healthcare case study quality management

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Original research

Hospital managers’ perspectives with implementing quality improvement measures and a new regulatory framework: a qualitative case study, sina furnes Øyri.

1 SHARE – Centre for Resilience in Healthcare, Faculty of Health Sciences, University of Stavanger, Stavanger, Norway

Geir Sverre Braut

2 Department of Research, Stavanger University Hospital, Stavanger, Norway

3 Department of Social Science, Western Norway University of Applied Sciences, Sogndal, Norway

4 Department of Safety, Economics and Planning, University of Stavanger, Stavanger, Norway

Carl Macrae

5 Centre for Health Innovation, Leadership and Learning, Nottingham University Business School, Nottingham, Nottinghamshire, UK

Associated Data

bmjopen-2020-042847supp001.pdf

A new regulatory framework to support local quality and safety efforts in hospitals was introduced to the Norwegian healthcare system in 2017. This study aimed to investigate hospital managers’ perspectives on implementation efforts and the resulting work practices, to understand if, and how, the new Quality Improvement Regulation influenced quality and safety improvement activities.

This article reports one study level (the perspectives of hospital managers), as part of a multilevel case study. Data were collected by interviews and analysed according to qualitative content analysis.

Three hospitals retrieved from two regional health trusts in Norway.

Participants

20 hospital managers or quality advisers selected from different levels of hospital organisations.

Four themes were identified in response to the study aim: (1) adaptive capacity in hospital management and practice, (2) implementation efforts and challenges with quality improvement, (3) systemic changes and (4) the potential to learn. Recent structural and cultural changes to, and development of, quality improvement systems in hospitals were discovered (3). Participants however, revealed no change in their practice solely due to the new Quality Improvement Regulation (2). Findings indicated that hospital managers are legally responsible for quality improvement implementation and participants described several benefits with the new Quality Improvement Regulation (2). This related to adaptation and flexibility to local context, and clinical autonomy as an inevitable element in hospital practice (1). Trust and a safe work environment were described as key factors to achieve adverse event reporting and support learning processes (4).

Conclusions

This study suggests that a lack of time, competence and/or motivation, impacted hospitals’ implementation of quality improvement efforts. Hospital managers’ autonomy and adaptive capacity to tailor quality improvement efforts were key for the new Quality Improvement Regulation to have any relevant impact on hospital practice and for it to influence quality and safety improvement activities.

Strengths and limitations of this study

• The main strength of this study is the novel approach of involving hospital managers’ perspectives in healthcare regulation research, as they are both legally and practically responsible for improving quality and safety.
• Most participants had substantial clinical experience and/or still worked in the clinic environment, in addition to having management responsibilities. This provided our study with valuable insight into the complexity in hospital management.
• The study did not include all four regional health trusts in Norway in its data.
• Variations in support systems and routines for training managers differ from region to region and may have implicitly or explicitly impacted participants’ views and experiences with quality and safety improvement and in turn potentially influenced findings.
• The individual interviews only focused on hospital managers own reflections and no actual, observational studies of practice, implementation or change where conducted.

Introduction

After years of regulatory interventions, management strategies and policy-making, improving quality and safety of healthcare systems remain high on political agendas around the world. Still, patient harm is listed as the world’s 14 biggest health burden along with illnesses such as malaria and tuberculosis. 1–5 The process of improving quality and safety has traditionally involved different dimensions, for instance clinical effectiveness, patient centeredness and care coordination. 6 If addressed, these dimensions seek to achieve an optimal healthcare system 6 (see table 1 for definitions of ‘quality’ and ‘safety’). A system perspective on quality improvement and involvement of stakeholders at different levels are portrayed as key in efforts to improve patient outcomes, system performance and professional development (learning). 7 8 Moreover, management of and leadership in healthcare is reckoned one of the fundamental elements to quality and safety, particularly related to implementation of improvement activities. 9 10 Inquiries into major healthcare failures, such as the Mid Staffordshire inquiry in 2013 and the Morecambe Bay inquiry in 2015 in the UK, revealed poor management and lack of safety oversight as common contributors to quality failures. 1 2 A progress report from 2018 added to these findings, calling for stronger management commitment in healthcare, amplifying how quality and safety should be incorporated into operational culture. 4 Internationally, increased attention has been brought to involvement of clinicians in management roles and highlighted the key role top managers play in providing support to lower level managers. 11 12 In Norway, hospital organisations are required to ensure their employees have relevant competences and training. Current leadership programmes and training regularly include learning about quality improvement methods and systematics. 5 13 14 Yet, recent research has indicated that to make quality improvement a thriving part of daily management practice, it needs to be supported by a strategic commitment to improvement, time to spend on improvement, and a culture that supports managers and clinicians working together. 15

Definitions and concepts

Prior research on healthcare regulation and its relation to improvements in organisational behaviour, including conduction of external inspection, has shown inconsistent outcomes in terms of its effectiveness 16–21 (see table 1 for this study’s conceptualisation of ‘regulation’ and regulatory activities). Several previous studies have explored healthcare organisations’ resilience potentials, including their capacity to adapt, but to date few multilevel studies link adaptive capacity with regulatory activities. 22–31 Others have highlighted that actively engaged participants from all organisational levels in healthcare are important, stressing how active improvement depends on leadership, also in the sense of recognising conditions that require flexibility. 7 32 The latter links management of quality improvement to management of adaptive capacity. Thus, attention should be paid to the development process of designing regulation that enables flexibility and supports adaptive capacity, by requesting non-detailed preferences or performance goals, especially since this may lead to a bottom-up perspective rather than top-bottom. 16 31–35

In 2017, a new regulatory framework to support local quality and safety efforts was introduced in the Norwegian healthcare system. 13 This framework, the Regulation on Management and Quality Improvement in the Healthcare Services (referred to as the Quality Improvement Regulation ) focuses on developing the capacity of healthcare organisations to continually improve quality and safety by constructing non-detailed goals for risk management 13 (see table 1 for definition of ‘risk’). Although the Quality Improvement Regulation is considered one of the most important governmental tools to support local quality and safety efforts in hospitals, 5 36 37 its impact on the healthcare services is still unknown from all perspectives (regulatory inspectors, hospital managers and healthcare personnel). The role of hospital managers is particularly important as they are stakeholders situated in the middle of governmental expectations and requirements, administrative demands and clinical practice.

Through the Quality Improvement Regulation, the regulators require hospital organisations to establish a system for risk management and responsibility. Its design embeds a structure of Plan, Do, Study, Act (PDSA), a four-step management methodology for quality improvement activities developed by Deming. 38 The Quality Improvement Regulation requires hospitals to plan for and establish systems to minimise risks, and to discover adverse events before they have consequences for the patients. Furthermore, it requires hospital managers to handle, correct and evaluate adverse events and failures. Accordingly, this study aims to investigate hospital managers’ perspectives on implementation efforts and the resulting work practices, to understand if, and how, the new Quality Improvement Regulation influenced quality and safety improvement activities.

Contextual background of the Norwegian regulatory regime for quality improvement

Several governmental initiatives have been launched in Norway in recent years in order to facilitate the hospitals’ continuous attention to patient safety and to increase the overall quality in the healthcare services they offer. The initiatives include annual quality and patient safety reports to the Norwegian Parliament (White Papers), national quality indicators, the previous National Strategy for Quality Improvement in Health and Social Services (2005–2015), a patient safety campaign (2010–2013), followed by a the national 5-year ‘Patient Safety Program’. 39–41 The latter was launched in 2014, as a broad scale effort to reduce patient injuries. 40 41 This programme (2014–2018) aimed at targeting several areas where it was believed to be crucial to increase care quality, including ‘Safe Surgery’ and ‘Management of Patient Safety’. It quantified several objectives—for instance to reduce infections, to improve survival rate and to improve patient safety culture. 40 Specific improvement projects were developed to meet relevant challenges in specific hospital settings, and hospitals were expected to incorporate the different initiatives to their daily work schedules. The recent national action plan for quality and patient safety (2019–2023) maintains attention on structural and cultural dimensions in quality and safety improvement. 5 In addition to these initiatives, previously conducted external hospital supervision across health regions in Norway have identified several challenges to systematic quality improvement 42–47 :

• Lack of adequate management responsibility and competencies.
• Lack of structure to ensure coworkers have prudent professional qualifications.
• Lack of systematic collecting of and evaluation of risks, vulnerabilities and adverse events.
• Lack of implementation of planned work tasks.
• Lack of evaluation of improvement efforts, post implementation.
• Lack of familiarity with and implementation of the previous regulatory framework for quality and safety management ‘the Internal Control Regulations’, 2002. 48

Moreover, hospital managers’ attitudes, values and organisational culture for learning were associated with non-compliance with governmental requirements. 42–46 These challenges and issues associated with implementation of quality improvement measures in hospitals formed an important backdrop to the questions that were asked in our study.

