delivery or why one implementation strategy might be chosen over another. This in turn can help develop or refine theory, as shown in our study of the teaching of patient safety in undergraduate curricula (Table 4 )[ 6 , 10 ]. Key questions to consider when selecting the most appropriate study design are whether it is desirable or indeed possible to undertake a formal experimental investigation in which individuals and/or organisations are allocated to an intervention or control arm? Or whether the wish is to obtain a more naturalistic understanding of an issue? The former is ideally studied using a controlled experimental design, whereas the latter is more appropriately studied using a case study design.

Case studies may be approached in different ways depending on the epistemological standpoint of the researcher, that is, whether they take a critical (questioning one's own and others' assumptions), interpretivist (trying to understand individual and shared social meanings) or positivist approach (orientating towards the criteria of natural sciences, such as focusing on generalisability considerations) (Table 6 ). Whilst such a schema can be conceptually helpful, it may be appropriate to draw on more than one approach in any case study, particularly in the context of conducting health services research. Doolin has, for example, noted that in the context of undertaking interpretative case studies, researchers can usefully draw on a critical, reflective perspective which seeks to take into account the wider social and political environment that has shaped the case[ 11 ].

How are case studies conducted?

Here, we focus on the main stages of research activity when planning and undertaking a case study; the crucial stages are: defining the case; selecting the case(s); collecting and analysing the data; interpreting data; and reporting the findings.

Defining the case

Carefully formulated research question(s), informed by the existing literature and a prior appreciation of the theoretical issues and setting(s), are all important in appropriately and succinctly defining the case[ 8 , 12 ]. Crucially, each case should have a pre-defined boundary which clarifies the nature and time period covered by the case study (i.e. its scope, beginning and end), the relevant social group, organisation or geographical area of interest to the investigator, the types of evidence to be collected, and the priorities for data collection and analysis (see Table 7 )[ 1 ]. A theory driven approach to defining the case may help generate knowledge that is potentially transferable to a range of clinical contexts and behaviours; using theory is also likely to result in a more informed appreciation of, for example, how and why interventions have succeeded or failed[ 13 ].

For example, in our evaluation of the introduction of electronic health records in English hospitals (Table 3 ), we defined our cases as the NHS Trusts that were receiving the new technology[ 5 ]. Our focus was on how the technology was being implemented. However, if the primary research interest had been on the social and organisational dimensions of implementation, we might have defined our case differently as a grouping of healthcare professionals (e.g. doctors and/or nurses). The precise beginning and end of the case may however prove difficult to define. Pursuing this same example, when does the process of implementation and adoption of an electronic health record system really begin or end? Such judgements will inevitably be influenced by a range of factors, including the research question, theory of interest, the scope and richness of the gathered data and the resources available to the research team.

Selecting the case(s)

The decision on how to select the case(s) to study is a very important one that merits some reflection. In an intrinsic case study, the case is selected on its own merits[ 8 ]. The case is selected not because it is representative of other cases, but because of its uniqueness, which is of genuine interest to the researchers. This was, for example, the case in our study of the recruitment of minority ethnic participants into asthma research (Table 1 ) as our earlier work had demonstrated the marginalisation of minority ethnic people with asthma, despite evidence of disproportionate asthma morbidity[ 14 , 15 ]. In another example of an intrinsic case study, Hellstrom et al.[ 16 ] studied an elderly married couple living with dementia to explore how dementia had impacted on their understanding of home, their everyday life and their relationships.

For an instrumental case study, selecting a "typical" case can work well[ 8 ]. In contrast to the intrinsic case study, the particular case which is chosen is of less importance than selecting a case that allows the researcher to investigate an issue or phenomenon. For example, in order to gain an understanding of doctors' responses to health policy initiatives, Som undertook an instrumental case study interviewing clinicians who had a range of responsibilities for clinical governance in one NHS acute hospital trust[ 17 ]. Sampling a "deviant" or "atypical" case may however prove even more informative, potentially enabling the researcher to identify causal processes, generate hypotheses and develop theory.

In collective or multiple case studies, a number of cases are carefully selected. This offers the advantage of allowing comparisons to be made across several cases and/or replication. Choosing a "typical" case may enable the findings to be generalised to theory (i.e. analytical generalisation) or to test theory by replicating the findings in a second or even a third case (i.e. replication logic)[ 1 ]. Yin suggests two or three literal replications (i.e. predicting similar results) if the theory is straightforward and five or more if the theory is more subtle. However, critics might argue that selecting 'cases' in this way is insufficiently reflexive and ill-suited to the complexities of contemporary healthcare organisations.

The selected case study site(s) should allow the research team access to the group of individuals, the organisation, the processes or whatever else constitutes the chosen unit of analysis for the study. Access is therefore a central consideration; the researcher needs to come to know the case study site(s) well and to work cooperatively with them. Selected cases need to be not only interesting but also hospitable to the inquiry [ 8 ] if they are to be informative and answer the research question(s). Case study sites may also be pre-selected for the researcher, with decisions being influenced by key stakeholders. For example, our selection of case study sites in the evaluation of the implementation and adoption of electronic health record systems (see Table 3 ) was heavily influenced by NHS Connecting for Health, the government agency that was responsible for overseeing the National Programme for Information Technology (NPfIT)[ 5 ]. This prominent stakeholder had already selected the NHS sites (through a competitive bidding process) to be early adopters of the electronic health record systems and had negotiated contracts that detailed the deployment timelines.

It is also important to consider in advance the likely burden and risks associated with participation for those who (or the site(s) which) comprise the case study. Of particular importance is the obligation for the researcher to think through the ethical implications of the study (e.g. the risk of inadvertently breaching anonymity or confidentiality) and to ensure that potential participants/participating sites are provided with sufficient information to make an informed choice about joining the study. The outcome of providing this information might be that the emotive burden associated with participation, or the organisational disruption associated with supporting the fieldwork, is considered so high that the individuals or sites decide against participation.

In our example of evaluating implementations of electronic health record systems, given the restricted number of early adopter sites available to us, we sought purposively to select a diverse range of implementation cases among those that were available[ 5 ]. We chose a mixture of teaching, non-teaching and Foundation Trust hospitals, and examples of each of the three electronic health record systems procured centrally by the NPfIT. At one recruited site, it quickly became apparent that access was problematic because of competing demands on that organisation. Recognising the importance of full access and co-operative working for generating rich data, the research team decided not to pursue work at that site and instead to focus on other recruited sites.

Collecting the data

In order to develop a thorough understanding of the case, the case study approach usually involves the collection of multiple sources of evidence, using a range of quantitative (e.g. questionnaires, audits and analysis of routinely collected healthcare data) and more commonly qualitative techniques (e.g. interviews, focus groups and observations). The use of multiple sources of data (data triangulation) has been advocated as a way of increasing the internal validity of a study (i.e. the extent to which the method is appropriate to answer the research question)[ 8 , 18 – 21 ]. An underlying assumption is that data collected in different ways should lead to similar conclusions, and approaching the same issue from different angles can help develop a holistic picture of the phenomenon (Table 2 )[ 4 ].

Brazier and colleagues used a mixed-methods case study approach to investigate the impact of a cancer care programme[ 22 ]. Here, quantitative measures were collected with questionnaires before, and five months after, the start of the intervention which did not yield any statistically significant results. Qualitative interviews with patients however helped provide an insight into potentially beneficial process-related aspects of the programme, such as greater, perceived patient involvement in care. The authors reported how this case study approach provided a number of contextual factors likely to influence the effectiveness of the intervention and which were not likely to have been obtained from quantitative methods alone.

In collective or multiple case studies, data collection needs to be flexible enough to allow a detailed description of each individual case to be developed (e.g. the nature of different cancer care programmes), before considering the emerging similarities and differences in cross-case comparisons (e.g. to explore why one programme is more effective than another). It is important that data sources from different cases are, where possible, broadly comparable for this purpose even though they may vary in nature and depth.

Analysing, interpreting and reporting case studies

Making sense and offering a coherent interpretation of the typically disparate sources of data (whether qualitative alone or together with quantitative) is far from straightforward. Repeated reviewing and sorting of the voluminous and detail-rich data are integral to the process of analysis. In collective case studies, it is helpful to analyse data relating to the individual component cases first, before making comparisons across cases. Attention needs to be paid to variations within each case and, where relevant, the relationship between different causes, effects and outcomes[ 23 ]. Data will need to be organised and coded to allow the key issues, both derived from the literature and emerging from the dataset, to be easily retrieved at a later stage. An initial coding frame can help capture these issues and can be applied systematically to the whole dataset with the aid of a qualitative data analysis software package.

The Framework approach is a practical approach, comprising of five stages (familiarisation; identifying a thematic framework; indexing; charting; mapping and interpretation) , to managing and analysing large datasets particularly if time is limited, as was the case in our study of recruitment of South Asians into asthma research (Table 1 )[ 3 , 24 ]. Theoretical frameworks may also play an important role in integrating different sources of data and examining emerging themes. For example, we drew on a socio-technical framework to help explain the connections between different elements - technology; people; and the organisational settings within which they worked - in our study of the introduction of electronic health record systems (Table 3 )[ 5 ]. Our study of patient safety in undergraduate curricula drew on an evaluation-based approach to design and analysis, which emphasised the importance of the academic, organisational and practice contexts through which students learn (Table 4 )[ 6 ].

Case study findings can have implications both for theory development and theory testing. They may establish, strengthen or weaken historical explanations of a case and, in certain circumstances, allow theoretical (as opposed to statistical) generalisation beyond the particular cases studied[ 12 ]. These theoretical lenses should not, however, constitute a strait-jacket and the cases should not be "forced to fit" the particular theoretical framework that is being employed.

When reporting findings, it is important to provide the reader with enough contextual information to understand the processes that were followed and how the conclusions were reached. In a collective case study, researchers may choose to present the findings from individual cases separately before amalgamating across cases. Care must be taken to ensure the anonymity of both case sites and individual participants (if agreed in advance) by allocating appropriate codes or withholding descriptors. In the example given in Table 3 , we decided against providing detailed information on the NHS sites and individual participants in order to avoid the risk of inadvertent disclosure of identities[ 5 , 25 ].

What are the potential pitfalls and how can these be avoided?

The case study approach is, as with all research, not without its limitations. When investigating the formal and informal ways undergraduate students learn about patient safety (Table 4 ), for example, we rapidly accumulated a large quantity of data. The volume of data, together with the time restrictions in place, impacted on the depth of analysis that was possible within the available resources. This highlights a more general point of the importance of avoiding the temptation to collect as much data as possible; adequate time also needs to be set aside for data analysis and interpretation of what are often highly complex datasets.

Case study research has sometimes been criticised for lacking scientific rigour and providing little basis for generalisation (i.e. producing findings that may be transferable to other settings)[ 1 ]. There are several ways to address these concerns, including: the use of theoretical sampling (i.e. drawing on a particular conceptual framework); respondent validation (i.e. participants checking emerging findings and the researcher's interpretation, and providing an opinion as to whether they feel these are accurate); and transparency throughout the research process (see Table 8 )[ 8 , 18 – 21 , 23 , 26 ]. Transparency can be achieved by describing in detail the steps involved in case selection, data collection, the reasons for the particular methods chosen, and the researcher's background and level of involvement (i.e. being explicit about how the researcher has influenced data collection and interpretation). Seeking potential, alternative explanations, and being explicit about how interpretations and conclusions were reached, help readers to judge the trustworthiness of the case study report. Stake provides a critique checklist for a case study report (Table 9 )[ 8 ].

