Understanding the integration of artificial intelligence in healthcare organisations and systems through the NASSS framework: a qualitative study in a leading Canadian academic centre.

BACKGROUND: Artificial intelligence (AI) technologies are expected to "revolutionise" healthcare. However, despite their promises, their integration within healthcare organisations and systems remains limited. The objective of this study is to explore and understand the systemic challenges and implications of their integration in a leading Canadian academic hospital. METHODS: Semi-structured interviews were conducted with 29 stakeholders concerned by the integration of a large set of AI technologies within the organisation (e.g., managers, clinicians, researchers, patients, technology providers). Data were collected and analysed using the Non-Adoption, Abandonment, Scale-up, Spread, Sustainability (NASSS) framework. RESULTS: Among enabling factors and conditions, our findings highlight: a supportive organisational culture and leadership leading to a coherent organisational innovation narrative; mutual trust and transparent communication between senior management and frontline teams; the presence of champions, translators, and boundary spanners for AI able to build bridges and trust; and the capacity to attract technical and clinical talents and expertise. Constraints and barriers include: contrasting definitions of the value of AI technologies and ways to measure such value; lack of real-life and context-based evidence; varying patients' digital and health literacy capacities; misalignments between organisational dynamics, clinical and administrative processes, infrastructures, and AI technologies; lack of funding mechanisms covering the implementation, adaptation, and expertise required; challenges arising from practice change, new expertise development, and professional identities; lack of official professional, reimbursement, and insurance guidelines; lack of pre- and post-market approval legal and governance frameworks; diversity of the business and financing models for AI technologies; and misalignments between investors' priorities and the needs and expectations of healthcare organisations and systems. CONCLUSION: Thanks to the multidimensional NASSS framework, this study provides original insights and a detailed learning base for analysing AI technologies in healthcare from a thorough socio-technical perspective. Our findings highlight the importance of considering the complexity characterising healthcare organisations and systems in current efforts to introduce AI technologies within clinical routines. This study adds to the existing literature and can inform decision-making towards a judicious, responsible, and sustainable integration of these technologies in healthcare organisations and systems.

Developing a typology of interventions to support doctors' mental health and wellbeing.

BACKGROUND: The problem of mental ill-health in doctors is complex, accentuated by the COVID-19 pandemic, and impacts on healthcare provision and broader organisational performance. There are many interventions to address the problem but currently no systematic way to categorise them, which makes it hard to describe and compare interventions. As a result, implementation tends to be unfocussed and fall short of the standards developed for implementing complex healthcare interventions. This study aims to develop: 1) a conceptual typology of workplace mental health and wellbeing interventions and 2) a mapping tool to apply the typology within research and practice. METHODS: Typology development was based on iterative cycles of analysis of published and in-practice interventions, incorporation of relevant theories and frameworks, and team and stakeholder group discussions. RESULTS: The newly developed typology and mapping tool enable interventions to be conceptualised and/or mapped into different categories, for example whether they are designed to be largely preventative (by either improving the workplace or increasing personal resources) or to resolve problems after they have arisen. Interventions may be mapped across more than one category to reflect the nuance and complexity in many mental health and wellbeing interventions. Mapping of interventions indicated that most publications have not clarified their underlying assumptions about what causes outcomes or the theoretical basis for the intervention. CONCLUSION: The conceptual typology and mapping tool aims to raise the quality of future research and promote clear thinking about the nature and purpose of interventions, In doing so it aims to support future research and practice in planning interventions to improve the mental health and wellbeing of doctors.

Theorising Support for Interdisciplinary Early-Career Researchers Using Communicative Genre and 'Rules of the Game'.

Qualitative social scientists working in medical faculties have to meet multiple expectations. On the one hand, they are expected to comply with the philosophical and theoretical expectations of the social sciences. On the other hand, they may also be expected to produce publications which align with biomedical definitions and framings of quality. As interdisciplinary scholars, they must handle (at least) two sets of journal editors, peer reviewers, grant-awarding panels, and conference audiences. In this paper, we extend the current knowledge base on the 'dual expectations' challenge by drawing on Orlikowski and Yates' theoretical concept of communicative genres. A 'genre' in this context is a format of communication (e.g. letter, email, academic paper, and conference presentation) aimed at a particular audience, having a particular material form and socio-linguistic style, and governed by both formal requirements and unwritten social rules. Becoming a member of any community of practice involves becoming familiar with its accepted communicative genres and adept in using them. Academic writing, for example, is a craft that is learned through participation in the social process of communicating one's ideas to one's peers in journal articles and other formats. In this reflective paper, we show how the concept of a communicative genre can sensitise us to the conflicting and often dissonant expectations and rule systems governing different academic fields. We use this key concept to suggest ways in which the faculty can support early-career researchers to progress in careers which straddle qualitative social science and medical science.