Content and design of the quality improvement regulation

The development and enactment of the Quality Improvement Regulation was thus the Government’s response to these challenges and launched in parallel with some of the other initiatives described above. The regulatory focus on the managerial level and the role of managers in risk management and quality improvement increased significantly with the new Quality Improvement Regulation compared with the previous Internal Control Regulations, as it (in a separate provision, cf. section 3) specifies the managerial responsibility to improve quality. The obligation to delegate tasks from one management level to another in daily work operations was specified. Moreover, one new substantial provision was added (cf. § 8 litra f): the obligation to systematically evaluate risk management and quality improvement measures (yearly). The Quality Improvement Regulation’s purpose is hence twofold: by explicitly stating managerial responsibilities it aims at improving managerial practices, whereas the PDSA methodology aims at organising the services in ways that improve clinical care. In table 2 , we illustrate details on the Quality Improvement Regulation’s regulatory PDSA design. Two specific examples of activities are given for each of the steps, all retrieved from the guidelines document relating to the Quality Improvement Regulation. 49

Details on the Quality Improvement Regulation’s regulatory Plan, Do, Study, Act (PDSA) design 48 49

The Norwegian specialised healthcare system

Four regional health trusts across Norway are responsible for implementing the national policies and regulations, and planning, organising, governing and coordinating all subordinated local health trusts, including the hospitals in their region (see box 1 displaying key numbers in the Norwegian specialist healthcare system). 50 51 Every hospital should be organised with a responsible manager at all organisational levels. 14 For each organisational unit in the hospital (eg, clinic (division or similar), department or equivalent, and sections), one manager with overall responsibility for the unit, both administratively and professionally should be appointed. 52

Key numbers in the Norwegian specialist healthcare system

Key numbers.

• 1 987 263 million million patients treated and/or hospitalised in 2019. 106 .
• 114 028 thousand people employed in the specialist healthcare services in 2018. 107 .
• The overall level of staffing by higher level health personnel is relatively high, with more than 50% of hospital employees being either physicians or nurses/midwives. 107 .
• €2667 (Kr27 100 Norway) in operating expenses per inhabitant in 2018. 106 .

Study design and setting

This article represents one substudy that is part of a broader qualitative, multilevel design single embedded case study, investigating regulatory quality improvement implementation and work across three levels of the specialised Norwegian healthcare system. 37 53 The case was defined as the design, implementation and enactment of the Quality Improvement Regulation and its impact on management and quality improvement across three organisational levels in two health regions. Specifically, the multilevel study involves three levels of stakeholders: macrolevel (governmental bodies of regulation), mesolevel (County Governors’ inspectors-regional supervision) and microlevel (three hospitals selected from two regional health trusts in Norway). To illustrate, figure 1 outlines the three system levels involved in the overall case study, whereas the microlevel presented in this article is specifically marked.

The system levels involved in the multilevel case study.

According to a multilevel approach, different levels of stakeholders have different impact on the risk management process. 54 These levels are interconnected through processes of information and decision-making, thus asking questions within three levels rather than within one single level, might help overcome single-level limitations. 55 Moreover, a multilevel study design can contribute to reflect healthcare organisations as integrated wholes where the patterns among different stakeholders are a key area of investigation. 56 Accordingly, this article presents the microlevel substudy, based on semistructured interviews with 20 Norwegian hospital managers and quality advisers. Macrolevel findings and mesolevel findings are presented in two separate research articles. 37 53

The inclusion criteria were participants who currently worked as hospital managers or advisers to hospital managers, preferably with clinical experience, situated at all levels within the hospital organisations, for example, head of clinic, head of department, divisional manager. Out of 20 participants, 18 had authorisation and license as health personnel and clinical experience from hospital practice. Several of them still worked clinically. Four out of five advisers had previous hospital manager experience and were chosen to highlight the support system for managers in the selected hospitals. Gender balance: 11 men and 9 women. See table 3 for participants’ characteristics.

Participants’ characteristics

*M.D., medical doctor, R.N., registered nurse, D.D.S, doctor of dental surgery, P.T, physiotherapist.

Recruitment

Participants were recruited from three different hospitals. Hospital one and two belonged to the same regional health trust, while hospital three belonged to a different regional health trust. These three hospitals were selected as they were affiliated with the three County Governors offices recruited at the mesolevel in the broader multilevel study. Relevant participants were contacted by email; proposed participation in the study, of which all (except one) accepted the invitation to participate.

Data collection

All interviews were conducted during the spring of 2019, then transcribed. SFO conducted and audio recorded all interviews face to face, at the participants’ workplace. Each interview had a duration of approximately 1 hour to 1 hour and 30 min. Based on the preplanned semistructured interview guide (see online supplemental file 1 ), open-ended questions focused on areas of responsibility, work practices, training, implementation of quality improvement measures, regulatory flexibility, the role of supervision in improvement work and learning, experiences connected to structural development and attitudes, cooperation among different levels of government, management levels in hospitals and clinical, front-line personnel.

Supplementary data

More specifically, questions were asked to determine if and how the Quality Improvement Regulation addressed some of the issues and challenges described in previous external inspections. The questions included for instance whether non-detailed risk management goals in the new regulatory framework facilitated flexibility in practical application and how managers experienced the systematic PDSA methodology (see preplanned questions in the online supplemental file 1 ). In addition, questions relating to communication and interaction among different system levels were asked to give insight into the regulator–regulatee interaction. The latter was particularly important to ascertain how hospital managers viewed the role of regulators and the new regulation, and the extent to which possible conflicts were reduced between government-level expectations and local-level, practices of managing quality improvement and safety.

Prior to the interviews, the participants received an information sheet informing them about the study’s topic, methods and data protection, and the researcher’s (SFO) credentials and occupation at the time of the study. Participants were subsequently requested to give their written consent. No pre-existing relationship with any of the participants existed.

Researcher SFO analysed the interview transcripts manually, using content analysis influenced by Graneheim and Lundman. 57 This analytical process consisted of several steps. SFO initially read through all interviews and took notes of immediate thoughts that occurred after reading, before organising all interview transcripts into a matrix. Thereafter, SFO identified and condensed all meaning units, suggested codes and subcategories. Four themes emerged across the data. Researchers GBS and SW read all interview transcripts and participated in discussions about categories and themes, to ensure the data’s reliability. 58 Our data were relatively rich, and we reached saturation during the analysis, justifying the number of participants. 59 60

Resilience in healthcare constitutes a valuable framework that helps to understand how systems can function and improve despite disruptions and adverse events. 61 A core idea is that resilience is the ability of the healthcare system to adjust its functioning prior to, during, or following changes and disturbances, so that it can sustain required performance under both expected and unexpected conditions . 62 63 Findings were therefore explained and interpreted by using resilience theory linked to adaptive capacity. 63–67 The data were partly analysed inductively by identifying concepts within resilience in healthcare and partly deductively by using predetermined questions explicitly exploring resilience potentials. 68

From our data of 20 interviews, we identified 4 themes: (1) adaptive capacity in hospital management and practice, (2) implementation efforts and challenges with quality improvement, (3) systemic changes, and (4) the potential to learn. All four themes are discussed below, along with illustrative participants’ quotes (numbers in parentheses indicate the link to participants characteristics, cf. table 3 ).