Conclusions

The case study approach allows, amongst other things, critical events, interventions, policy developments and programme-based service reforms to be studied in detail in a real-life context. It should therefore be considered when an experimental design is either inappropriate to answer the research questions posed or impossible to undertake. Considering the frequency with which implementations of innovations are now taking place in healthcare settings and how well the case study approach lends itself to in-depth, complex health service research, we believe this approach should be more widely considered by researchers. Though inherently challenging, the research case study can, if carefully conceptualised and thoughtfully undertaken and reported, yield powerful insights into many important aspects of health and healthcare delivery.

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Acknowledgements

We are grateful to the participants and colleagues who contributed to the individual case studies that we have drawn on. This work received no direct funding, but it has been informed by projects funded by Asthma UK, the NHS Service Delivery Organisation, NHS Connecting for Health Evaluation Programme, and Patient Safety Research Portfolio. We would also like to thank the expert reviewers for their insightful and constructive feedback. Our thanks are also due to Dr. Allison Worth who commented on an earlier draft of this manuscript.

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Sarah Crowe & Anthony Avery

Centre for Population Health Sciences, The University of Edinburgh, Edinburgh, UK

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AS conceived this article. SC, KC and AR wrote this paper with GH, AA and AS all commenting on various drafts. SC and AS are guarantors.

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Crowe, S., Cresswell, K., Robertson, A. et al. The case study approach. BMC Med Res Methodol 11 , 100 (2011). https://doi.org/10.1186/1471-2288-11-100

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Received : 29 November 2010

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Case Studies

Case studies are a popular research method in business area. Case studies aim to analyze specific issues within the boundaries of a specific environment, situation or organization.

According to its design, case studies in business research can be divided into three categories: explanatory, descriptive and exploratory.

Explanatory case studies aim to answer ‘how’ or ’why’ questions with little control on behalf of researcher over occurrence of events. This type of case studies focus on phenomena within the contexts of real-life situations. Example: “An investigation into the reasons of the global financial and economic crisis of 2008 – 2010.”

Descriptive case studies aim to analyze the sequence of interpersonal events after a certain amount of time has passed. Studies in business research belonging to this category usually describe culture or sub-culture, and they attempt to discover the key phenomena. Example: “Impact of increasing levels of multiculturalism on marketing practices: A case study of McDonald’s Indonesia.”

Exploratory case studies aim to find answers to the questions of ‘what’ or ‘who’. Exploratory case study data collection method is often accompanied by additional data collection method(s) such as interviews, questionnaires, experiments etc. Example: “A study into differences of leadership practices between private and public sector organizations in Atlanta, USA.”

Advantages of case study method include data collection and analysis within the context of phenomenon, integration of qualitative and quantitative data in data analysis, and the ability to capture complexities of real-life situations so that the phenomenon can be studied in greater levels of depth. Case studies do have certain disadvantages that may include lack of rigor, challenges associated with data analysis and very little basis for generalizations of findings and conclusions.

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Call for applications: Health Research at the Nexus of Humanitarian Crises and Climate Change

The Fogarty International Center of the U.S. National Institutes of Health (NIH) and partner organizations will host a Global Forum on Humanitarian Health Research (GFH2R) inclusive of public webinars and an in-person meeting in May 2025 (dates TBD) in Nairobi, Kenya.

GFH2R seeks to bring researchers and humanitarian organizations (including NGOs, local policymakers, and international agencies) together to share experiences and promote collaboration around health research in humanitarian settings. The theme for GFH2R 2025 is Health Research at the Nexus of Humanitarian Crises and Climate Change.

All interested applicants should review the information below and submit an application no later than October 7, 2024 on the application website . Note: Case study presenter applications will include a brief proposal.

This notice includes details on the following:

About GFH2R

Background and theme, case study overview, call for applications, eligibility, selection criteria.

• Application Checklist

Steering Committee

Definitions.

For questions about the call for applications or GFH2R, please email [email protected] .

For technical questions regarding the application submission system, please email [email protected] .

Humanitarian crises—including those resulting from armed conflict, forced migration and displacement, natural hazards, large-scale epidemics, and climate change—continue to proliferate globally and impact more people today than at any point in recorded history. To better meet the health needs of people affected by these events, humanitarian organizations need to act on reliable evidence. Unfortunately, there is limited scientific evidence available for these organizations to draw upon. Conducting health research in a humanitarian context is complex and uniquely challenging and has often been limited to small-scale pilots or evaluation in the past, which has resulted in a significant gap in evidence available to inform humanitarian policy and practice.

The Global Forum for Humanitarian Health Research (GFH2R) is a unique effort to address this gap. The Forum seeks to bring researchers and humanitarian organizations (including NGOs, local policymakers, and international agencies) together to share experiences and promote collaboration around health research in humanitarian settings. The 2025 meeting will be built around case study presentations by researchers from regions of the world affected by humanitarian crises. The Forum prioritizes the participation of researchers from low- and middle-income countries (LMICs), encourages networking and mentoring, and creates a venue for open and inclusive discussions.

GFH2R 2025 will consist of a series of public webinars and an in-person meeting in May 2025 (dates TBD). Compared to traditional scientific meetings, GFH2R is unique in that it is limited in size and built around small group discussions of case studies that are presented by researchers from settings affected by humanitarian crises. This format encourages open debate from varied perspectives, highlighting the voices of LMIC researchers. The model facilitates opportunities for networking amongst diverse participants for whom few formal, structured venues for interaction currently exist. Additionally, the involvement of research funders in the meeting will raise awareness among researchers of funding opportunities and help funders understand the unique challenges of humanitarian health research.

GFH2R is hosted by the Fogarty International Center at the U.S. National Institutes of Health in collaboration with the International Development Research Centre and Elrha.

Humanitarian crises are occurring in the context of climate change and its environmental consequences, such as increasing sea levels, temperatures, extreme weather events, droughts, flooding, and wildfires, all of which impact human health and livelihoods (see reference 1 ). Some consider climate change itself to be a humanitarian and health crisis, with increasingly complex, frequent, and unpredictable climate risks that compound existing vulnerabilities and inequities within populations and cause cascading emergencies across different systems and sectors (see reference 2 and reference 3 ). The evidence base on the links between climate change and human health has emphasized the meteorological impacts of climate change on adverse physical health outcomes, including infectious diseases and respiratory, cardiovascular, and neurological outcomes (see reference 1 ). However, much of this evidence draws from studies in high-income countries (see reference 4 ). There is a dearth of evidence from low- and middle-income countries (see reference 2 ), which have contributed the least to climate change but often bear the brunt of increasingly catastrophic events (see reference 5 ). There is also limited evidence on the impacts of climate change on mental health and broader social well-being (see reference 1 ).

Conducting health research in the context of humanitarian crises is already extremely challenging. Researchers may need to deal with safety and security concerns, political sensitivities, damaged or overwhelmed health systems, and a wide range of logistical challenges. Climate change acts as a “threat multiplier” and exacerbates the vulnerability of populations, making research in these contexts even more difficult.

In response to these realities, the theme of GFH2R is “Health Research at the Nexus of Humanitarian Crises and Climate Change.” The in-person meeting will be built upon in-depth case studies that describe research conducted at this nexus and share the challenges faced and strategies utilized by research teams.

Case Study Structure

For the purposes of GFH2R, a case study is a concise write up that provides insight into the planning and implementation of a funded research study. The case study will highlight challenges experienced and strategies employed throughout the research process. Unlike a traditional research paper focused on results and outcomes, a case study will provide an in-depth description of the research process and decision points throughout the study.

GFH2R case study proposals should describe an example of health research conducted at the nexus of humanitarian crises and climate change. Ideally, case studies should examine one of the sub-themes listed below but they may explore more than one sub-theme Case study applications are also free to explore the intersection of two sub-themes or discuss other issues associated with conducting health research at the nexus of humanitarian crises and climate change beyond the sub-themes listed. Case studies should be relevant to research in LMICs. 

• For more information on the GFH2R theme and sub-themes, please refer to the GFH2R Background Paper [PDF] .

GFH2R Meeting Sub-Themes

• Community engagement in research
• Equity in global research partnerships
• Academic-humanitarian collaboration
• Research methods innovation and adaptation in humanitarian settings
• Evidence use

Case study applications can be submitted under one of two categories:

• Research that is funded and will be complete by January 2025 or
• Research that is funded and still in progress after January 2025 that could benefit from feedback. 

Case study applications should not be based on research ideas or concepts that have not yet been implemented. However, applicants interested in sharing and discussing research ideas for future work should apply as a general participant as there will be other opportunities for these discussions during the in-person component of GFH2R.

For the purposes of GFH2R, “research” is inclusive of quantitative research, qualitative research, and mixed methods research, in addition to operational research.

GFH2R is seeking two types of participants for the meeting:

• Case study presenters will receive informal mentoring prior to the Forum and present case studies of their research experiences during the Forum.
• General participants will be selected based on geographic, disciplinary, and experiential diversity, to join the meeting and participate in small group discussions and networking activities.

Case Study Presenters

We invite applicants to submit case studies that highlight issues related to conducting health research at the nexus of humanitarian crises and climate change. We welcome health-related case studies from various perspectives, including researchers, policymakers, practitioners (including clinicians and healthcare workers), government representatives, humanitarian NGOs, and intergovernmental organizations. Priority will be given to applicants from LMICs, though applicants from high-income countries (HICs) may also apply and are encouraged to discuss the relevance of their work for research in LMICs.

Selected case study presenters will be paired with a mentor from the GFH2R Steering Committee to help develop their application into a brief paper (2-3 pages) and a PowerPoint presentation. During the GFH2R meeting, case study presenters from around the world will share their presentations and discuss cross-cutting issues. The meeting will also feature keynote speakers and networking opportunities.

Case study presenters can apply as teams of two individuals for a joint presentation. All case study presenter applicants must be meaningfully involved in the research that is presented.

General Participants

In addition to case study presenters, general participants will be selected by the Steering Committee to attend the in-person component of GFH2R. General participants will be selected to ensure broad geographical representation, a mix of disciplinary expertise, and a combination of people who are early in their careers and leaders in their fields. These individuals will be expected to participate in discussions, attend presentations, and join networking activities. There may also be informal opportunities for these individuals to present their ideas for future work at the meeting.

Applicants from HICs and LMICs are welcome, although priority will be given to applicants from LMICs and researchers who are living in the country or region affected by crises. Applications are welcome from all career levels, although early- to mid-career scientists or those who are new to the field of humanitarian health research will be prioritized. Applicants are not limited to academic researchers; staff from government, non-governmental organizations (NGOs), and private sector organizations are also encouraged to apply as long as their applications are focused on research.

All applicants must be able to submit an application in English, as GFH2R 2025 will be primarily held in English.

Note that travel to GFH2R, lodging, per diem, and visa costs for all accepted applicants (both case study presenters and general participants) will be fully sponsored.

The GFH2R Steering Committee will select successful case study presenters based on the following factors:

• Relevance of the case study to the meeting theme of “Health Research at the Nexus of Humanitarian Crises and Climate Change” and extent to which the proposed case study discusses how climate risks are compounding existing vulnerabilities and health impacts of humanitarian crises
• Scientific and public health significance of the case study for the field of humanitarian health
• Case study location (preference will be given to locations that are underrepresented in existing literature, e.g., LMICs)
• Diversity of the submitting applicant or team in terms of geographic location and area of expertise (preference will be given to applicants under-represented in the field).

Successful case presenter applicants are expected to fully participate in all mentorship activities and the complete in-person meeting.