The usage of data in NHS primary care commissioning: a realist review.

BACKGROUND: Primary care has been described as the 'bedrock' of the National Health Service (NHS) accounting for approximately 90% of patient contacts but is facing significant challenges. Against a backdrop of a rapidly ageing population with increasingly complex health challenges, policy-makers have encouraged primary care commissioners to increase the usage of data when making commissioning decisions. Purported benefits include cost savings and improved population health. However, research on evidence-based commissioning has concluded that commissioners work in complex environments and that closer attention should be paid to the interplay of contextual factors and evidence use. The aim of this review was to understand how and why primary care commissioners use data to inform their decision making, what outcomes this leads to, and understand what factors or contexts promote and inhibit their usage of data. METHODS: We developed initial programme theory by identifying barriers and facilitators to using data to inform primary care commissioning based on the findings of an exploratory literature search and discussions with programme implementers. We then located a range of diverse studies by searching seven databases as well as grey literature. Using a realist approach, which has an explanatory rather than a judgemental focus, we identified recurrent patterns of outcomes and their associated contexts and mechanisms related to data usage in primary care commissioning to form context-mechanism-outcome (CMO) configurations. We then developed a revised and refined programme theory. RESULTS: Ninety-two studies met the inclusion criteria, informing the development of 30 CMOs. Primary care commissioners work in complex and demanding environments, and the usage of data are promoted and inhibited by a wide range of contexts including specific commissioning activities, commissioners' perceptions and skillsets, their relationships with external providers of data (analysis), and the characteristics of data themselves. Data are used by commissioners not only as a source of evidence but also as a tool for stimulating commissioning improvements and as a warrant for convincing others about decisions commissioners wish to make. Despite being well-intentioned users of data, commissioners face considerable challenges when trying to use them, and have developed a range of strategies to deal with 'imperfect' data. CONCLUSIONS: There are still considerable barriers to using data in certain contexts. Understanding and addressing these will be key in light of the government's ongoing commitments to using data to inform policy-making, as well as increasing integrated commissioning.

TRIPLE C reporting principles for case study evaluations of the role of context in complex interventions.

BACKGROUND: Guidance and reporting principles such as CONSORT (for randomised trials) and PRISMA (for systematic reviews) have greatly improved the reporting, discoverability, transparency and consistency of published research. We sought to develop similar guidance for case study evaluations undertaken to explore the influence of context on the processes and outcomes of complex interventions. METHODS: A range of experts were recruited to an online Delphi panel, sampling for maximum diversity in disciplines (e.g. public health, health services research, organisational studies), settings (e.g. country), and sectors (e.g. academic, policy, third sector). To inform panel deliberations, we prepared background materials based on: [a] a systematic meta-narrative review of empirical and methodological literatures on case study, context and complex interventions; [b] the collective experience of a network of health systems and public health researchers; and [c] the established RAMESES II standards (which cover one kind of case study). We developed a list of topics and issues based on these sources and encouraged panel members to provide free text comments. Their feedback informed development of a set of items in the form of questions for potential inclusion in the reporting principles. We circulated these by email, asking panel members to rank each potential item twice (for relevance and validity) on a 7-point Likert scale. This sequence was repeated twice. RESULTS: We recruited 51 panel members from 50 organisations across 12 countries, who brought experience of a range of case study research methods and applications. 26 completed all three Delphi rounds, reaching over 80% consensus on 16 items covering title, abstract, definitions of terms, philosophical assumptions, research question(s), rationale, how context and complexity relates to the intervention, ethical approval, empirical methods, findings, use of theory, generalisability and transferability, researcher perspective and influence, conclusions and recommendations, and funding and conflicts of interest. CONCLUSION: The 'Triple C' (Case study, Context, Complex interventions) reporting principles recognise that case studies are undertaken in different ways for different purposes and based on different philosophical assumptions. They are designed to be enabling rather than prescriptive, and to make case study evaluation reporting on context and complex health interventions more comprehensive, accessible and useable.