Theme I adaptive capacity in hospital management and practice

Participants agreed that the Quality Improvement Regulation was designed in a way that supported flexibility, enabling managers to determine and adapt implementation efforts and quality improvement measures to their local context. This was portrayed as essential, partly due to the complexity in the system including different risks and elements (eg, postoperative complications, team coordination, complex procedures) of variation and uncertainty. Risk-based management was thus characterised as one of the favourable advantages with the new Quality Improvement Regulation, as it encourages managers to assess risks according to specifics and hallmarks in the relevant unit, department and clinic.

The Quality Improvement Regulation gives you room to maneuver because it has a generic design. - Medical doctor, head of department (13 )

After all, you are completely dependent on close dialogue with those who work (at the sharp end) and we as managers need to move closer to find out where we need to adjust and to discover the areas where things are not working. - Medical doctor, head of clinic (11 )

Participants argued that having a one size fits all solution is not easy, as improvising will always be necessary at a local level. They continued with describing that in a hospital you are not in control of your day because new situations occur, implying that it is impossible to anticipate every possible event. This is one of the main reasons for why implementation of new routines and procedures are challenging, participants claimed. They believed that the embedded risks would remain risks regardless of new regulatory requirements, illustrated by the fact that adverse events still occur despite new, improved routines and procedures. Adding to this, participants described how they worked on standardising procedures aiming to reduce some of the unwanted variation in their work but noted that methods of treatment and evidence evolve so quickly that procedures need constant updates. While the government sometimes presents a black and white solution, a procedure is only valid until good reasons exist to deviate from it, they noted.

There are so many different things that come up and occur, that it is not always easy to have a one size fits all solution. There is some improvisation sometimes, in how to approach a problem. - Medical doctor, head of department (12 )

For a very detailed procedure to work well, you must be able to predict all types of situations that the different medical practitioners may come across, and we do not always manage to predict that. - Medical doctor, adviser in quality and patient safety (18 )

Autonomy was described as a key flexibility feature in everyday hospital work, especially for physicians. However, high degrees of autonomy may sometimes compromise physicians’ willingness to actively participate in systematic quality improvement work compared with the nursing profession, participants claimed.

They must get the impression of being involved in- and to influence their daily work. To give a purely administrative order, like: “Now you must pull yourself together, you should do this and that”, that approach will not do, they will boycott it. - Medical doctor, head of clinic (15 )

They also reported that the flexibility leaves the hospitals with the choice to implement whatever adverse event reporting system they choose. Furthermore, adaptive capacity to handle risks and challenges implies that hospitals are influenced by their own competences in terms of having the right personnel and training. Some participants even requested more strict support and correctives from their senior managers because that would indicate that their manager knew what sort of challenges they struggled with in their everyday work (eg, quality improvement efforts are added on top of their everyday workload, lack of good quality indicators, lack of personnel and time, information overload, lack of coordinated data systems).

I feel that we are free to express it (further up the hierarchy) if we experience that some efforts do not make sense to our work practices. - Nurse, head of department (14 )

Physicians hate to be controlled. At the same time, they write to the Ministry “we got to have some clear guidelines”, so physicians both love and hate rules. And it’s a schizophrenia that physicians have always had. - Medical doctor, adviser in quality and patient safety (18 )

Theme II implementation efforts and challenges with quality improvement

Our participants all agreed about the advantage and necessity of highlighting management responsibility in the new Quality Improvement Regulation. However, participants reported that most managers already have too many obligations and do not have time to prioritise systematic quality improvement efforts. Some even reported that many managers simply do not care about professional management and administering of their unit, department or clinic.

I think that the Quality Improvement Regulation is providing managers with an overall description of how a manager should act. You must do all these things that many people believe are obvious. And the Quality Improvement is kind of “stating the obvious”. - Medical doctor, adviser in quality and patient safety (18 )

Although PDSA as a method was familiar to the hospitals prior to introducing the Quality Improvement Regulation, several participants argued that the systematic four phase process is not embedded in health personnel’s work practice. They described all four phases as equally important but stressed that evaluation and restoring/returning to a normal state are the most demanding to operationalise into reality.

The extent to which these (PDSA) circles work according to the intention: there are measures implemented, and then there is no follow-up of the decisions. There is a total lack of it, I would almost say. - Medical doctor, head of research (9 )

I do not know if I am able to articulate how I work specifically with the four (PDSA) elements (…) because it is quite different from one area to the next. - Nurse, head of quality (6 )

Participants believed that the Quality Improvement Regulation did not lead to change in their practice.

Some things have been done by the executive level, but the clinic managers have not addressed it. - Nurse, quality coordinator (5 )

Not directly linked (the introduction of the Quality Improvement Regulation and implementation of practical measures into clinical work). I cannot think of (episodes) where it was like “let us take a look at this (the Quality Improvement Regulation) and then start changing things”. - Nurse, Head of Quality (20 )

Lack of understanding of what was referred to as ‘internal jargon’ in quality improvement and patient safety was believed to add to the burden and responsibilities of managers. However, several quality improvement measures were described, such as double check of medications, focus on communication in teamwork, reducing the number of hallway patients, questionnaire for patients’ satisfaction, preoperative marking, and surgical checklists. The latter was described as the most difficult, yet most successful implementation measure.

Several participants referred to what they experienced to be a common, yet a false claim: that physicians are not concerned about or involved in quality improvement. A lot of the improvement methodology is present although it is not stated clearly or written down and most physicians do work unconsciously in accordance with the quality improvement methodology, participants reported.

Theme III systemic changes

Findings revealed both structural and cultural changes to, and development of, quality improvement systems in the hospitals. The structural quality improvement elements were described in terms of the establishment of different types of meetings, councils and committees (eg, patient safety and quality councils, network meetings, internal audit meetings) at the administrative and management levels in hospitals.

We have built a new structure of quality and patient safety units. - Lawyer, legal adviser in quality and patient safety (3 )

Furthermore, systems of adverse event reporting and systems for documentation of procedures, routines, guidelines were introduced, and constantly evaluated and improved. The latter was described as extremely challenging in everyday work, as the number of available documents felt overwhelming, and sometimes routines and procedures overlapped or were outdated.

It has been one of the most important things, the system for documentation, and we have been working intensely to clear away old routines, revise all routines and get them updated, especially since our new quality adviser started. - Lawyer, deputy head of clinic (7 )

In addition to hospital internal structural changes, participants described an increased governmental spotlight on patient safety in general and on managers’ roles in reducing risks and enabling their employees to work safely and provide high quality care to patients. As a legal document, the Quality Improvement Regulation manifested this development, the participants explained.

We were probably more mature now in order to get that new Quality Improvement Regulation, and what I think is very nice is that it is to the point, three pages and it is kind of “this is how we should do it”. - Nurse, Head of Quality (20 )

We are obliged to do an annual risk review, which we have never done before, and we believe that the (Quality Improvement) Regulation has helped us in turning the spotlight on that. - Medical Director (8 )

All participants reported a cultural shift in improvement work over recent years. They described a change in attitudes towards the importance of continuous quality improvement and the systematic approach to it. Courses and training that used to be ignored by physicians, had gained attention, and increased its popularity, however support systems and routines varied among the study sites. Several participants also had experienced and expected a further shift with new generations of physicians approaching the field. This was explained partly due to the renewed curriculum introducing the methodology of systematic planning, acting, restoring and evaluation early on in their education.

(Quality improvement work) is not entirely new, but quite new. When I started as a surgeon, these were things that never came into view, so it’s been a remarkable change, especially over the last ten years. - Medical doctor, head of clinic (15 )

Today, managers can hardly speak without having to mention the word patient safety. So, it’s been an interesting development. - Medical doctor, adviser in quality and patient safety (18)

Theme IV the potential to learn

To maintain high quality care, interpersonal trust among health personnel and institutional trust between hospital managers and governmental supervisory bodies is a necessity, participants argued. Explaining why adverse event reporting was still weak, participants highlighted a safe work environment. Participants felt that a healthy reporting regime emerges from a just culture, which in turn leads health personnel to feel confident that they will be taken care of if they make mistakes and if they report adverse events. Some noted that a systems-perspective to adverse events, supported by the Quality Improvement Regulation, was more frequently applied now compared with in previous supervision activities, contributing to the needed sense of confidence to openly discuss adverse events and risks.