The GFH2R Steering Committee will select successful general participants based on the following factors:

• Geographic location : Applications will be selected to ensure a representative distribution of participants from different regions of the world.
• Background/current area of expertise : Applicants will be selected for a diverse representation of different disciplines.
• Experience conducting research in the context of humanitarian settings : GFH2R is intended for early- to mid-career scientists or those who are new to humanitarian health research, though applications are welcome from all career and expertise levels.
• Reasons for attending the meeting : Participants should benefit from participating in the Forum and be able to actively contribute to discussions at the meeting.

Case study applicants who are not selected will automatically be submitted for consideration as general participants.

Applications are due by 23:59 ET (USA) on October 7, 2024.

All case study applicants will be informed of the Steering Committee’s decision in November 2024. All general participant applicants will be informed of the Steering Committee’s decision in December 2024. The decision of the committee will be final.

Tentative timeline

• August 2024 – Call for applications opens
• October 7, 2024 – Call for applications closes
• November 2024 – Case study applicants informed of status
• December 2024 – General participant applicants informed of status
• February – April 2025 – Steering Committee provides informal mentoring to presenters to develop and strengthen their case studies
• May 2025 – GFH2R (Dates TBD)

Application checklist

To apply as a case study presenter or general participant, visit the application submission site . Please use the following checklist to make sure you have provided all the requested information in your application, in English.

Deadline: Applications are due by 23:59 ET (USA) on October 7, 2024.

If you are unsure about the suitability of a case study application or would like to discuss your proposed case study further, please email [email protected] .

For technical questions regarding the application submission process, please email [email protected] .

Please ensure you include all the requested information as incomplete applications cannot be considered (see the checklist below). Applications received after the deadline will not be considered.

All applicants

All applicants must submit the following information:

• Contact information (email, phone)
• Affiliation/institution
• Country of residence and country of citizenship
• Highest degree earned
• Career level and discipline of expertise
• Why do you want to participate in the GFH2R meeting? (200-word limit)
• What would you uniquely contribute to the GFH2R meeting as a participant? How would you share meeting takeaways with your institution and local/regional partners? (400-word limit)
• Curriculum vitae (CV) or resume (5 pages maximum)

Case Study Presenter applicants

In addition to the items listed above, case study presenter applicants must submit a Case Study Proposal (2 pages maximum) which includes the following information:

• Name of partner if applying to present as a team (2 people max)
• Names of key collaborators and all relevant partners involved in the research
• Please indicate if the research study will be complete by January 2025 or still in progress after January 2025.
• Identify source of funding support
• Identify selected major sub-theme
• Identify selected minor subtheme(s) if applicable or other areas/topics explored
• Research question explored
• Public health challenge or disease area studied
• Importance of study
• Brief overview of results
• Location of study (if different from your own country of residence or citizenship, explain your connection to study location)
• Description of the humanitarian crisis
• Explanation of relevant climate risks/context affecting the study population
• Relevant facts about the host country/community
• Discussion of research issues. Refer to the theme descriptions and sub-themes for questions that could be addressed in this section.
• Conclusions and two lessons learned to be shared as recommendations with other researchers.
• Adam Levine, Brown University School for International and Public Affairs
• Catherine Lee, International Rescue Committee
• Chaza Akik, Independent public health research consultant
• Eliana Martinez-Herrera, National School of Public Health, Universidad de Antioquia
• Gillian McKay, Elrha
• Irene Torres, Inter-American Institute for Global Change Research
• John Jamir Benzon Aruta, De La Salle University
• Jura Augustinavicius, McGill University School of Population and Global Health
• Manuela A. Orjuela-Grimm, Columbia University
• Marie Roseline Darnycka Belizaire, World Health Organization
• Miriam Orcutt, World Health Organization
• Montasser Kamal, International Development Research Centre
• Patrick Opiyo Owili, African Population and Health Research Center
• Sabina Faiz Rashid, BRAC James P Grant School of Public Health, BRAC University
• Sasha Fahme, Weill Cornell Medicine
• Shannon Doocy, Johns Hopkins Bloomberg School of Public Health
• Thandi Kapwata, South African Medical Research Council
• Veena Pillai, Médecins Sans Frontières/Diode Consultancy
• Yasser Kamaledin, Médecins Sans Frontières – Netherlands

The following are definitions of some of the key terms related to the scope of the meeting and theme developed for the purposes of GFH2R.

Climate change refers to changes in global or regional climate patterns attributed largely to human-caused increased levels of atmospheric greenhouse gases and planetary warming. Climate drivers affect health outcomes directly through weather events such as extreme heat, wildfires, droughts, storm surges, and floods, but also indirectly through a series of exposure pathways such as air and water quality, food quality, infectious diseases, and massive population displacement events (see reference 6 ). Climate change can act as a cause of humanitarian crises and/or as a threat multiplier of health risks in humanitarian settings.

Humanitarian crises involve sudden or protracted events that disrupt and threaten lives and livelihoods on a large scale and require extensive assistance and/or response, broadly including armed conflict, forced migration and displacement, refugee crises, natural hazards and disasters (e.g., extreme weather events, earthquakes, and droughts), large-scale epidemics, and disease outbreaks.

Humanitarian health research is inclusive of health research conducted in the setting of a humanitarian crisis and/or health research with a population directly affected by a humanitarian crisis (e.g., a refugee population fleeing conflict, relocated to a more stable setting, which may be in LMICs or high-income countries (HICs)). Such research may explore the effects of humanitarian crises on health systems or populations in specific contexts.

Humanitarian settings include locations where humanitarian crises have occurred or settings with populations directly affected by humanitarian crises (e.g., a setting where refugees fleeing conflict reside).

Low- and middle-income country (LMIC) refers a country categorized in “low-income economies,” lower-middle-income economies,” or “upper-middle-income economies” based on gross national income per capita by the World Bank. We recognize this terminology is not ideal and fails to account for many of the nuanced differences between nations. For consistency however, this language matches the current general NIH terminology used in NIH program announcements and funding opportunities. It is not intended to promote a hierarchy between different countries based on economic status.

Note on Privacy GFH2R understands the delicate balance between protecting data collected and permitting access to those who need to use the data for authorized purposes. The primary use of this information is to identify candidates for participation in the GFH2R meeting. GFH2R and its Steering Committee will take every reasonable precaution to protect your information by maintaining appropriate physical, electronic, and procedural safeguards to ensure the security, integrity, and privacy of your personal information. Additional information regarding CRDF Global’s Privacy Policy can be found here.

• Rocque RJ, Beaudoin C, Ndjaboue R, Cameron L, Poirier-Bergeron L, Poulin-Rheault RA, et al. Health effects of climate change: an overview of systematic reviews. BMJ Open. 2021;11(6):e046333.
• Baxter L, McGowan CR, Smiley S, Palacios L, Devine C, Casademont C. The relationship between climate change, health, and the humanitarian response. Lancet. 2022;400(10363):1561-3.
• Romanello M, Di Napoli C, Drummond P, Green C, Kennard H, Lampard P, et al. The 2022 report of the Lancet Countdown on health and climate change: health at the mercy of fossil fuels. Lancet. 2022;400(10363):1619-54.
• Berrang-Ford L, Sietsma AJ, Callaghan M, Minx JC, Scheelbeek PFD, Haddaway NR, et al. Systematic mapping of global research on climate and health: a machine learning review. Lancet Planet Health. 2021;5(8):e514-e25.
• Health, Wellbeing and the Changing Structure of Communities. In: Intergovernmental Panel on Climate C, editor. Climate Change 2022 – Impacts, Adaptation and Vulnerability: Working Group II Contribution to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge: Cambridge University Press; 2023. p. 1041-170.
• Climate Change and Health Initiative Strategic Framework. National Institutes of Health; 2022.

More Information

• Global Forum on Humanitarian Health Research (GFH2R)
• Advancing Health Research in Humanitarian Crises
• Center for Global Health Studies

Updated August 2, 2024

• Study protocol
• Open access
• Published: 05 August 2024

A pragmatic, stepped-wedge, hybrid type II trial of interoperable clinical decision support to improve venous thromboembolism prophylaxis for patients with traumatic brain injury

• Christopher J. Tignanelli   ORCID: orcid.org/0000-0002-8079-5565 1 , 2 , 3 , 4 ,
• Surbhi Shah 5 ,
• David Vock 6 ,
• Lianne Siegel 6 ,
• Carlos Serrano 6 ,
• Elliott Haut 7 ,
• Sean Switzer 8 ,
• Christie L. Martin 9 ,
• Rubina Rizvi 2 , 3 ,
• Vincent Peta 1 ,
• Peter C. Jenkins 10 ,
• Nicholas Lemke 1 ,
• Thankam Thyvalikakath 11 , 12 ,
• Jerome A. Osheroff 13 ,
• Denise Torres 14 ,
• David Vawdrey 15 ,
• Rachael A. Callcut 16 ,
• Mary Butler 3 , 17 &
• Genevieve B. Melton 1 , 2 , 3  

Implementation Science volume  19 , Article number:  57 ( 2024 ) Cite this article

198 Accesses

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Metrics details

Venous thromboembolism (VTE) is a preventable medical condition which has substantial impact on patient morbidity, mortality, and disability. Unfortunately, adherence to the published best practices for VTE prevention, based on patient centered outcomes research (PCOR), is highly variable across U.S. hospitals, which represents a gap between current evidence and clinical practice leading to adverse patient outcomes.

This gap is especially large in the case of traumatic brain injury (TBI), where reluctance to initiate VTE prevention due to concerns for potentially increasing the rates of intracranial bleeding drives poor rates of VTE prophylaxis. This is despite research which has shown early initiation of VTE prophylaxis to be safe in TBI without increased risk of delayed neurosurgical intervention or death. Clinical decision support (CDS) is an indispensable solution to close this practice gap; however, design and implementation barriers hinder CDS adoption and successful scaling across health systems. Clinical practice guidelines (CPGs) informed by PCOR evidence can be deployed using CDS systems to improve the evidence to practice gap. In the Scaling AcceptabLE cDs (SCALED) study, we will implement a VTE prevention CPG within an interoperable CDS system and evaluate both CPG effectiveness (improved clinical outcomes) and CDS implementation.

The SCALED trial is a hybrid type 2 randomized stepped wedge effectiveness-implementation trial to scale the CDS across 4 heterogeneous healthcare systems. Trial outcomes will be assessed using the RE 2 -AIM planning and evaluation framework. Efforts will be made to ensure implementation consistency. Nonetheless, it is expected that CDS adoption will vary across each site. To assess these differences, we will evaluate implementation processes across trial sites using the Exploration, Preparation, Implementation, and Sustainment (EPIS) implementation framework (a determinant framework) using mixed-methods. Finally, it is critical that PCOR CPGs are maintained as evidence evolves. To date, an accepted process for evidence maintenance does not exist. We will pilot a “Living Guideline” process model for the VTE prevention CDS system.

The stepped wedge hybrid type 2 trial will provide evidence regarding the effectiveness of CDS based on the Berne-Norwood criteria for VTE prevention in patients with TBI. Additionally, it will provide evidence regarding a successful strategy to scale interoperable CDS systems across U.S. healthcare systems, advancing both the fields of implementation science and health informatics.

Trial registration

Clinicaltrials.gov – NCT05628207. Prospectively registered 11/28/2022, https://classic.clinicaltrials.gov/ct2/show/NCT05628207 .

Contributions to the Literature

This paper provides a study protocol for a new and novel stepped wedge study variation which includes external control sites to take into account external influences on the uptake of traumatic brain injury guidelines nationally

This paper provides a study design for one of the largest trauma pragmatic trials in the U.S. of 9 heterogenous hospitals

This study is also unique and first-in-kind feature as the guideline may change over time during the study due to the “living” nature of the guideline being implemented.