Mobilising context as complex and dynamic in evaluations of complex health interventions.

BACKGROUND: The relationship between healthcare interventions and context is widely conceived as involving complex and dynamic interactions over time. However, evaluations of complex health interventions frequently fail to mobilise such complexity, reporting context and interventions as reified and demarcated categories. This raises questions about practices shaping knowledge about context, with implications for who and what we make visible in our research. Viewed through the lens of case study research, we draw on data collected for the Triple C study (focused on Case study, Context and Complex interventions), to critique these practices, and call for system-wide changes in how notions of context are operationalised in evaluations of complex health interventions. METHODS: The Triple C study was funded by the Medical Research Council to develop case study guidance and reporting principles taking account of context and complexity. As part of this study, a one-day workshop with 58 participants and nine interviews were conducted with those involved in researching, evaluating, publishing, funding and developing policy and practice from case study research. Discussions focused on how to conceptualise and operationalise context within case study evaluations of complex health interventions. Analysis focused on different constructions and connections of context in relation to complex interventions and the wider social forces structuring participant's accounts. RESULTS: We found knowledge-making practices about context shaped by epistemic and political forces, manifesting as: tensions between articulating complexity and clarity of description; ontological (in)coherence between conceptualisations of context and methods used; and reified versions of context being privileged when communicating with funders, journals, policymakers and publics. CONCLUSION: We argue that evaluations of complex health interventions urgently requires wide-scale critical reflection on how context is mobilised - by funders, health services researchers, journal editors and policymakers. Connecting with how scholars approach complexity and context across disciplines provides opportunities for creatively expanding the field in which health evaluations are conducted, enabling a critical standpoint to long-established traditions and opening up possibilities for innovating the design of evaluations of complex health interventions.

Stakeholder Perspectives of Clinical Artificial Intelligence Implementation: Systematic Review of Qualitative Evidence.

BACKGROUND: The rhetoric surrounding clinical artificial intelligence (AI) often exaggerates its effect on real-world care. Limited understanding of the factors that influence its implementation can perpetuate this. OBJECTIVE: In this qualitative systematic review, we aimed to identify key stakeholders, consolidate their perspectives on clinical AI implementation, and characterize the evidence gaps that future qualitative research should target. METHODS: Ovid-MEDLINE, EBSCO-CINAHL, ACM Digital Library, Science Citation Index-Web of Science, and Scopus were searched for primary qualitative studies on individuals' perspectives on any application of clinical AI worldwide (January 2014-April 2021). The definition of clinical AI includes both rule-based and machine learning-enabled or non-rule-based decision support tools. The language of the reports was not an exclusion criterion. Two independent reviewers performed title, abstract, and full-text screening with a third arbiter of disagreement. Two reviewers assigned the Joanna Briggs Institute 10-point checklist for qualitative research scores for each study. A single reviewer extracted free-text data relevant to clinical AI implementation, noting the stakeholders contributing to each excerpt. The best-fit framework synthesis used the Nonadoption, Abandonment, Scale-up, Spread, and Sustainability (NASSS) framework. To validate the data and improve accessibility, coauthors representing each emergent stakeholder group codeveloped summaries of the factors most relevant to their respective groups. RESULTS: The initial search yielded 4437 deduplicated articles, with 111 (2.5%) eligible for inclusion (median Joanna Briggs Institute 10-point checklist for qualitative research score, 8/10). Five distinct stakeholder groups emerged from the data: health care professionals (HCPs), patients, carers and other members of the public, developers, health care managers and leaders, and regulators or policy makers, contributing 1204 (70%), 196 (11.4%), 133 (7.7%), 129 (7.5%), and 59 (3.4%) of 1721 eligible excerpts, respectively. All stakeholder groups independently identified a breadth of implementation factors, with each producing data that were mapped between 17 and 24 of the 27 adapted Nonadoption, Abandonment, Scale-up, Spread, and Sustainability subdomains. Most of the factors that stakeholders found influential in the implementation of rule-based clinical AI also applied to non-rule-based clinical AI, with the exception of intellectual property, regulation, and sociocultural attitudes. CONCLUSIONS: Clinical AI implementation is influenced by many interdependent factors, which are in turn influenced by at least 5 distinct stakeholder groups. This implies that effective research and practice of clinical AI implementation should consider multiple stakeholder perspectives. The current underrepresentation of perspectives from stakeholders other than HCPs in the literature may limit the anticipation and management of the factors that influence successful clinical AI implementation. Future research should not only widen the representation of tools and contexts in qualitative research but also specifically investigate the perspectives of all stakeholder HCPs and emerging aspects of non-rule-based clinical AI implementation. TRIAL REGISTRATION: PROSPERO (International Prospective Register of Systematic Reviews) CRD42021256005; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=256005. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/33145.