And I think that in doing quality improvement and patient safety work, we need to recognise that the number one priority is to ensure that health personnel are confident that they will be taken care of if they make mistakes, and that they find themselves in a system that reduces the number of adverse events to a minimum. - Medical doctor, head of department (19 )

In general, organisational, and individual learning was described as challenging and even more so learning across departments, clinics and between hospitals. Participants explained that it was difficult to learn from adverse events during normal work operations due to time pressures, nor did health personnel always have the motivation to do it.

We are part of an intellectual organisation, right, that is what drives us forward. After all, it is about our minds. To be able to change things you must get all these minds on board. Otherwise, everything stops. - Medical doctor, head of clinic (15 )

Since it is difficult to learn from adverse events, and the time is lacking—participants argued that it is difficult to learn from successful outcomes too. Implementation of the Quality Improvement Regulation did not change this.

We do have regular meetings within the clinic and across departments, so we learn a lot and it is our responsibility to somehow pass it on to our department. I don’t think there is a good system for that, but I don’t know how it could be resolved. The challenge is the amounts of information which I must communicate further down the system, to my employees, but they work shifts and are not necessarily checking their email every day. - Head nurse (17 )

As a response to questions about the interplay between hospitals and supervisory bodies, most participants emphasised that supervision could be useful and help the managers to focus on certain risk areas or challenging work practices. However, participants gave examples of less helpful episodes, such as inspectors having different views on certain rules and regulations, adding that some recommendations from inspectors were difficult or impossible to implement in practice. Some noted that supervision focuses primarily on negative aspects of improvement and felt that internal audits were more relevant and useful than governmental supervision, because the hospitals are leading their own problem solving.

If you have a written procedure and something happens, then they (red. inspectors) ask: “But why did you not do that?” Because the anatomy indicated differently (red. physician answers). “But it states in your written procedure that you should do it, right?” That is how a lawyer speaks compared to a physician… - Medical doctor, head of clinic (15 )

The main findings

According to the Quality Improvement Regulation, managers are responsible for implementation efforts and for the use of PDSA methodology. Our participants nevertheless described no change in their practice (related to quality and safety activities) solely due to this new regulatory framework. The introduction of the Quality Improvement Regulation was thus perceived by the participants as having no direct link with how they performed their work. Despite that, this study discovered structural and cultural changes to, and development of, quality improvement systems in hospitals in recent years. We argue that the structural and cultural changes that have happened (eg, annual quality and patient safety reports to the Norwegian Parliament, National Strategy for Quality Improvement in Health and Social Services (2005–2015), 39 ‘Patient Safety Program’ 40 ), also included the revision of the previous Internal Control Regulations into a new regulatory framework. 13 48 Hence, the governmental development of the Quality Improvement Regulation appears to be part of that systemic change. Participants described several benefits with the Quality Improvement Regulation in terms of adaptation and flexibility to local context, and clinical autonomy as an inevitable element in hospital practice. Trust and a safe work environment were considered key factors to support adverse event reporting and learning processes in general. The latter was crucial if collaboration with external supervisory inspectors should positively influence hospital quality enhancement.

It is assumed essential to involve different types of stakeholders when researching the system-level phenomenon of risk-based management, where complexity, uncertainty and variation are key concepts. 53 69 This study investigated hospital managers’ perspectives and experiences with practical implications of a specific regulatory change. Lower level management implementation of the new regulatory requirements was given main attention in our study. It is thus a limitation that it only reports the perspectives of managers and no other stakeholders from different levels in the system, such as patients, full-time clinicians, regulators. The perspectives of regulators and inspectors are presented in two separate research articles. 37 53 The main study strength is the uncommon approach of involving hospital managers in healthcare regulation research, as they both legally and practically are responsible for improving quality and safety. An additional strength is that most participants had substantial clinical experience and/or stilled worked in the clinic environment, in addition to having management responsibilities, which provided the study with valuable insight into the complexity in hospital management. A limitation with this study is that the interviews focused on hospital managers own reflections and did not include any observational study of practice/implementation/change. Another limitation is that two out of four regional health trusts in the Norwegian specialist healthcare system were not included. This may have hampered valuable information about the implementation process and geographical variations since the support systems and routines for training managers differ from region to region. Guided by the information power, however, the sample size of 20 participants was adequate and supported our effort to ensure trustworthiness. 57 70 We did nevertheless not discuss potential differences among participants belonging to the three different local health trusts (which could be viewed as a limitation), as we did not fully map resources, size and context of their quality advising units. However, all hospitals had established committees, boards and units related to quality improvement, and the structural and cultural changes reported in theme 3 reflected that overall systemic development.

Implementation, the capacity to adapt and the link to support systems

Healthcare regulation is tailored in various ways by the government, depending on the area. Some sectors are strictly governed by prescriptive rules (eg, medication-related issues). 64 The idea with the Quality Improvement Regulation’s design on the other hand was to provide managers with non-detailed goals for risk management-based implementation. With a non-detailed regulatory framework, the government does not specify how hospital managers should ‘get there’, built on ideas of local autonomy and context sensitivity. 64 As our data revealed, improvisation and local adaptation is viewed as essential to hospital management, along with an acceptance that healthcare situations such as patient treatment, diagnosis or surgery can develop into unforeseen scenarios which cannot be planned for. Regulatory measures that are too standardised or prescriptive could adversely reduce the autonomy of managers and health personnel. Our findings illustrated that managers acknowledged that strict regulations could potentially affect and hamper patient safety in cases where flexibility could be beneficial to the outcome.

However, a high degree of system adaptive capacity could occasionally represent a disadvantage, for instance when a procedure is adjusted but leads to an unsuccessful or unacceptable outcome, 67 or regulatory flexibility combined with a lack of interest in quality improvement work allows regulatees to deliberately ignore quality and safety expectations. Moreover, when choices and decisions are left to hospital organisations it creates considerable demand for internal systems to train managers, to establish systems for implementation support and IT solutions. This is echoed by past research on the growth of internal bureaucracy due to governmental deregulation of safety management. 71 Hence, our study found a paradox in the systemic development of meetings, councils and committees at the administrative and management levels in hospitals to comply with regulatory requirements for quality and safety, while managers reported few changes at the sharp end; in clinic, related to implementation of quality and safety activities. It is reasonable to think that there is a disparity in hospital manager support across different hospitals. Thus, having autonomous responsibility for competences and management training could in turn lead to different priorities in different regions and hospitals. Variation in support systems and routines was nevertheless reflected in our results.