Introduction

Venous thromboembolism (VTE) is a preventable complication of traumatic brain injury (TBI), which has a substantial impact on patient morbidity, mortality, disability. It is also associated with significant economic burden > $1.5 billion per year [ 1 , 2 ]. VTE is considered a preventable medical condition in the majority of cases [ 2 , 3 ]. Unfortunately, adherence with patient centered outcomes research (PCOR)-informed VTE prevention best practices is highly variable and often poor across U.S. hospitals. Compliance with best practice is especially relevant in the case of TBI as 54% of TBI patients will develop a VTE if they do not receive appropriate anticoagulation [ 4 ]. The delivery of appropriate VTE prophylaxis to TBI patients is such an important quality measure that adherence is tracked nationally and benchmarked by the American College of Surgeons Trauma Quality Improvement Program (ACS-TQIP) [ 5 ]. We have previously shown that instituting a hospital-wide VTE prevention initiative modeled after the Berne-Norwood criteria for VTE prophylaxis in TBI was associated with significantly increased compliance with VTE-related process and improved outcome metrics [ 6 ]. Specifically, we observed improved adherence with the Berne-Norwood criteria [ 7 , 8 ], reduced time to initiation of VTE prophylaxis, and reduced VTE events [ 9 ]. Multiple studies have shown that VTE prophylaxis in trauma patients not only reduces VTE events, but also significantly reduces mortality [ 10 ]. We noted the same reduction in mortality for TBI patients following the initiation of a VTE prophylaxis guideline for patients with TBI [ 11 ]. Unfortunately, despite widely published PCOR-informed best practice, nationally there is reluctance to initiate VTE prevention due to concerns for progression of intracranial hemorrhage. This is despite research which has shown early initiation of VTE prophylaxis to be safe in TBI without increased risk of delayed neurosurgical intervention or death [ 12 , 13 , 14 , 15 , 16 ].

Since approximately 40% of TBI patients do not receive DVT prophylaxis in a timely manner, there is a critical and timely need to close the gap between current PCOR evidence and clinical practice. [ 17 , 18 , 19 , 20 , 21 , 22 , 23 ]. Clinical decision support (CDS) systems are an indispensable solution to close this practice gap; however, design and implementation barriers hinder CDS adoption [ 24 , 25 ]. Another significant challenge to the implementation of CDS is that health information technology (IT) needs a common language for PCOR evidence to translate it into practice across multiple organizations [ 26 ]. Because of these challenges, we will deploy CDS using fast healthcare interoperability resources (FHIR) standards to rapidly implement PCOR evidence into practice [ 27 , 28 ]. We hypothesize that, FHIR standards will reduce CDS development and maintenance costs, increase PCOR uptake in rural and other underserved sites, and speed the development timeline to build a comprehensive suite of CDS for PCOR evidence [ 29 ].

Few studies have investigated specific barriers to and facilitating factors for adoption of interoperable FHIR-based CDS [ 30 ]. For example, many current studies investigating barriers and facilitators for interoperable CDS are limited to expert opinion [ 30 , 31 ] or lack a formal implementation science framework-guided investigation [ 32 , 33 ]. Barriers to and facilitating factors for adoption of interoperable CDS following real-life implementation and multicenter scaling guided by validated implementation science frameworks should be rigorously investigated. This study will facilitate comprehensive exploration of clinician and environmental (internal and external) contextual elements that influence interoperable CDS implementation success. In this study, we will scale and assess the effectiveness of a CDS system for a VTE prophylaxis guideline in patients with TBI and evaluate implementation across 9 sites within 4 U.S. trauma systems.

Study aims and implementation framework

This trial consists of a stepped wedge hybrid effectiveness-implementation trial to scale the CDS system across 4 trauma systems and in parallel evaluate implementation strategy guided by the Exploration, Preparation, Implementation, and Sustainment (EPIS) implementation framework (Fig.  1 a) [ 34 ]. We anticipate variability in CDS adoption across sites during the implementation trial. This variation represents a unique opportunity to study implementation at each site and understand what strategies, system factors, and engagement of specific stakeholders are associated with improved CDS adoption. We will rigorously evaluate each implementation phase, guided by The EPIS Implementation Framework [ 34 ], our determinant framework (Fig.  1 b). We will apply the EPIS framework to guide assessment of implementation phases, barriers, and facilitators (Fig.  2 ) [ 34 ]. EPIS comprises 16 constructs over 4 domains (outer context, inner context, bridging factors, and innovation factors). We selected EPIS as our determinant framework as it includes clearly delineated implementation stages and allows for examination of change at multiple levels, across time, and through phases that build toward implementation. While EPIS was initially developed for implementation in public service, it has since been translated to healthcare, especially for complex multi-institutional healthcare interventions [ 34 , 35 , 36 ].

a Randomized Stepped Wedge design of the SCALED clinical trial. b Parallel, implementation evaluation guided by Explore, Preparation, Implementation and Sustain (EPIS) framework

Implementation evaluation across study sites

Trial overview, setting, and inclusion/exclusion criteria

This trial will be conducted at 4 healthcare systems with 1–3 hospitals per system and is projected to occur over a 3 to 4-year period. The trial uses a randomized stepped-wedge design to scale an interoperable CDS system for the Berne-Norwood TBI CPG. Figure  1 a provides a schematic for the trial design. The order of health systems and sites will be randomly determined. This study will include a heterogeneous number of hospitals by trauma verification status, electronic health record (EHR) platform, bed size, and setting (Table  1 ). Our target population is adult patients admitted with an acute TBI defined as International Classification of Disease 10 Clinical Modification (ICD-10-CM): S06.1 – S06.9 or S06.A. Patients who die within 24 h of hospital admission and patients documented as “comfort cares” during the first 72 h of hospitalization will be excluded, as they would have a limited opportunity to receive adherence with the Berne-Norwood criteria. Additionally, patients with a pre-existing VTE or inferior vena cava (IVC) filter at the time of admission, and patients with a mechanical heart valve or ventricular assist device will be excluded from final analysis.

This study will also include up to 3 control sites (Fig.  1 a), a feature not typically included with historic stepped-wedge trial designs, which will strengthen our ability to understand external influences on the study findings. These control sites, which do not receive the CDS intervention and do not have any planned initiatives around guideline implementation, will allow the study to assess baseline adherence and variation in clinical practice over the study period.

CDS Intervention

TBI diagnosis upon admission will activate an interoperable CDS system leveraging the Stanson Health (Charlotte, NC) CDS platform [ 37 ], which is being expanded to include interoperable offerings for TBI VTE prophylaxis. This system provides a knowledge representation framework to faithfully express the intent of the Berne-Norwood prevention criteria computationally (Table  2 ). The interoperable FHIR data standard will be used for bi-directional data transfer between each site’s EHR and the CDS platform. Workflow integration includes a combination of both passive and interruptive provider and trauma system leader information and “nudges”. Table 2 represents the Standards-based, Machine-readable, Adaptive, Requirements-based, and Testable (SMART) L2 layer [ 38 ] of the Berne-Norwood criteria.

CDS user-centered design

We will complete a rapid cycle CDS evaluation to optimize CDS workflow integration by conducting a user-driven simulation and expert-driven heuristic usability optimization as we have previously done [ 39 ]. For rapid cycle CDS evaluation, multidisciplinary trauma end-user “teams” will complete up to 3 scenarios designed to represent various extremes in TBI VTE prevention decision making. Simulation usability testing will be overseen by usability experts, who will catalogue usability issues that arise during simulation. Via consensus ranking, the development and planning teams will rank usability issues from 0 (cosmetic) to 5 (usability catastrophe). Using 10 predefined heuristics for usability design [ 40 ], we will conduct a heuristic evaluation of the CDS, then catalogue and rank usability issues. These results will inform CDS application design, optimized for TBI workflow integration.

Implementation strategy

Following CDS development, our healthcare system relies on a time-tested approach for the implementation and scaling of user-centered CDS: this approach is called the Scaling AcceptabLE cDs (SCALED) Strategy [ 41 ]. This framework integrates multiple evidence-based implementation strategies (Table  3 ).

Study outcomes

The primary implementation outcome is patient-level adherence with the CPG: Specifically, did the patient received guideline-concordant care? Adherence will be measured as an all-or-none measure (binary endpoint at the encounter/patient-level). Thus, if a patient is low-risk for TBI progression, by 24 h they should have risk-specific VTE prevention ordered; if they receive this after 24 h, or if they receive the intermediate risk VTE prevention regimen, this would be deemed non-adherent. The primary effectiveness outcome is VTE (binary endpoint at the patient-encounter level). Safety outcomes evaluated include: TBI progression, in-hospital mortality, and bleeding events. A secondary hypothesis is that as the trial scales to additional sites, iterative implementations will be more efficient (reduced implementation time) and more effective (improved adoption). Secondary hypotheses will be evaluated using the RE 2 -AIM framework [ 42 , 43 ] and are displayed in Table  4 .

Clinical trial data collection methods

Data sources used in this trial include the Stanson Health CDS eCaseReport and site trauma registry. The eCaseReport is a living registry of all patients, and their associated clinical trial data elements, that were eligible for the CDS. All sites also maintain a trauma registry adhering to the National Trauma Data Standards [ 44 ], a requirement for ACS trauma center verification. This dataset is manually annotated by trained clinical abstractors. Data will be sent to the biostatistical team at 6-month intervals. Control and pre-implementation sites will provide their trauma registry in addition to supplemental standards-based EHR extraction of clinical trial data elements or manual abstraction. A data dictionary has been created for the study and will be made available on the trial webpage.

Multiple methods evaluation of implementation success at each EPIS phase

Survey instruments will be prepared using Likert-type scales. Outcomes will be calculated based on scoring guides for the following validated scales: Program Sustainability Assessment Tool (PSAT) [ 45 ], Clinical Sustainability Assessment Tool (CSAT) [ 46 ], Implementation Leadership Scale (ILS) [ 47 ], and Evidenced-based Practice Attitude Scale-36 (EBPAS-36) [ 48 ]. Two scales do not have scoring rubrics: the Organizational Readiness for Change Questionnaire [ 49 , 50 ] and the Normalization Measure Development (NoMAD) Questionnaire [ 51 , 52 , 53 ]. Since both of these scales group questions into constructs, they will be analyzed by generating mean Likert scores and standard deviations per construct, and a mean across constructs, at each of the four implementation phases [ 54 ].

To deeply investigate barriers and facilitators of successful implementation, semi-structured qualitative interviews of key personnel (clinical leadership and end-users, IT leadership and staff) will be conducted at each of the 4 implementation phases. Studies suggest saturation of new ideas occurs after approximately 12 interviews [ 55 ]. Additional samples will be added as needed if thematic saturation is not achieved. Following informed consent, interviews will be performed by a trained qualitative research assistant, audio recorded, and transcribed verbatim. An interview guide, informed by the EPIS framework, was developed to collect key informant experiences with CDS implementation with a focus on inner and outer context factors [ 56 ]. A hybrid approach, primarily deductive and secondarily inductive, approach will be applied. All interviews will be independently double-coded and coding discrepancies will be resolved through discussion. A descriptive thematic analysis approach [ 57 ] will be used to characterize the codes into themes and sub-themes representing the barriers and facilitators to implementation success.

Results for all instruments will be primarily stratified according to site implementation success at each study phase. Additional stratifications may include respondent role, discipline, and hospital system. Bar charts displaying mean survey domains with integrative quotations from the qualitative analysis will be used to facilitate data visualization and understanding of key themes representing barriers and facilitators to successful CDSS implementation.