Implementation and delivery of group consultations for young people with diabetes in socioeconomically deprived, ethnically diverse settings.

BACKGROUND: Young people with diabetes experience poor clinical and psychosocial outcomes, and consider the health service ill-equipped in meeting their needs. Improvements, including alternative consulting approaches, are required to improve care quality and patient engagement. We examined how group-based, outpatient diabetes consultations might be delivered to support young people (16-25 years old) in socio-economically deprived, ethnically diverse settings. METHODS: This multi-method, comparative study recruited a total of 135 young people with diabetes across two implementation and two comparison sites (2017-2019). Informed by a 'researcher-in-residence' approach and complexity theory, we used a combination of methods: (a) 31 qualitative interviews with young people and staff and ethnographic observation in group and individual clinics, (b) quantitative analysis of sociodemographic, clinical, service use, and patient enablement data, and (c) micro-costing analysis. RESULTS: Implementation sites delivered 29 group consultations in total. Overall mean attendance per session was low, but a core group of young people attended repeatedly. They reported feeling better understood and supported, gaining new learning from peers and clinicians, and being better prepared to normalise diabetes self-care. Yet, there were also instances where peer comparison proved difficult to manage. Group consultations challenged deeply embedded ways of thinking about care provision and required staff to work flexibly to achieve local tailoring, sustain continuity, and safely manage complex interdependencies with other care processes. Set-up and delivery were time-consuming and required in-depth clinical and relational knowledge of patients. Facilitation by an experienced youth worker was instrumental. There was indication that economic value could derive from preventing at least one unscheduled consultation annually. CONCLUSIONS: Group consulting can provide added value when tailored to meet local needs rather than following standardised approaches. This study illustrates the importance of adaptive capability and self-organisation when integrating new models of care, with young people as active partners in shaping service provision. TRIAL REGISTRATION: ISRCTN reference 27989430.

Patient-initiated cardiovascular monitoring with commercially available devices: How useful is it in a cardiology outpatient setting? Mixed methods, observational study.

BACKGROUND: The availability, affordability and utilisation of commercially available self-monitoring devices is increasing, but their impact on routine clinical decision-making remains little explored. We sought to examine how patient-generated cardiovascular data influenced clinical evaluation in UK cardiology outpatient clinics and to understand clinical attitudes and experiences with using data from commercially available self-monitoring devices. METHODS: Mixed methods study combining: a) quantitative and qualitative content analysis of 1373 community cardiology clinic letters, recording consultations between January-September 2020 including periods with different Covid-19 related restrictions, and b) semi-structured qualitative interviews and group discussions with 20 cardiology-affiliated clinicians at the same NHS Trust. RESULTS: Patient-generated cardiovascular data were described in 185/1373 (13.5%) clinic letters overall, with the proportion doubling following onset of the first Covid-19 lockdown in England, from 8.3% to 16.6% (p < 0.001). In 127/185 (69%) cases self-monitored data were found to: provide or facilitate cardiac diagnoses (34/127); assist management of previously diagnosed cardiac conditions (55/127); be deployed for cardiovascular prevention (16/127); or be recommended for heart rhythm evaluation (10/127). In 58/185 (31%) cases clinicians did not put the self-monitored data to any evident use and in 12/185 (6.5%) cases patient-generated data prompted an unnecessary referral. In interviews and discussions, clinicians expressed mixed views on patient-generated data but foresaw a need to embrace and plan for this information flow, and proactively address challenges with integration into traditional care pathways. CONCLUSIONS: This study suggests patient-generated data are being used for clinical decision-making in ad hoc and opportunistic ways. Given shifts towards remote monitoring in clinical care, accelerated by the pandemic, there is a need to consider how best to incorporate patient-generated data in clinical processes, introduce relevant training, pathways and governance frameworks, and manage associated risks.