Moreover, previous research has emphasised skills and support to manage conditions of unexpected events, and that managers (due to prioritisation struggles) need guidance to understand what is operationally needed. 72–74 Indeed, lack of knowledge and skills is perceived a significant barrier to quality improvement. 75 76 We argue that our current study demonstrates that the Quality Improvement Regulation’s non-detailed regulatory design, leaving implementation decisions to managers, could complicate managers’ understanding of governmental expectations. This resonates especially since the requirements need to be translated before practically applied (eg, how to define specific hospital-conduct as reasonable; safe; prudent or what is adequate documentation). As successful implementation requires more than a change in regulatory rhetoric or design, our study indicates that support tools for managers to achieve the goals in a systematic way have not been fully developed yet. The disjunction between rhetoric and reality, or theory versus practice, is a familiar one in research on implementation of rules and regulations in healthcare. It is often referred to as a dichotomy of work as imagined versus work as done. 66 77 This applies particularly to how requirements are trickled down the system to get resonance with those who do the actual implementation. 31 34 35 78 79 When lower level managers fail to implement efforts because they are difficult to convert into practice or that the policies being implemented have a weak relationship with the core clinical tasks, a process of ‘decoupling’ has occurred. 34 35 The study of van de Bovenkamp et al 80 revealed that hospitals needed to do a lot of interpretive work to make use of regulation; however, autonomy enabled this strategic work. Other studies have shown that additional resources and systems sometimes are needed to interpret and implement regulatory requirements. 81 As detailed rules and regulations may often be perceived as barriers to implementation, focusing regulatory attention on defining the quality of processes and outcomes could potentially make regulatory expectations more feasible for practical implementation. On the other hand, some hospital managers may find less details less helpful, because most of the responsibility, decisions and operationalisation are left with them. What can be drawn from this is that it will be important to consider how regulatory expectations are designed in ways that enable hospital managers to put efforts into practical reality. This implementation gap may also partly be explained by the type of managers who oversee implementation efforts. With different leadership approaches debated in the literature, prior research has identified how clinical managers’ sometimes struggle with role and identity. 12 82–86 Thus, to become interested in management, there ought to be awareness of meaning and purpose in management training, as it is first and foremost clinical work that is perceived meaningful to them. 12 86 Moving forward, it will be crucial to develop management practices that encourage quality improvement efforts, and encourage health personnel to participate. 15 87 Putting clinicians in management roles, provided with adequate leadership and quality improvement training, is key to making improvement an embedded and inclusive activity in everyday clinical work—especially since clinical managers often have experienced the importance of flexible and adaptive behaviour firsthand. 11 12 32 Thus, the ‘hybrid professional manager’ might bridge professional management, clinical identity and engagement, constituting an important system factor underpinning successful quality improvement and implementation. 84 85 88

PDSA—government favoured methodology for quality improvement

Although the Quality Improvement Regulation manifested the PDSA logic, 38 it did not independently explain if and why managers decided to put quality and safety activities on their agenda. Our findings indicated that clinicians worked with quality improvement, but they did not necessarily follow the PDSA-logic nor were they familiar with the Quality Improvement Regulation. Moreover, several participants described that measuring improvement efforts was challenging. This study links this to the assumption that everything is measurable according to the PDSA logic. 89 In that sense, and alike our study, prior research has found some drawbacks in using PDSA in hospitals’ quality improvement work. 90–92 Although the PDSA methodology encourages learning and supports adaptation of interventions, its efficient use requires considerable training and organisational and managerial support. 91 If PDSA is to remain at the core of regulatory design, then issues of organisational support and training need to be accounted for by regional health trusts and Government budgets.

Several alternative quality improvement methodologies exist. For instance, Six Sigma (define, measure, analyse, improve, control), Lean (identify waste; activities that do not add value), root cause analysis (identify the underlying causes; reactive in its approach), failure modes and effect analysis (identify potential adverse events, failures and hazards; proactive in in its approach). 93 Commonly among these approaches is that they presuppose identification of a specific problem area or cause(es) before the next steps of action might be implemented. This could possibly make managers overlook certain areas that are not obviously apparent. Thus, based on the contextual reality of hospital managers, reflected in our findings about resources and lack of time, we argue that complex, non-linear processes are challenged by these methodologies. Moreover, systemic risk factors such as resources and time are embedded and often linked and interrelated when an adverse event occurs. 94–97 Other organisational design considerations also seem important, beyond specific improvement methods. For instance, the inclusion of short, daily breaks to facilitate learning episodes may assist in improvement efforts. 98 Organisational adaptations such as this could address some of the challenges identified by participants in this study, where systematic quality improvement in line with the Quality Improvement Regulation’s PDSA logic, was viewed as too time consuming to justify full-scale implementation.

Implications for clinicians and policy-makers—and future research

This study is of relevance to both regulatory bodies and the management levels within hospitals. It adds some useful insights to development and implementation of future regulatory amendments in a Norwegian and in an international context. Moreover, the study highlights the importance of ensuring that any macrolevel quality improvement initiatives and regulatory requirements are accompanied by appropriate resourcing, support, and advanced preparation to ensure that it has the best possible chance of being implemented effectively. Our results therefore may contribute to theoretical development of macrolevel regulation, by implying how inclusive governance can add value to fill in the gap between work as imagined and work as done and support adaptive capacity as a positive element in quality improvement work. 67 Additionally, our study highlights regional variation in management training and programmes for leadership development, which fuels the idea that it will be important to provide a minimum level of training to all hospital managers, regardless of organisational level and regional affiliation. Yet, there are some unanswered questions that speaks for future research, for instance:

• How to provide additional management support for implementation through adding ‘practice facilitators’. 72
• How to improve the collaboration between inspectors and hospital managers. 99
• It would also be valuable to engage in cross-country comparative research to investigate how different regulatory regimes value flexibility in regulatory strategies for quality improvement and patient safety.

In this study, we explored how hospital managers work to improve quality and investigated their experiences with implementing the new Quality Improvement Regulation, provided to support management of quality improvement. The study showed that lack of time, competence and/or motivation, appears to limit the implementation of quality improvement efforts. While managers’ work to improve quality does not solely depend on a specific regulatory framework, the Quality Improvement Regulation may be an instrument that over time, leads to structural and cultural change. In turn, it can push managers towards a shift in strategic learning focus and resource allocations. Ultimately, hospital managers’ autonomy and their adaptive capacity and ability to tailor quality improvement efforts to local circumstances were key for the new Quality Improvement Regulation to have any relevant impact on hospital practice and for it to influence quality and safety activities.

Supplementary Material

Contributors: All authors designed the study. SFO conducted all interviews and transcribed 11 of these. Nine interviews were transcribed by a consultant. SFO analysed the data, and SW and GSB read the interview transcripts and discussed categories and themes. SFO drafted the manuscript. All four authors made critical revisions to the manuscript’s scientific content.

Funding: This work was supported by the Norwegian Ministry of Education and Research; University of Stavanger, Norway and part of the Resilience in Healthcare Research Program which has received funding from the Research Council of Norway from the FRIPRO TOPPFORSK program, grant agreement no. 275367.

Competing interests: None declared.

Patient consent for publication: Not required.

Ethics approval: The study did not collect specific patient information; thus, no approval from the regional committees for medical and health research ethics was required. Personal data derived from the study’s interviews were notified to the Norwegian Centre for Research Data (NSD) (Ref. No: 381276, 1 October 2018), as required in line with the agreement between the University of Stavanger and the NSD . Every participant signed informed consent ahead of the interview.

Provenance and peer review: Not commissioned; externally peer reviewed.

Data availability statement: Data may be obtained from a third party and are not publicly available. Data retrieved from the interviews are not publicly available due to the risk of identification but may be available from the corresponding author upon reasonable request and with permission from the participant(s).

Author note: SFO holds a Master of Laws (LL.M.) and MSc in Risk Management and Societal Safety and is currently a PhD candidate in Health and Medicine, SHARE – Centre for Resilience in Healthcare, at the University of Stavanger, Norway. GSB, MD, Adjunct professor, University of Stavanger; former Chief County Medical Officer Office; former Deputy Director General at the Norwegian Board of Health Supervision; Senior Adviser, Department of Research, Stavanger University Hospital. CM, PhD, Professor of Organisational Behaviour and Psychology, Centre for Health Innovation, Leadership and Learning, Nottingham University Business School and an Adjunct Professor at the University of Stavanger. SW, PhD, Professor of Quality and Safety in Healthcare Systems, SHARE – Centre for Resilience in Healthcare, at the University of Stavanger and Honorary Professor at the Australian Institute of Health Innovation, Faculty of Medicine and Health Sciences, Macquarie University, Australia.

Supplemental material: This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

Making quality assurance smart

For decades, outside forces have dictated how pharmaceutical and medtech companies approach quality assurance. The most influential force remains regulatory requirements. Both individual interpretations of regulations and feedback received during regulatory inspections have shaped quality assurance systems and processes. At the same time, mergers and acquisitions, along with the proliferation of different IT solutions and quality software, have resulted in a diverse and complicated quality management system (QMS) landscape. Historically, the cost of consolidating and upgrading legacy IT systems has been prohibitively expensive. Further challenged by a scarcity of IT support, many quality teams have learned to rely on the processes and workflows provided by off-the-shelf software without questioning whether they actually fit their company’s needs and evolving regulatory requirements.