Statistical analysis

Mixed-effects logistic regression models will be fit to test whether or not CDS implementation changes the likelihood of a VTE event during TBI admission (effectiveness outcome) and the likelihood that the clinical guideline was followed (implementation outcome). The models for these outcomes include fixed-effects for month (when available, to account for secular trends) and an indicator variable for whether the center had the CDS integrated in the EHR. The primary test statistic will be a Wald test of the coefficient for this treatment indicator. We will include random center-specific intercepts to account for correlation within center. Assuming there are 9 sites enrolled with an average of 400 TBI admissions per year and the typical site has between 20%-40% adherence to the clinical guidelines, we will have > 80.0% and > 99.9% power to detect a 5 and 10 percentage point increase in the adherence. Similarly, assuming the typical site has between a VTE event rate of 5–6%, we will have > 80.0% power to detect a 40%-50% reduction in VTE consistent with our published data [ 11 ].

Study oversight

This study is overseen by the University of Minnesota Surgical Clinical Trials Office and by an independent Data Safety Monitoring Board (DSMB). Even though this intervention is deploying a TBI clinical guideline that is currently considered best practice, we believe the addition of a DSMB will improve trial safety, data quality, and trial integrity [ 58 ]. DSMB membership will be independent from the study investigators and will consist of 3 members including: 1 trauma surgeon, 1 informaticist, and 1 statistician. Annual reports including data from all sites, including control sites, will be shared with the DSMB to assure timely monitoring of safety and data quality. The trial will not be stopped early in the event of CDS efficacy because a critical secondary outcome focuses on studying implementation and effectiveness over time.

VTE guideline monitoring and maintenance

Given the potential for a changing evidence-base, it is possible that best practice VTE prevention guidance may change during the study period or afterwards. A critical element in improving adherence with PCOR evidence is updating guidance based on this evidence – in this study, this requires ensuring that the CDS system remains current.

We will pilot a model for producing and maintaining TBI VTE prophylaxis 'Living Guidance and CDS' to ensure that the CDS remains current (Fig.  3 ). The University of Minnesota Evidence-based Practice Center (EPC) Evidence Generation team will conduct and maintain a “living” systematic review. Systematic review data will be uploaded to the AHRQ’s Systematic Review Data Repository (SRDR). “Living” implies that every 6 months the EPC team will evaluate and synthesize new evidence related to TBI VTE prophylaxis, update the existing systematic review and deliver it to a multi-stakeholder Guideline Committee. The Guideline Committee will then use the GRADE (Grading of Recommendations, Assessment, Development and Evaluations) evidence-to-decision (EtD) framework to develop VTE prophylaxis guidelines for patients with TBI [ 59 , 60 , 61 ]. A computational representation of these guidelines will be updated and maintained within the CDS platform by Stanson Health, the CDS Vendor.

Pilot process for “Living Guideline”

Spreading successful results beyond study sites

The ultimate goal of this study is to spread successful CDS tools and strategies to broadly improve TBI VTE-related care processes and outcomes. The research outlined above will surface sharable insights about what information needs to be presented to which people in what formats through what channels at what times to reliably deliver guideline-based care – i.e., specific instantiations of the “CDS 5 Rights Framework” applied to this target [ 62 ]. We will use Health Service Blueprint tools to describe our recommended implementation approaches; these tools are being applied in an increasing number of public and private care delivery organizations as a structured approach to ‘get the CDS 5 Right right’ for various improvement targets. We will further adapt and apply Health Service Blueprint foundations supported by VA and AHRQ [ 63 ] to capture VTE care transformation guidance in Health Service Blueprint tooling [ 64 ]. Presenting recommended CDS-enabled workflow, information flow – as well as and related implementation considerations and broader healthcare ecosystem implications – in this structured format will help organizations beyond the initial study participants put study results into action efficiently and effectively.

In this paper, we present the protocol for the SCALED trial, a stepped-wedge cluster randomized trial of a CDS intervention to improve adherence with VTE prevention best practices for patients with TBI. As a hybrid type 2 trial, this study will evaluate both implementation and effectiveness outcomes. In addition to investigating effectiveness, we will also be able to provide insight into the implementation challenges for deploying interoperable CDS across heterogenous health systems. In our pilot study [ 9 ], while patients who received guideline-concordant care had significantly improved outcomes, we noted that not all patients receive guideline concordant care following implementation. Additionally, best strategies for scaling interoperable CDS systems are poorly studied. Thus, this study represents one of the earliest implementation evaluations of scaling interoperable CDS systems across heterogeneous health systems.

This study has several strengths. First, it will rigorously test implementation of a CPG for VTE prevention across 9 U.S. trauma centers using a multi-faceted CDS platform supporting both passive and interruptive decision support. Second, it will rigorously investigate scalable and interoperable CDS strategies to deploy CPGs. Third, this study leverages a centralized eCaseReport generated by the CDS system, a solution which can drive data collection for future pragmatic trials. Importantly, this study takes place at trauma centers which are geographically distinct, utilize different EHR vendors, include both ACS-verified level 1 through level 3 trauma centers, and include rural, community, and university-based trauma centers. In addition to helping spread recommended care transformation strategies beyond additional study sites, documenting these approaches in Health Service Blueprint tools will also support creation of learning communities for sharing, implementing, and enhancing these strategies.

This study also has limitations. First, we are only investigating 4 trauma systems which already have fairly advanced informatics divisions and experience implementing interoperable CDS systems. Thus, these findings may not be broadly applicable to health systems with less informatics experience and expertise. Second, we are only investigating implementation across two EHR vendors: Epic and Cerner, thus these findings may not be applicable to health systems with different EHR vendors such as Meditech or Allscripts. However, the Health Service Blueprint implementation strategy representations should still enable users of other systems to glean valuable insights about components of the transformation approach less dependent on specific EHRs used.

In summary, this study will implement and scale a CDS-enabled care transformation approach across a diverse collaborative CDS community, serving as an important demonstration of this critical healthcare challenge. We will integrate lessons learned for a planned national scaling in collaboration with U.S. trauma societies. Finally, we will pilot an approach for the “Living Guideline” and use that to maintain evidenced-based decision logic within CDS platforms.

Availability of data and materials

Following trial completion data will be made available upon request through the University of Minnesota Data Repository.

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CT conceived and jointly designed the study protocol and helped write and critically revise this protocol paper, SS conceived and jointly designed the study protocol and helped write and critically revise this protocol paper, DV jointly designed the study protocol and helped write and critically revise this protocol paper, LS jointly designed the study protocol and helped write and critically revise this protocol paper, CS jointly designed the study protocol and helped write and critically revise this protocol paper, EH jointly designed the study protocol and helped write and critically revise this protocol paper, SS jointly designed the study protocol and helped write and critically revise this protocol paper, CM jointly designed the study protocol and helped write and critically revise this protocol paper, RR jointly designed the study protocol and helped write and critically revise this protocol paper, VP jointly designed the study protocol and helped write and critically revise this protocol paper, PJ jointly designed the study protocol and helped write and critically revise this protocol paper, NL jointly designed the study protocol and helped write and critically revise this protocol paper, TT jointly designed the study protocol and helped write and critically revise this protocol paper, JO jointly designed the study protocol and helped write and critically revise this protocol paper, DT jointly designed the study protocol and helped write and critically revise this protocol paper, DV jointly designed the study protocol and helped write and critically revise this protocol paper, RC jointly designed the study protocol and helped write and critically revise this protocol paper, MB jointly designed the study protocol and helped write and critically revise this protocol paper, GM conceived and jointly designed the study protocol and helped write and critically revise this protocol paper.

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Tignanelli, C.J., Shah, S., Vock, D. et al. A pragmatic, stepped-wedge, hybrid type II trial of interoperable clinical decision support to improve venous thromboembolism prophylaxis for patients with traumatic brain injury. Implementation Sci 19 , 57 (2024). https://doi.org/10.1186/s13012-024-01386-4

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• Published: 08 August 2024

Comprehensive study on the efficiency of vertical bifacial photovoltaic systems: a UK case study

• Ghadeer Badran 1 &
• Mahmoud Dhimish 1  

Scientific Reports volume  14 , Article number:  18380 ( 2024 ) Cite this article

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• Photovoltaics
• Renewable energy
• Solar energy

This paper presents the first comprehensive study of a groundbreaking Vertically Mounted Bifacial Photovoltaic (VBPV) system, marking a significant innovation in solar energy technology. The VBPV system, characterized by its vertical orientation and the use of high-efficiency Heterojunction cells, introduces a novel concept diverging from traditional solar panel installations. Our empirical research, conducted over a full year at the University of York, UK, offers an inaugural assessment of this pioneering technology. The study reveals that the VBPV system significantly outperforms both a vertically mounted monofacial PV (VMPV) system and a conventional tilted monofacial PV (TMPV) system in energy output. Key findings include a daily power output increase of 7.12% and 10.12% over the VMPV system and an impressive 26.91% and 22.88% enhancement over the TMPV system during early morning and late afternoon hours, respectively. Seasonal analysis shows average power gains of 11.42% in spring, 8.13% in summer, 10.94% in autumn, and 12.45% in winter compared to the VMPV system. Against the TMPV system, these gains are even more substantial, peaking at 24.52% in winter. These results underscore the VBPV system's exceptional efficiency in harnessing solar energy across varied environmental conditions, establishing it as a promising and sustainable solution in solar energy technology.

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Introduction.

Solar photovoltaic (PV) technology has become a cornerstone of the renewable energy revolution, offering a clean, sustainable solution to the world's growing energy demands 1 . At its core, solar PV harnesses the sun's energy, converting it directly into electricity through semiconducting materials. This technology has traditionally been dominated by monofacial PV modules 2 , which collect sunlight from a single surface facing the sun. However, as the need for more efficient and cost-effective energy solutions intensifies, the evolution of solar PV has given rise to the bifacial module 3 , 4 —a novel approach to solar energy capture that promises to redefine the efficiency standards of solar energy systems.

Bifacial PV modules, as shown in Fig.  1 , are designed to capture sunlight on both their front and rear surfaces, utilizing direct sunlight and the light that reaches the rear surface through ground reflection and diffuse albedo 5 , 6 . Despite relying on silicon cells with the same spectral response as monofacial PV modules, the dual-sided design of bifacial modules allows them to significantly enhance energy yield by absorbing reflected and diffused light from surrounding surfaces 7 . This design is particularly beneficial in environments with high ground reflectivity or engineered ground covers to increase reflectivity 8 .

Illustration of bifacial PV system operation. The arrows indicate the different pathways of sunlight: yellow arrows represent direct sunlight hitting the front surface and the ground, orange arrows indicate the sunlight reflected from the ground hitting the rear surface, and red arrows depict the diffuse sunlight captured by both the front and rear surfaces 11 .

The evolution of bifacial PV modules represents more than just an incremental improvement in solar technology; it signifies a paradigm shift in how solar energy is harvested. Unlike traditional monofacial systems 9 that are limited by their unidirectional light capture, bifacial systems exploit the full spectrum of solar irradiance. This is achieved through a combination of advanced cell technology and innovative panel designs, which optimize light absorption from multiple angles 10 . The result is a marked increase in energy production per unit area, a critical factor in maximizing the efficiency of solar installations.

Moreover, the integration of bifacial PV technology aligns seamlessly with the global push towards sustainable development. By enhancing the power output of solar installations without the need for additional land, bifacial PV systems contribute to a more efficient use of resources. This efficiency is not confined to optimal conditions; bifacial modules demonstrate resilience in a variety of environmental settings 11 , 12 , including regions with lower solar irradiance and urban landscapes 13 where space and light conditions are constrained.