In recent years, however, several developments have enabled a better way. New digital and analytics technologies make it easier for quality teams to access data from different sources and in various formats, without replacing existing systems. Companies can now build dynamic user experiences in web applications at a fraction of the cost of traditional, enterprise desktop software; this development raises the prospect of more customized, user-friendly solutions. Moreover, regulators, such as the FDA, are increasingly focused on quality systems and process maturity. 1 MDIC Case for Quality program. The FDA also identified the enablement of innovative technologies as a strategic priority, thereby opening the door for constructive dialogue about potential changes. 2 Technology Modernization Action Plan, FDA.

Smart quality at a glance

“Smart quality” is a framework that pharma and medtech companies can apply to redesign key quality assurance processes and create value for the organization.

Smart quality has explicit objectives:

• to perceive and deliver on multifaceted and ever-changing customer needs
• to deploy user-friendly processes built organically into business workflows, reimagined with leading-edge technologies
• to leapfrog existing quality management systems with breakthrough innovation, naturally fulfilling the spirit—not just the letter—of the regulations

The new ways in which smart quality achieves its objectives can be categorized in five building blocks (exhibit).

To learn more about smart quality and how leading companies are reimagining the quality function, please see “ Smart quality: Reimagining the way quality works .”

The time has arrived for pharmaceutical and medtech companies to act boldly and reimagine the quality function. Through our work on large-scale quality transformation projects and our conversations with executives, we have developed a new approach we call “smart quality” (see sidebar, “Smart quality at a glance”). With this approach, companies can redesign key quality processes and enable design-thinking methodology (to make processes more efficient and user-friendly), automation and digitization (to deliver speed and transparency), and advanced analytics (to provide deep insights into process capability and product performance).

The quality assurance function thereby becomes a driver of value in the organization and a source of competitive advantage—improving patient safety and health outcomes while operating efficiently, effectively, and fully aligned with regulatory expectations. In our experience, companies applying smart quality principles to quality assurance can quickly generate returns that outweigh investments in new systems, including line-of-sight impact on profit; a 30 percent improvement in time to market; and a significant increase in manufacturing and supply chain reliability. Equally significant are improvements in customer satisfaction and employee engagement, along with reductions in compliance risk.

Revolutionizing quality assurance processes

The following four use cases illustrate how pharmaceutical and medtech companies can apply smart quality to transform core quality assurance processes—including complaints management, quality management review, deviations investigations, and supplier risk management, among others.

1. Complaint management

Responding swiftly and effectively to complaints is not only a compliance requirement but also a business necessity. Assessing and reacting to feedback from the market can have an immediate impact on patient safety and product performance. Today, a pharmaceutical or medtech company may believe it is handling complaints well if it has a single software deployed around the globe for complaint management, with some elements of automation (for example, flagging reportable malfunctions in medical devices) and several processing steps happening offshore (such as intake, triage, and regulatory reporting).

Yet, for most quality teams, the average investigation and closure cycle time hovers around 60 days—a few adverse events are reported late every month, and negative trends are addressed two or more months after the signals come in. It can take quality assurance teams even longer to identify complaints that collectively point to negative trends for a particular product or device. At the same time, less than 5 percent of incoming complaints are truly new events that have never been seen before. The remainder of complaints can usually be categorized into well-known issues, within expected limits; or previously investigated issues, in which root causes have been identified and are already being addressed.

The smart quality approach improves customer engagement and speed

By applying smart quality principles and the latest technologies, companies can reduce turnaround times and improve the customer experience. They can create an automated complaint management process that reduces costs yet applies the highest standards:

• For every complaint, the information required for a precise assessment is captured at intake, and the event is automatically categorized.
• High-risk issues are immediately escalated by the system, with autogenerated reports ready for submission.
• New types of complaints and out-of-trend problems are escalated and investigated quickly.
• Low-risk, known issues are automatically trended and closed if they are within expected limits or already being addressed.
• Customer responses and updates are automatically available.
• Trending reports are available in real time for any insights or analyses.

To transform the complaint management process, companies should start by defining a new process and ensuring it meets regulatory requirements. The foundation for the new process can lie in a structured event assessment that allows automated issue categorization based on the risk level defined in the company’s risk management documentation. A critical technological component is the automation of customer complaint intake; a dynamic front-end application can guide a customer through a series of questions (Exhibit 1). The application captures only information relevant to a specific complaint evaluation, investigation, and—if necessary—regulatory report. Real-time trending can quickly identify signals that indicate issues exceeding expected limits. In addition, companies can use machine learning to scan text and identify potential high-risk complaints. Finally, risk-tailored investigation pathways, automated reporting, and customer response solutions complete the smart quality process. Successful companies maintain robust procedures and documentation that clearly explain how the new process reliably meets specific regulatory requirements. Usually, a minimal viable product (MVP) for the new process can be built within two to four months for the first high-volume product family.

In our experience, companies that redesign the complaint management process can respond more swiftly—often within a few hours—to reduce patient risk and minimize the scale and impact of potential issues in the field. For example, one medtech company that adopted the new complaint management approach can now automatically assess all complaints and close more than 55 percent of them in 24 hours without human intervention. And few, if any, reportable events missed deadlines for submission. Now, subject matter experts are free to focus on investigating new or high-risk issues, understanding root causes, and developing the most effective corrective and preventive actions. The company also reports that its customers prefer digital interfaces to paper forms and are pleased to be updated promptly on their status and resolution of their complaints.

2. Quality management review

Real-time performance monitoring is crucial to executive decision making at pharmaceutical and medtech companies. During a 2019 McKinsey roundtable discussion, 62 percent of quality assurance executives rated it as a high priority for the company, exceeding all other options.

For many companies today, the quality review process involves significant manual data collection and chart creation. Often, performance metrics focus on quality compliance outcomes and quality systems—such as deviation cycle times—at the expense of leading indicators and connection to culture and cost. Managers and executives frequently find themselves engaged in lengthy discussions, trying to interpret individual metrics and often missing the big picture.

Although many existing QMS solutions offer automated data-pull and visualization features, the interpretation of complex metric systems and trends remains largely a manual process. A team may quickly address one performance metric or trend, only to learn several months later that the change negatively affected another metric.

The smart quality approach speeds up decision making and action

By applying smart quality principles and the latest digital technologies, companies can get a comprehensive view of quality management in real time. This approach to performance monitoring allows companies to do the following:

• automatically collect, analyze, and visualize relevant leading indicators and outcomes on a simple and intuitive dashboard
• quickly identify areas of potential risk and emerging trends, as well as review their underlying metrics and connections to different areas
• rapidly make decisions to address existing or emerging issues and monitor the results
• adjust metrics and targets to further improve performance as goals are achieved
• view the entire value chain and create transparency for all functions, not just quality

To transform the process, companies should start by reimagining the design of the process and settling on a set of metrics that balances leading and lagging indicators. A key technical enabler of the system is establishing an interconnected metrics structure that automates data pull and visualization and digitizes analysis and interpretation (Exhibit 2). Key business processes, such as regular quality management reviews, may require changes to include a wider range of functional stakeholders and to streamline the review cascade.

Healthcare companies can use smart quality to redesign the quality management review process and see results quickly. At one pharmaceutical and medtech company, smart visualization of connected, cross-functional metrics significantly improved the effectiveness and efficiency of quality management review at all levels. Functions throughout the organization reported feeling better positioned to ascertain the quality situation quickly, support decision making, and take necessary actions. Because of connected metrics, management can not only see alarming trends but also link them to other metrics and quickly align on targeted improvement actions. For example, during a quarterly quality management review, the executive team linked late regulatory reporting challenges to an increase in delayed complaint submissions in some geographic regions. Following the review, commercial leaders raised attention to this issue in their respective regions, and in less than three months, late regulatory reporting was reduced to zero. Although the company is still in the process of fully automating data collection, it has already noticed a significant shift in its work. The quality team no longer spends the majority of its time on data processing but has pivoted to understanding, interpreting, and addressing complex and interrelated trends to reduce risks associated with quality and compliance.

Healthcare companies can use smart quality to redesign the quality management review process and see results quickly.

3. Deviation or nonconformance investigations

Deviation or nonconformance management is a critical topic for companies today because unaddressed issues can lead to product recalls and reputational damage. More often, deviations or nonconformances can affect a company’s product-release process, capacity, and lead times. As many quality teams can attest, the most challenging and time-consuming part of a deviation or nonconformance investigation is often the root cause analysis. In the best of circumstances, investigators use a tracking and trending system to identify similar occurrences. However, more often than not, these systems lack good classification of root causes and similarities. The systems search can become another hurdle for quality teams, resulting in longer lead times and ineffective root cause assessment. Not meeting the standards defined by regulators regarding deviation or nonconformance categorization and root cause analysis is one of the main causes of warning letters or consent decrees.

The smart quality approach improves effectiveness and reduces lead times

Our research shows companies that use smart quality principles to revamp the investigation process may reap these benefits:

• all pertinent information related to processes and equipment is easily accessible in a continuously updated data lake
• self-learning algorithms predict the most likely root cause of new deviations, thereby automating the review of process data and statements

In our experience, advanced analytics is the linchpin of transforming the investigation process. The most successful companies start by building a real-time data model from local and global systems that continuously refreshes and improves the model over time. Natural language processing can generate additional classifications of deviations or nonconformances to improve the quality and accuracy of insights. Digitization ensures investigators can easily access graphical interfaces that are linked to all data sources. With these tools in place, companies can readily identify the most probable root cause for deviation or nonconformance and provide a fact base for the decision. Automation also frees quality assurance professionals to focus on corrective and preventive action (Exhibit 3).

Pharmaceutical and medtech companies that apply these innovative technologies and smart quality principles can see significant results. Our work with several companies shows that identifying, explaining, and eliminating the root causes of recurring deviations and nonconformances can reduce the overall volume of issues by 65 percent. Companies that use the data and models to determine which unexpected factors in processes and products influence the end quality are able to control for them, thereby achieving product and process mastery. What’s more, by predicting the most likely root causes and their underlying drivers, these companies can reduce the investigation cycle time for deviations and nonconformances by 90 percent.

4. Supplier quality risk management

Drug and medical device supply chains have become increasingly global, complex, and opaque as more pharmaceutical and medtech companies outsource major parts of production to suppliers and contract manufacturing organizations (CMOs). More recently, the introduction of new, complex modalities, such as cell therapy and gene editing, has further increased pressure to ensure the quality of supplier products. Against this backdrop, it is critical to have a robust supplier quality program that can proactively identify and mitigate supplier risks or vulnerabilities before they become material issues.

Today, many companies conduct supplier risk management manually and at one specific point in time, such as at the beginning of a contract or annually. Typically, risk assessments are done in silos across the organization; every function completes individual reports and rarely looks at supplier risk as a whole. Because the results are often rolled up and individual risk signals can become diluted, companies focus more on increasing controls than addressing underlying challenges.

The smart quality approach reduces quality issues and optimizes resources

Companies that break down silos and apply a more holistic risk lens across the organization have a better chance of proactively identifying supplier quality risks. With smart quality assurance, companies can do the following:

• identify vulnerabilities by utilizing advanced analytics on a holistic set of internal and external supplier and product data
• ensure real-time updates and reviews to signal improvements in supplier quality and any changes that may pose an additional risk
• optimize resource allocation and urgency of action, based on the importance and risk level of the supplier or CMO

Current technologies make it simpler than ever to automatically collect meaningful data. They also make it possible to analyze the data, identify risk signals, and present information in an actionable format. Internal and supplier data can include financials, productivity, and compliance metrics. Such information can be further enhanced by publicly available external sources—such as regulatory reporting, financial statements, and press releases—that provide additional insights into supplier quality risks. For example, using natural language processing to search the web for negative press releases is a simple yet powerful method to identify risks.

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Once a company has identified quality risks, it must establish a robust process for managing these risks. Mitigation actions can include additional monitoring with digital tools, supporting the supplier to address the sources of issues, or deciding to switch to a different supplier. In our experience, companies that have a deep understanding of the level of quality risk, as well as the financial exposure, have an easier time identifying the appropriate mitigation action. Companies that identify risks and proactively mitigate them are less likely to experience potentially large supply disruptions or compliance findings.

Many pharmaceutical and medtech companies have taken steps to improve visibility into supplier quality risks by using smart quality principles. For example, a large pharmaceutical company that implemented this data-driven approach eliminated in less than two years major CMO and supplier findings that were identified during audits. In addition, during the COVID-19 pandemic, a global medtech company was able to proactively prevent supply chain disruptions by drawing on insights derived from smart quality supplier risk management.

Getting started

Pharmaceutical and medtech companies can approach quality assurance redesign in multiple ways. In our experience, starting with two or three processes, codifying the approach, and then rolling it out to more quality systems accelerates the overall transformation and time to value.

Smart quality assurance starts with clean-sheet design. By deploying modern design techniques, organizations can better understand user needs and overcome constraints. To define the solution space, we encourage companies to draw upon a range of potential process, IT, and analytics solutions from numerous industries. In cases where the new process is substantially different from the legacy process, we find it beneficial to engage regulators in an open dialogue and solicit their early feedback to support the future-state design.

Once we arrive at an MVP that includes digital and automation elements, companies can test and refine new solutions in targeted pilots. Throughout the process, we encourage companies to remain mindful of training and transition planning. Plans should include details on ensuring uninterrupted operations and maintaining compliance during the transition period.

The examples in this article are not exceptions. We believe that any quality assurance process can be significantly improved by applying a smart quality approach and the latest technologies. Pharmaceutical and medtech companies that are willing to make the organizational commitment to rethink quality assurance can significantly reduce quality risks, improve their speed and effectiveness in handling issues, and see long-term financial benefits.

Note: The insights and concepts presented here have not been validated or independently verified, and future results may differ materially from any statements of expectation, forecasts, or projections. Recipients are solely responsible for all of their decisions, use of these materials, and compliance with applicable laws, rules, and regulations. Consider seeking advice of legal and other relevant certified/licensed experts prior to taking any specific steps.

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Please note you do not have access to teaching notes, integrated approach to healthcare quality management: a case study.

The TQM Magazine

ISSN : 0954-478X

Article publication date: 1 November 2006

The purpose of the paper is to develop an integrated quality management model, which identifies problems, suggests solutions, develops a framework for implementation and helps evaluate performance of health care services dynamically.

Design/methodology/approach

This paper uses logical framework analysis (LFA), a matrix approach to project planning for managing quality. This has been applied to three acute healthcare services (Operating room utilization, Accident and emergency, and Intensive care) in order to demonstrate its effectiveness.

The paper finds that LFA is an effective method of quality management of hospital‐based healthcare services.

Research limitations/implications

This paper shows LFA application in three service processes in one hospital. However, ideally this is required to be tested in several hospitals and other services as well.

Practical implications

In the paper the proposed model can be practised in hospital‐based healthcare services for improving performance.

Originality/value

The paper shows that quality improvement in healthcare services is a complex and multi‐dimensional task. Although various quality management tools are routinely deployed for identifying quality issues in health care delivery and corrective measures are taken for superior performance, there is an absence of an integrated approach, which can identify and analyze issues, provide solutions to resolve those issues, develop a project management framework (planning, monitoring, and evaluating) to implement those solutions in order to improve process performance. This study introduces an integrated and uniform quality management tool. It integrates operations with organizational strategies.

• Service operations
• Health services
• Quality management

Dey, P.K. and Hariharan, S. (2006), "Integrated approach to healthcare quality management: a case study", The TQM Magazine , Vol. 18 No. 6, pp. 583-605. https://doi.org/10.1108/09544780610707093

Emerald Group Publishing Limited

Copyright © 2006, Emerald Group Publishing Limited

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Healthcare Quality Management: A Case Study Approach 1st Edition

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Healthcare Quality Management: A Case Study Approach is the first comprehensive case-based text combining essential quality management knowledge with real-world scenarios. With in-depth healthcare quality management case studies, tools, activities, and discussion questions, the text helps build the competencies needed to succeed in quality management.