The significance of bifacial PV modules extends beyond their operational advantages. Their deployment has profound implications for energy policy, economic planning, and environmental strategy. By offering a more versatile and powerful solution for solar energy generation, bifacial PV systems can accelerate the transition to renewable energy sources, reduce dependency on fossil fuels, and mitigate the impacts of climate change.

In the realm of bifacial PV technology, various configurations have been explored to maximize the efficiency and adaptability of solar energy systems. These include vertical, tilted, and other innovative arrangements, each with its unique operational characteristics and applications. Vertical bifacial PV systems: These systems involve panels mounted in a vertical orientation. The key advantage of vertical bifacial PV is its ability to capture sunlight effectively throughout the day, from both sides of the panel 14 . This configuration is particularly beneficial in higher latitudes where the sun is lower in the sky 15 . Vertical systems are also less prone to accumulating dirt and debris, reducing maintenance requirements. Current research indicates that vertical bifacial systems can achieve significant energy gains in urban environments, where space is limited, and in regions with considerable diffuse light 16 .

Tilted bifacial PV Systems: Tilted systems are more traditional, where panels are installed at an angle to maximize exposure to direct sunlight. Bifacial panels in this configuration can capture reflected light from the ground or any reflective surface below. The optimal tilt angle is a subject of ongoing research, with studies 17 , 18 , 19 suggesting that slight adjustments in the tilt can lead to substantial increases in energy capture, particularly in areas with high ground albedo. And finally, tracking bifacial PV systems: These are dynamic systems where panels can adjust their orientation to follow the sun’s path 20 . This tracking capability, combined with bifacial technology, maximizes solar energy capture throughout the day. Research 21 , 22 shows that tracking bifacial systems offer the highest yield, especially in regions with high direct sunlight, making them a promising solution for large-scale solar farms.

Each of these configurations brings unique advantages and challenges, shaping the current research and development in the field of bifacial PV technology. Studies are continually underway to optimize the design, installation, and operational parameters of these systems. This includes investigating factors like the optimal distance between rows of panels 23 to prevent shading, the effect of different surfaces 24 and materials on light reflection, and the integration of smart technologies for performance monitoring and optimization. Furthermore, the performance of bifacial PV systems is significantly influenced by shading and the reflective properties of surrounding surfaces. Shading can reduce the overall efficiency by blocking sunlight from reaching both the front and rear surfaces of the panels. Detailed models of shading and illumination, such as those reported by 25 and 26 , provide comprehensive insights into these effects. In 25 the authors demonstrated that partial shading could lead to substantial reductions in energy output, especially in high-density installations. Further work by 26 explored the impacts of various surface materials and albedo on bifacial PV performance, showing that engineered surfaces with higher reflectivity can enhance energy yield by increasing the diffuse light captured by the rear surface of the panels. These models underscore the importance of considering shading and surface properties in the design and deployment of bifacial PV systems to optimize their performance.

The evolution of bifacial PV modules represents more than just an incremental improvement in solar technology; it signifies a paradigm shift in how solar energy is harvested. Unlike traditional monofacial systems that are limited by their unidirectional light capture, bifacial systems exploit the full spectrum of solar irradiance. This is achieved through a combination of advanced cell technology and innovative panel designs, which optimize light absorption from multiple angles. While Heterojunction (HJT) cells are a prominent technology used in bifacial modules, other technologies such as n-type 27 , Passivated Emitter and Rear Cell (PERC) 28 , Passivated Emitter Rear Totally Diffused (PERT) 29 , Passivated Emitter Rear Locally Diffused (PERL) 30 , and Interdigitated Back Contact (IBC) 30 solar cells are also suitable for bifacial applications, demonstrating widely successful results. These technologies collectively contribute to the marked increase in energy production per unit area 31 , a critical factor in maximizing the efficiency of solar installations.

This study introduces the first-ever exploration and publication on the vertically mounted bifacial photovoltaic (VBPV) system, a groundbreaking advancement in solar energy technology. This prototype's uniqueness stems from its vertical orientation and the use of high-efficiency Heterojunction (HJT) cells, a significant departure from traditional solar panel setups. Our research is pioneering in its empirical approach, offering the initial real-world evaluation of the VBPV system's performance across various environmental conditions over an entire year. This includes a comparative analysis with conventional monofacial systems, providing new insights into the practical efficiencies and benefits of bifacial technology. Additionally, the study navigates the complexities of modelling such an innovative system, addressing the challenges in accurately predicting performance and highlighting the need for advanced simulation techniques.

Materials and methods

New vertical pv bifacial concept design.

This study presents a pioneering exploration and evaluation of the vertically mounted bifacial photovoltaic system, focusing on its unique design and operational characteristics. The VBPV system utilizes high-efficiency HJT cells and is mounted in a vertical orientation, which significantly differs from traditional solar panel setups 32 , 33 . The experimental setup involved the installation of the VBPV system on the rooftop of the Physics Tower at the University of York (Fig.  2 a). The system comprises 36 series-connected PV units with a maximum output power of 1.5 kW under standard test conditions (STC) of 1000 W/m 2 irradiance and 25 °C ambient temperature. The location of the system was selected to maximize exposure to sunlight while also taking advantage of the reflective properties of the surrounding environment. The ground surface material beneath and around the PV modules is white gravel, known for its high albedo. This choice of material enhances the diffuse reflection, thereby increasing the amount of light captured by the rear side of the bifacial panels and boosting the overall energy yield. This setup ensures that the system benefits from both direct and reflected sunlight, optimizing its performance across various environmental conditions.

The new VBPV system examined in this work. ( a ) The system is located on the rooftop of the Physics Tower at the University of York, UK. The ground surface material is white gravel, chosen to enhance the albedo effect and increase the diffuse reflection captured by the rear side of the bifacial panels, ( b ) CFD simulation of the VBPV system under examination in this work, indicating the system has negligible lift forces at extreme wind speeds of 27.2 m/s.

The distance between each row of modules is 50 cm. This spacing was determined based on extensive simulations by Over Easy Solar AS, Norway, to optimize the balance between minimizing shading and maximizing ground reflection. This decision, while not arbitrary, aligns with findings from other research indicating that the optimal distance is a function of module height and should be carefully considered for each specific installation 34 , 35 , 36 . In addition to the nominal power output, the system's performance characteristics include a temperature coefficient of −0.29%/°C and a conversion efficiency of 22.5%, which are critical for understanding the operational efficiency and resilience of the VBPV system under varying environmental conditions.

The performance of the VBPV system was continuously monitored over a full annual cycle, from February 2023 to December 2023, and compared against a vertically mounted monocrystalline silicon monofacial PV (VMPV) system and a traditional tilted monofacial PV (TMPV) system. Data was recorded using a 3-kW inverter integrated with the university's grid, allowing for real-time tracking and analysis of energy production. This comprehensive empirical approach provides valuable insights into the practical efficiencies and benefits of bifacial technology, highlighting the superior performance of the VBPV system under varied environmental conditions.

The VBPV system was subjected to a Computational Fluid Dynamics (CFD) simulation to assess its aerodynamic stability. The simulation was conducted using ANSYS Fluent, employing a k-ε turbulence model to accurately capture the airflow dynamics around the panels. The boundary conditions included an inlet wind speed of up to 27 m/s, representing extreme weather conditions that the system might encounter. The panels were modeled with a surface roughness corresponding to the actual material properties, and the spacing between panels was set at 50 cm, as per the physical setup.

The CFD simulation results, shown in Fig.  2 b, reveal that the VBPV system maintains minimal lift forces even at high wind speeds of up to 27 m/s. This indicates exceptional aerodynamic stability, which is crucial for ensuring the durability and safety of the installation in adverse weather conditions. In comparison, traditional tilted PV systems have been documented to experience higher lift forces under similar wind conditions due to their inclined surfaces which can act like airfoils.

Data comparison and analysis

The innovative VBPV system under study is strategically positioned on the rooftop of the Physics Tower at the University of York, UK. It has been meticulously oriented towards the south to optimize solar gain. This system is seamlessly integrated with a 3-kW inverter, which facilitates the direct feed of generated electricity into the university's grid. The performance data of the system is meticulously monitored and recorded through the inverter's online platform, ensuring real-time tracking and analysis of energy production.

The installation of the VBPV system was completed in December 2022, with its official commissioning taking place in January 2023. As such, the performance data presented and analyzed in this work encompasses a comprehensive annual cycle, ranging from February 2023 to the end of December 2023. This dataset provides a robust foundation for assessing the system’s efficiency and energy output across various seasonal conditions.

To establish a baseline for comparison and underscore the VBPV system's performance, we juxtaposed its data against that of a vertically mounted monocrystalline silicon monofacial PV (VMPV) system situated adjacent to it, with the same PV capacity of 1.5 kW. This parallel analysis illuminates the advantages of bifacial technology in a like-for-like vertical setup. Furthermore, to extend the comparative analysis, we scrutinized the VBPV system's output relative to that of a traditional tiled 1.5 kW polycrystalline silicon monofacial PV system (TMPV). The latter is installed at the customary 45-degree angle prevalent in UK solar installations, thus representing the conventional approach to solar energy generation in the region; all PV configurations examined in this work are presented in Fig.  3 .

Comparison of Three Examined Photovoltaic (PV) System Configurations.

The power gain between two PV systems, such as the VBPV compared to VMPV or TMPV, is calculated using (1).

where \(Power\; Output_{VBPV}\) is the electrical power output of the VBPV, and \( Power \;Output_{Reference\; System}\) is the electrical power output of the reference system, which can be either VMPV or TMPV.

Vertical bifacial PV vs vertical monofacial PV

In the evaluation of PV systems performance, a comparative analysis was conducted between the VBPV system and the VMPV system. The results, illustrated in Fig.  4 a, b, present a compelling narrative on the efficacy of bifacial technology in solar energy capture throughout the day. Figure  4 a delineates the power output patterns of both systems over a 24-h period. Notably, the VBPV system exhibited a pronounced increase in power generation during the early morning hours, from 5:30 to 9:00 AM, where a bifacial gain of 1.64 kWh was recorded. This trend was not an isolated incident; a similar surge was observed in the late afternoon window from 5:00 to 8:30 PM, with an additional gain of 1.39 kWh. Collectively, these increments contributed to a total daily power output of 24.57 kWh for the VBPV system, compared to 23.3 kWh for the VMPV system, marking a 1.27 kWh gain or a 7.87% improvement.

Comparative daily power output of VBPV versus VMPV Systems, highlighting bifacial gain in early morning and late afternoon hours, ( a ) Day 1, ( b ) Day 2. This data was taken on 26th April 2023, with a mean temperature of 14.3 °C.

Complementing this, Fig.  4 b reaffirms the superior performance of the VBPV system under what can be presumed to be varying operational conditions. The early morning hours once again showed an enhanced power output with a gain of 2.46 kWh, while the afternoon session contributed an additional 1.87 kWh. Collectively, these increments contributed to a total daily power output of 24.66 kWh for the VBPV system, compared to 22.85 kWh for the VMPV system, marking a 1.81 kWh gain or a 11.45% improvement.

The consistency with which the VBPV system outstripped the VMPV system in energy generation is a testament to the inherent advantages of bifacial technology. By effectively harnessing sunlight not only from direct overhead exposure but also from reflected light, the VBPV system demonstrates its capacity for increased energy capture, particularly during the low-angle sunlight periods at dawn and dusk. This ability to capitalize on diffuse and reflected irradiance adds a dimension of efficiency that is particularly advantageous in regions with significant ground albedo 21 , 24 or in installations with reflective surroundings.