Written in an easy-to-read style, Part One of the textbook introduces students to the fundamentals of quality management, including history, culture, and different quality management philosophies, such as Lean and Six Sigma. Part One additionally explains the A3 problem-solving template used to follow the Plan-Do-Study-Act (PDSA) or Define, Measure, Analyze, Improve, and Control (DMAIC) cycles, that guides your completion of the problem-solving exercises found in Part Two. The bulk of the textbook includes realistic and engaging case studies featuring common quality management problems encountered in a variety of healthcare settings. The case studies feature engaging scenarios, descriptions, opinions, charts, and data, covering such contemporary topics as provider burnout, artificial intelligence, the opioid overdose epidemic, among many more.

Serving as a powerful replacement to more theory-based quality management textbooks, Healthcare Quality Management provides context to challenging situations encountered by any healthcare manager, including the health administrator, nurse, physician, social worker, or allied health professional.

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• eBook Access–Included with print purchase so you can continue your studies on the go on mobile devices and computers
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• ISBN-10 0826145132
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• Publisher Springer Publishing Company
• Publication date February 21, 2020
• Language English
• Dimensions 7.2 x 0.8 x 9.9 inches
• Print length 404 pages
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Zachary Pruitt, PhD, MHA, CPH, is assistant professor and director of community practice at the University of South Florida College of Public Health.

Candace S. Smith, PhD, RN, NEA-BC, is chief nursing officer at Manatee Memorial Hospital.

Eddie Pérez-Ruberté, MS, is senior Lean project manager at BayCare Health Systems who leads the deployment of the Lean management system and culture. Eddie is a certified Lean expert and a certified Six Sigma Black Belt from the American Society for Quality. He also helps organizations implement Lean programs through his consulting company, Areito Group. Eddie is an instructor for the Institute of Industrial and Systems Engineers where he teaches Lean and Six Sigma and certifies students in these methodologies at multiple universities and healthcare organizations across the United States.

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The role of place on healthcare quality improvement: A qualitative case study of a teaching hospital

Affiliation.

• 1 Queen's Management School, Queen's University Belfast, Riddel Hall, 185 Stranmillis Road, Belfast, BT9 5EE, Northern Ireland, UK. Electronic address: [email protected].
• PMID: 29524869
• DOI: 10.1016/j.socscimed.2018.03.003

This article examines how the built environment impacts, and is impacted by, healthcare staff day to day practice, care outcomes and the design of new quality and patient safety (Q&PS) projects. It also explores how perceptions of the built environment affect inter-professional dynamics. In doing so, it contributes to the overlooked interplay between the physical, social, and symbolic dimensions associated with a hospital's place. The study draws on 46 in-depth semi-structured interviews conducted at a large teaching hospital in Portugal formed by two buildings. Interview transcripts were analysed inductively using thematic analysis. The major contribution of this study is to advance the understanding of the interactions among the different dimensions of place on Q&PS improvement. For example, findings indicate that some of the characteristics of the physical infrastructure of the hospital have a negative impact on the quality of care provided and/or significantly limit the initiatives that can be implemented to improve it, including refurbishment works. However, decisions on refurbishment works were also influenced by the characteristics of the patient population, hospital budget, etc. Likewise, clinicians' emotional reactions to the limitations of the buildings depended on their expectations of the buildings and the symbolic projections they attributed to them. Nevertheless, differences between clinicians' expectations regarding the physical infrastructure and its actual features influenced clinicians' views on Q&PS initiatives designed by non-clinicians.

Keywords: Case study; Healthcare quality management; Hospital; Patient safety; Place.

Copyright © 2018. Published by Elsevier Ltd.

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• Research Support, Non-U.S. Gov't
• Hospital Design and Construction*
• Hospitals, Teaching / statistics & numerical data*
• Organizational Case Studies
• Patient Safety
• Qualitative Research
• Quality Improvement / organization & administration*

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Case Study: The Implementation of Total Quality Management at the Charleston VA Medical Center's Dental Service

The views expressed in this article are those of the author and do not reflect the official policy or position of the U.S. Air Force, Department of Defense, or the Department of Veterans Affairs.

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Barry L. Matthews, Case Study: The Implementation of Total Quality Management at the Charleston VA Medical Center's Dental Service, Military Medicine , Volume 157, Issue 1, January 1992, Pages 21–24, https://doi.org/10.1093/milmed/157.1.21

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Total Quality Management (TQM) is an evolving management philosophy which has recently been introduced to the health care industry. TQM requires the use of a continuous process improvement methodology for delivered services. It was implemented at Charleston VAMC's Dental Service as a study to determine its effectiveness at the grassroots level. A modified Quality Circle was established within the clinical service under the guidance of Dr. Edward Deming's 14 principles. Top management support was not present. Many lessons were learned as process improvements were made. The overall success was limited due to the inability to address interdepartment process problems.

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ELEC 2022: Lean, Green and Sustainability pp 72–81 Cite as

A Lean Approach for Reducing Downtimes in Healthcare: A Case Study

• Stefano Frecassetti   ORCID: orcid.org/0000-0002-9649-314X 19 ,
• Matteo Ferrazzi   ORCID: orcid.org/0000-0001-9035-0773 19 &
• Alberto Portioli-Staudacher   ORCID: orcid.org/0000-0002-9807-1215 19  
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Part of the book series: IFIP Advances in Information and Communication Technology ((IFIPAICT,volume 668))

Lean Management is considered one of the most successful management paradigms for enhancing operational performance in the manufacturing environment. However, it has been applied throughout the years to several sectors and organisational areas, such as service, healthcare, and office departments. After the Covid-19 outbreak, increasing attention has been given to potential performance improvements in healthcare organisations by leveraging Lean. This paper intends to add further knowledge to this field by presenting a case study in a hospital. In this paper, a pilot project is presented carried out in a healthcare organisation. Lean methods were used to improve the operating room performance, particularly by reducing the operating room changeover time. The A3 template was used to drive the project and implement a new procedure using the Single Minute Exchange of Die (SMED) method. With the implementation of the new procedure, the changeover time between two different surgeries in the operating room was significantly reduced, together with a more stable and reliable process.

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Amati, M., et al.: Reducing changeover time between surgeries through lean thinking: an action research project. Front. Med. 9 (2022). https://doi.org/10.3389/fmed.2022.822964

Bharsakade, R.S., Acharya, P., Ganapathy, L., Tiwari, M.K.: A lean approach to healthcare management using multi criteria decision making. Opsearch 58 (3), 610–635 (2021). https://doi.org/10.1007/s12597-020-00490-5

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Frecassetti, S., Ferrazzi, M., Portioli-Staudacher, A. (2023). A Lean Approach for Reducing Downtimes in Healthcare: A Case Study. In: McDermott, O., Rosa, A., Sá, J.C., Toner, A. (eds) Lean, Green and Sustainability. ELEC 2022. IFIP Advances in Information and Communication Technology, vol 668. Springer, Cham. https://doi.org/10.1007/978-3-031-25741-4_8

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Metallurgicheskii Zavod Electrostal AO (Russia)

In 1993 "Elektrostal" was transformed into an open joint stock company. The factory occupies a leading position among the manufacturers of high quality steel. The plant is a producer of high-temperature nickel alloys in a wide variety. It has a unique set of metallurgical equipment: open induction and arc furnaces, furnace steel processing unit, vacuum induction, vacuum- arc furnaces and others. The factory has implemented and certified quality management system ISO 9000, received international certificates for all products. Elektrostal today is a major supplier in Russia starting blanks for the production of blades, discs and rolls for gas turbine engines. Among them are companies in the aerospace industry, defense plants, and energy complex, automotive, mechanical engineering and instrument-making plants.

Headquarters Ulitsa Zheleznodorozhnaya, 1 Elektrostal; Moscow Oblast; Postal Code: 144002

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