Vertical bifacial PV vs tilted monofacial PV

Our comprehensive assessment extends to Fig.  5 a, b, which provide further evidence of the enhanced performance of the VBPV system compared to the TMPV system. These figures represent a pivotal set of data showcasing the daily power output and clearly delineate the differential advantages offered by the bifacial technology under varied lighting conditions.

Comparative daily power output of VBPV versus TMPV Systems, ( a ) Day 1, ( b ) Day 2. This data was taken on 7 th May 2023, with a mean temperature of 16.7 °C.

In Fig.  5 a, we observe that the VBPV system significantly surpasses the TMPV system during the early hours, with a recorded bifacial gain of 3.24 kWh between 5:30 and 9:00 AM. This trend of increased efficiency extends to the latter part of the day, with an additional gain of 2.59 kWh noted from 5:00 to 8:30 PM. The aggregate gain for the VBPV system in this instance is an impressive 4.92 kWh, which equates to an enhancement of 25.38% when compared to its monofacial counterpart.

Similarly, Fig.  5 b corroborates the superior performance of the bifacial system. The morning hours once again present a marked advantage with a bifacial gain of 2.71 kWh. The evening period contributes to this lead with a gain of 2.03 kWh. Together, these increases amount to a total gain of 3.91 kWh for the VBPV system, representing a 21.40% boost in power output over the TMPV system.

The substantial gains in power output during the less intense light conditions of morning and evening highlight the potential for VBPV systems to provide a more consistent energy supply throughout the day, mitigating the well-known midday peak in power generation associated with traditional solar systems. This distribution of energy generation could align more closely with typical consumption patterns, thereby enhancing the match between supply and demand. For instance, residential energy consumption typically peaks in the early morning and late afternoon to evening hours, coinciding with periods when people are at home and engaging in activities such as cooking, heating, and using electronic devices 37 . Similarly, commercial buildings experience peak energy demand in the late morning and early afternoon, driven by the operation of lighting, HVAC systems, and office equipment 38 , 39 . By aligning energy generation with these demand patterns, VBPV systems can improve grid stability and reduce the reliance on energy storage solutions or supplementary power sources.

Monthly power gain comparison

This section analyzes the performance enhancements of the VBPV system in comparison to both VMPV and TMPV systems, as depicted in Figs.  6 and 7 , respectively. Figure  6 offers a nuanced view of the monthly power gains achieved by the VBPV system over the VMPV system, categorized by season. The histograms detail the frequency of power gain percentages, with a red dashed line indicating the seasonal average. In spring, the VBPV system shows a robust average power gain of 11.42%, indicating its superior performance during a time when sun angles and daylight hours start to increase. Summer, typically characterized by high solar irradiance, presents an average gain of 8.13%, a figure that might reflect high baseline performance from the VMPV system, reducing the relative gain. Autumn and winter follow with average gains of 10.94% and 12.45%, respectively, illustrating the VBPV system's effective light capture even during seasons with lower solar angles and shorter daylight hours.

VBPV compared to VMPV. ( a ) Monthly power gain (Percentage, %) for VBPV over VMPV. ( b ) Seasonal variations in power gain (Percentage, %) for VBPV over VMPV. The histograms represent the frequency distribution of the power gain percentages, and the red dashed lines indicate the seasonal average power gains.

VBPV compared to TMPV. ( a ) Monthly power gain (Percentage, %) for VBPV over TMPV. ( b ) Seasonal variations in power gain (Percentage, %) for VBPV over TMPV. The histograms represent the frequency distribution of the power gain percentages, and the red dashed lines indicate the seasonal average power gains.

Turning to Fig.  7 , the VBPV system's performance is compared with the TMPV system. Here, the seasonal average power gains are significantly higher, underscoring the VBPV system's advanced capabilities. Spring shows a remarkable average gain of 19.32%, indicating the profound impact of bifacial technology during this season. Summer months present an average gain of 14.77%, autumn shows a substantial 20.27%, and winter peaks with a 24.52% average gain, reinforcing the idea that the VBPV system's design is particularly beneficial in capturing low-angle light and diffused reflections, a common scenario in the colder months.

The data from Figs.  6 and 7 underscore the VBPV system's consistent and significant outperformance relative to both the VMPV and TMPV systems across all seasons. The marked efficiency of the VBPV system is reflective of its dual-capture capability, which enables it to harness light from both its front and rear surfaces. This capability is evidenced in the results by the substantial power gains observed during periods of diffuse light conditions, such as early morning and late afternoon, as well as during seasons with lower sun angles, like autumn and winter. Specifically, the VBPV system's ability to capture reflected light from the ground and surrounding surfaces significantly contributes to its enhanced performance, as demonstrated by the higher average power gains in comparison to monofacial systems. This dual-capture feature ensures that the VBPV system maximizes energy harvest from both direct sunlight and diffuse, reflected light, leading to a more consistent and higher overall energy output.

In concluding to this section, Fig.  8 offers a comprehensive statistical overview of the PV systems over an annual cycle. The box plot visualization encapsulates the monthly power gain percentages, delivering a succinct and robust comparative analysis. The box plots reveal that the VBPV system consistently exhibits higher power gains when compared to the TMPV and VMPV systems throughout the year. These gains are quantified by the median of each box, indicating that regardless of the month, the VBPV system capitalizes on its design, which allows it to capture additional energy from reflected light not accessible to monofacial systems.

Annual comparative analysis of monthly power gain percentages for VBPV versus TMPV and VBPV versus VMPV systems. The box plots illustrate the distribution of monthly power gain percentages for each system throughout the year. The blue box plot shows the power gain of the VBPV system compared to the TMPV system, while the green box plot shows the power gain of the VBPV system compared to the VMPV system. Median values are indicated by the horizontal lines within each box.

A critical observation from Fig.  8 is that the VBPV system not only outperforms the TMPV but also shows a significant advantage over the VMPV system. This distinction is noteworthy as it suggests that the enhancements in bifacial technology translate to tangible gains in power output, even when compared to a more conventional monofacial system like the VMPV. When analyzing the VBPV's performance against the TMPV system, we see an even more pronounced difference in reflective gain. The box plots for the VBPV and TMPV comparison stretch higher on the percentage axis, indicating that the traditional system, without the advanced technology of the VMPV, falls short in harnessing the available solar energy. Moreover, the box plots for the VBPV and VMPV comparison demonstrate that the VMPV, while more efficient than the TMPV, cannot match the VBPV system's capacity for increased energy capture. This pattern is consistent across all months, underlining the VBPV's superior design and efficiency.

To ascertain the financial benefits of VBPV systems, we conducted an analysis based on the monthly power gain percentages derived from empirical data, taken from Fig.  8 . Using an assumed standard monthly energy output of 1500 kWh as a baseline for all the systems, we applied the power gain percentages to estimate the additional energy produced solely due to the bifacial gain. The cost of electricity was factored in at the 2023 standard variable price of 28.62p/kWh. This price point reflects the retail electricity rate for an average consumer in the UK, which is subject to regional variations and market fluctuations. The analysis revealed discernible monthly fluctuations in savings (as shown in Fig.  9 ), which correspond with the changes in power gain percentages over the course of the year. The savings reached their zenith during the summer months, in alignment with the augmented power gains from increased solar irradiance. Conversely, the savings diminished during the winter months, reflecting the diminished solar irradiance inherent to the season.

Comparative Estimation of Monthly Savings Achieved Through Power Gain: A side-by-side comparison of the economic advantages of using VBPV systems versus VMPV systems (in green) and TMPV systems (in blue), across each month of the year.

For the VBPV compared with the VMPV systems, the additional solar energy captured by the bifacial technology translated into considerable monthly and cumulative annual savings. With the power output for these systems set at 1500 kWh, the use of VBPV systems resulted in a total estimated annual saving of £932.58 over the VMPV systems (Fig.  9 ). These savings are reflective of the consistent additional power generation offered by VBPV systems across all months, with the highest gains observed during the peak solar irradiance months of summer. In comparison to the TMPV systems, the VBPV systems demonstrated even greater economic advantages. The enhanced power gain percentages of VBPV systems, particularly noted during the winter months, emphasize their efficiency in low-irradiance conditions. The annual savings when comparing VBPV to TMPV systems amounted to a notable £1,221.13. This significant difference in savings highlights the VBPV system's ability to harness solar energy more effectively throughout the year, including during periods of lower sunlight availability.

In addition to the power gain analysis, a cost estimation comparison between the VBPV, VMPV, and TMPV systems is provided. The analysis considers the initial installation costs, maintenance costs, and the economic benefits derived from the increased energy output of the VBPV system. The initial installation cost of the VBPV system is higher than that of the VMPV and TMPV systems due to the advanced bifacial technology and the need for specialized mounting structures. Based on current market prices, the estimated cost per kW for VBPV systems is approximately £1,200, compared to £1,000 for VMPV and £900 for TMPV systems. Maintenance costs for VBPV systems are slightly lower due to the reduced accumulation of dirt and debris on vertically mounted panels.

To provide a comprehensive economic comparison, the annual energy savings and return on investment (ROI) were calculated. The cost of electricity in the UK is approximately £0.2862 per kWh. The annual additional energy produced by the VBPV system, as demonstrated in Fig.  9 , results in significant cost savings compared to VMPV and TMPV systems.

Bificail PV system gain vs solar irradiance

This section presents a critical analysis of the modeling challenges and successes encountered in simulating the performance of bifacial PV systems. Plane of Array (POA) irradiance, which refers to the solar irradiance incident on the plane of the PV array, is a key parameter in this analysis. However, to provide a complete picture of the relations, both direct and diffuse irradiance contributions to the bifacial gain are compared.

Figure  10 illuminates the relationship between bifacial gain and incident light, showcasing a clear trend where increased diffuse irradiance correlates with higher bifacial gain. This direct association highlights the complex interplay between light conditions and the energy capture efficiency of bifacial panels 7 . The scatter of data points emphasizes the difficulty in predicting performance due to the variability of solar irradiance, especially the proportion of diffuse light 40 . Such insights indicate that current modeling approaches may need refinement to account for this variability. This complexity is further evidenced by the limited data available for bifacial systems, which constrains the ability of models to accurately capture the nuances of their performance. The scarcity of robust datasets is a significant hurdle, suggesting a pressing need for more comprehensive data collection to improve the predictability and reliability of bifacial PV system models.

Correlation between bifacial gain and diffuse irradiance, highlighting the importance of diffuse light in bifacial PV system performance. The scatter plots show data points and regression lines indicating the trend, highlighting the significant role of diffuse irradiance in bifacial PV system performance.

Transitioning to Fig.  11 a, we examine the initial modeling attempts using the SAM NREL model 41 , 42 , which did not adequately capture the performance of the VBPV system. The figure portrays a significant discrepancy between modeled DC power and measured DC power, evidenced by the mean model error of 37.16% and an RMSE of 0.38%. This gap between expected and actual performance underscores the limitations of the model when it does not incorporate critical factors such as the variability of sunlight, particularly the diffuse component.

Modelling VBPV system output power (mix between hourly and daily data samples), ( a ) Initial modelling results, ( b ) Refined modelling results with adjusted sunlight variability.

In the quest to enhance the fidelity of PV system performance models, the incorporation of sunlight variability, specifically the ratio of diffuse to direct sunlight, stands as a pivotal aspect. This is particularly crucial for bifacial PV systems due to their ability to capture light from both their front and rear sides. The ratio of diffuse to direct sunlight can dramatically influence the amount of light received by the rear side of bifacial panels, which is not directly exposed to the sun. For this reason, Fig.  11 b presents a refined modeling approach where the variability of the sun, especially the ratio of diffuse to direct sunlight, is accounted for. The adjusted model results in a markedly improved correlation between modeled and measured DC power, with a substantially reduced mean model error of 11.55% and an RMSE of 0.12%. This improved alignment validates our hypothesis that incorporating the dynamic nature of sunlight, and its interactions with bifacial panels, is essential to accurately simulate their performance.

The refined model can be described by a set of equations that account for the bifacial gain, which is a function of both the direct and diffuse components of solar irradiance. The ratio of diffuse to direct irradiance, also known as the clearness index, is a crucial parameter in evaluating the performance of bifacial PV systems. This ratio, widely reported in the literature, indicates the proportion of solar radiation that is diffuse as opposed to direct. A higher clearness index signifies more diffuse light, which is particularly advantageous for bifacial systems as they can capture light from both their front and rear surfaces. According to 43 , understanding the clearness index is essential for accurately modeling bifacial PV performance, as it affects the amount of light available for the rear side of the panels. Similarly 44 , emphasized that regions with higher diffuse irradiance ratios exhibit enhanced bifacial gains. These findings underscore the importance of incorporating the clearness index in performance models for bifacial PV systems.

Let \({G}_{bifacial}\) be the bifacial gain, \({I}_{direct}\) is the direct irradiance, \({I}_{diffuse}\) is the diffuse irradiance, therefore, the bificail gain can be calculated in (2).

where \(\propto \) is the bifaciality coefficient for ground-reflected irradiance, \({R}_{ground}\) is the ground albedo, \(\beta \) is the bifaciality coefficient for sky-diffuse irradiance, and \({R}_{sky}\) is a factor representing the effective sky view factor affecting diffuse irradiance capture. The total amount of power output, \({P}_{modelled}\) , can then be calculated by (3). Where \({P}_{STC}\) is the power output under standard test conditions, \({\eta }_{conversion}\) is the conversion efficiency of the PV cells, and \(FF\) is the fill factor.

To calibrate the model with respect to the ratio of diffuse to direct sunlight, we introduce weighting coefficients that adjust the impact of each component on the total irradiance. The calibration process involves optimizing these coefficients so that the model output matches measured data as closely as possible. This was achieved by adjusting, \({w}_{direct}\) and \({w}_{diffuse}\) , the weighting coefficients for direct and diffuse irradiance, respectively. And therefore, to find the total effective irradiance, \({I}_{effective}\) calculated using (4). The optimization process aims to find the values of \({w}_{direct}\) and \({w}_{diffuse}\) , that minimize the error between the modeled and measured power output. This was achieved using an Levenberg–Marquardt optimization algorithm 45 , which is suited for solving non-linear least squares problems 46 .

Figure  12 presents the outcomes of modelling bifacial gain versus irradiance over two distinct temporal scales: daily and hourly. In the top panel, showcasing daily data, we observe the daily bifacial gain plotted against the day of the year. The data points, marked in blue, display a degree of variability that seems to follow a seasonal trend, likely reflecting the sinusoidal nature of solar irradiance throughout the year. A polynomial model fit, depicted by the red dashed line, attempts to capture this underlying trend. The fit seems to trace the central tendency of the data but does not adhere closely to individual data points, reflecting in a mean model error of 3.71% and an RMSE of 0.07. These metrics suggest that while the model grasps the general pattern, there is room for improvement, particularly in capturing the daily variability.

Comparative analysis of bifacial gain vs. irradiance on daily and hourly basis. The top panel illustrates the variation and model fit of daily bifacial gain over a year, while the bottom panel depicts the hourly bifacial gain for a week. The polynomial model fits (red dashed line for daily data, orange dashed line for hourly data) highlight the challenge in capturing temporal dynamics in bifacial PV system performance.

The bottom panel of Fig.  12 displays the hourly data, where each green dot represents the hourly bifacial gain for a particular hour of the week. Here, the volatility is more pronounced, reflecting the more dynamic changes in irradiance that occur throughout the day. The hourly model fit, illustrated by the orange dashed line, shows considerable deviation from the actual data points, with a mean error of 9.61% and an RMSE of 0.19. This discrepancy indicates that the hourly variations in irradiance and corresponding bifacial gain are not adequately captured by the current model, suggesting a need for a more complex or different modeling approach for short-term predictions.

The environmental and economic implications of adopting VBPV systems on a large scale are multifaceted and far-reaching. Environmentally, the most significant impact would be the substantial reduction in carbon emissions. Solar power is a clean, renewable resource, and the increased efficiency of VBPV systems means that more electricity can be generated per unit area compared to traditional solar solutions. This increased efficiency is critical in densely populated or land-scarce regions where the optimization of limited space is essential. Furthermore, the dual-sided nature of bifacial panels captures reflected light, enhancing energy yield and reducing the need for additional land, which is crucial for preserving natural habitats and biodiversity. These findings are consistent with studies that highlight the environmental benefits of bifacial PV systems, such as reduced land use 47 and lower carbon footprint 48 .

From an economic standpoint, the adoption of VBPV systems could lead to substantial cost savings over time. Although the initial investment might be higher than traditional systems due to the advanced technology involved, the higher energy yield and efficiency of VBPV systems will likely result in lower long-term costs. According to recent studies, bifacial PV systems can provide a return on investment that is 20–30% higher compared to monofacial systems due to the additional energy captured from the rear side 47 , 48 . Additionally, the maintenance costs might be lower due to the vertical design, which is less prone to dirt accumulation and potential shading issues. This factor alone could make VBPV systems more economically viable, especially in regions where labour and maintenance costs are significant factors.

The findings of this study have profound implications for global renewable energy strategies. The enhanced efficiency of VBPV systems aligns well with the growing global emphasis on sustainable development and the urgent need to shift to renewable energy sources. Studies have demonstrated the viability of bifacial PV systems in various urban environments, highlighting their adaptability and high energy yield even in constrained spaces 47 . For instance, bifacial PV installations on building facades and rooftops have shown significant energy production benefits 49 , supporting the transition to more sustainable urban infrastructure. By demonstrating the potential of VBPV systems in diverse environmental settings, this technology could play a pivotal role in the transition to a low-carbon economy.

In terms of policy and planning, these findings could influence government and industry leaders to reconsider their investment strategies. Encouraging the adoption of VBPV technology in urban planning and building design could be a significant step towards achieving energy efficiency targets. The literature since 2018 has explored various aspects of bifacial PV systems, emphasizing their efficiency, cost-effectiveness, and integration into smart grids such 50 , 51 . Future research should focus on testing VBPV systems in a variety of geographical locations and environmental conditions to validate and extend these findings. Additionally, it would be beneficial to explore the integration of VBPV systems with other renewable energy technologies such as wind or hydroelectric power to create more robust and resilient energy systems.

The specific geographical location and environmental conditions of York, UK, where this study was conducted, play a significant role in the performance of VBPV systems. York experiences a temperate maritime climate, characterized by relatively mild temperatures throughout the year, moderate rainfall, and variable cloud cover. The average annual temperature is around 10°C, with average daylight hours ranging from approximately 5–7 h in winter to 14–16 h in summer. The sun angle in York varies significantly with the seasons, reaching a maximum elevation of about 62 degrees during the summer solstice and a minimum of approximately 15 degrees during the winter solstice. These climatic conditions and solar geometry are critical factors influencing the performance of VBPV systems, as they determine the amount of direct and diffuse irradiance received by the panels.

In summary, the environmental and economic potential of VBPV systems is significant, with the possibility to make a considerable impact on global renewable energy strategies. However, acknowledging and addressing the limitations of current research is crucial in advancing this technology and maximizing its benefits.

Conclusions

This pioneering study on the VBPV system marks a significant leap forward in the realm of solar energy technology. Our comprehensive year-long research at the University of York, UK, serves as the first in-depth exploration of this innovative concept, diverging from conventional solar panel installations. The VBPV system, with its vertical orientation and utilization of advanced HJT cells, has demonstrated exceptional performance, surpassing traditional solar solutions in efficiency and energy output.

Key findings of this study reveal the superior capability of the VBPV system compared to its counterparts. Notably, the system outperformed VMPV system, showing a 7.12% and 10.12% increase in daily power output during early morning and late afternoon periods. When compared to a traditional TMPV system, the VBPV system exhibited even more remarkable gains, with a 26.91% and 22.88% enhancement in energy output in similar time frames. Seasonal analysis further highlights the system's efficiency, with average power gains of 11.42% in spring, 8.13% in summer, 10.94% in autumn, and 12.45% in winter over the VMPV system. Against the TMPV system, these gains peaked at an impressive 24.52% in the winter months.

These findings underscore the VBPV system's unparalleled ability to harness solar energy efficiently, irrespective of seasonal variances. Its design not only maximizes land use but also integrates seamlessly with modern architectural landscapes, adding an aesthetic value to its functional benefits. The system's bifacial technology, capable of capturing solar radiation from both sides, significantly boosts its energy yield, making it a potent solution for regions with variable sun exposure and reflective environments.

In conclusion, the VBPV system emerges as a promising solution for the future of sustainable energy. Its innovative design, superior efficiency, and adaptability to various environmental conditions position it as an ideal candidate for widespread adoption in both urban and rural settings. This study paves the way for future research and development in photovoltaic technology, encouraging a shift towards more efficient, environmentally friendly, and architecturally integrated solar energy solutions. As the first paper to delve into this new PV technology and concept design, it lays a strong foundation for the evolution of solar energy systems, steering the industry towards a more sustainable and energy-efficient future.

Data availability

Data will be made available on reasonable request to the corresponding author of the paper.

Abbreviations

Computational fluid dynamics

Direct current

Heterojunction

Interdigitated Back Contact

National Renewable Energy Laboratory

Passivated Emitter and Rear Cell

Passivated Emitter Rear Locally Diffused

Passivated Emitter Rear Totally Diffused

Plane of Array

Photovoltaic

Root mean square error

Standard test conditions

Tilted monofacial photovoltaic

Vertical bifacial photovoltaic

Vertical monofacial photovoltaic

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Acknowledgements

This research was supported by the EPSRC IAA under the project "Next-Generation Vertically Mounted Bifacial Solar Panels: Conceptualization, Field Testing, and Energy Performance Monitoring." We are grateful for the industrial collaboration and financial backing provided by Over Easy Solar AS and the Norwegian Research Council. Special thanks are extended to Richard Armitage, Electrical Technician, and Andy White, Chief Engineer at the University of York, for their invaluable assistance with the installation of the VBPV system. Additionally, we acknowledge the OverEasy team, particularly Jørgen Wallerud and Trygve Mongstad, for their pivotal role in facilitating the acquisition and funding of this system in the UK.

EPSRC, Next-Generation Vertically Mounted Bifacial Solar Panels: Conceptualization, Field Testing, and Energy Performance Monitoring, Next-Generation Vertically Mounted Bifacial Solar Panels: Conceptualization, Field Testing, and Energy Performance Monitoring.

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Ghadeer Badran & Mahmoud Dhimish

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Both authors discussed the organization and the content of the manuscript. G.B. performed the experiments, prepared figures, and wrote the main manuscript text. M.G validated the experimental results and revised the manuscript. Both authors have approved the manuscript before submission.

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Correspondence to Ghadeer Badran .

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Badran, G., Dhimish, M. Comprehensive study on the efficiency of vertical bifacial photovoltaic systems: a UK case study. Sci Rep 14 , 18380 (2024). https://doi.org/10.1038/s41598-024-68018-1

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Received : 25 January 2024

Accepted : 18 July 2024

Published : 08 August 2024

DOI : https://doi.org/10.1038/s41598-024-68018-1

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