Evaluating complex interventions in context: systematic, meta-narrative review of case study approaches.

BACKGROUND: There is a growing need for methods that acknowledge and successfully capture the dynamic interaction between context and implementation of complex interventions. Case study research has the potential to provide such understanding, enabling in-depth investigation of the particularities of phenomena. However, there is limited guidance on how and when to best use different case study research approaches when evaluating complex interventions. This study aimed to review and synthesise the literature on case study research across relevant disciplines, and determine relevance to the study of contextual influences on complex interventions in health systems and public health research. METHODS: Systematic meta-narrative review of the literature comprising (i) a scoping review of seminal texts (n = 60) on case study methodology and on context, complexity and interventions, (ii) detailed review of empirical literature on case study, context and complex interventions (n = 71), and (iii) identifying and reviewing 'hybrid papers' (n = 8) focused on the merits and challenges of case study in the evaluation of complex interventions. RESULTS: We identified four broad (and to some extent overlapping) research traditions, all using case study in a slightly different way and with different goals: 1) developing and testing complex interventions in healthcare; 2) analysing change in organisations; 3) undertaking realist evaluations; 4) studying complex change naturalistically. Each tradition conceptualised context differently-respectively as the backdrop to, or factors impacting on, the intervention; sets of interacting conditions and relationships; circumstances triggering intervention mechanisms; and socially structured practices. Overall, these traditions drew on a small number of case study methodologists and disciplines. Few studies problematised the nature and boundaries of 'the case' and 'context' or considered the implications of such conceptualisations for methods and knowledge production. CONCLUSIONS: Case study research on complex interventions in healthcare draws on a number of different research traditions, each with different epistemological and methodological preferences. The approach used and consequences for knowledge produced often remains implicit. This has implications for how researchers, practitioners and decision makers understand, implement and evaluate complex interventions in different settings. Deeper engagement with case study research as a methodology is strongly recommended.

Interrogating the promise of technology in epilepsy care: systematic, hermeneutic review.

Technology development is gathering pace in epilepsy with seizure detection devices promising to transform self-care and service provision. However, such accounts often neglect the uncertainties, displacements and responsibilities that technology-supported care generates. This review brings together a heterogeneous literature, identified through systematic searches in 8 databases and snowball searching, to interrogate how technology becomes positioned in epilepsy care. We took a hermeneutic approach in our analysis of the 206 included articles, which resulted in the development of a conceptual framework surfacing the underlying logics by which technology-supported epilepsy care is organised. Each of these logics enacts different techno-scientific futures and carries specific assumptions about how (often imagined) 'users' and their bodies become co-constituted. Our review shows that studies in this area remain primarily deterministic and technology-focused. Few draw phenomenological insights on lived experiences with epilepsy or use social theory to problematise the role of technology. We propose future directions for sociotechnical, theory-driven studies of technology in epilepsy care and offer a framework transferable across other long-term conditions.

Spread, Scale-up, and Sustainability of Video Consulting in Health Care: Systematic Review and Synthesis Guided by the NASSS Framework.

BACKGROUND: COVID-19 has thrust video consulting into the limelight, as health care practitioners worldwide shift to delivering care remotely. Evidence suggests that video consulting is acceptable, safe, and effective in selected conditions and settings. However, research to date has mostly focused on initial adoption, with limited consideration of how video consulting can be mainstreamed and sustained. OBJECTIVE: This study sought to do the following: (1) review and synthesize reported opportunities, challenges, and lessons learned in the scale-up, spread, and sustainability of video consultations, and (2) identify transferable insights that can inform policy and practice. METHODS: We identified papers through systematic searches in PubMed, CINAHL, and Web of Science. Included articles reported on synchronous, video-based consultations that had spread to more than one setting beyond an initial pilot or feasibility stage, and were published since 2010. We used the Nonadoption, Abandonment, and challenges to the Scale-up, Spread, and Sustainability (NASSS) framework to synthesize findings relating to 7 domains: an understanding of the health condition(s) for which video consultations were being used, the material properties of the technological platform and relevant peripherals, the value proposition for patients and developers, the role of the adopter system, organizational factors, wider macro-level considerations, and emergence over time. RESULTS: We identified 13 papers describing 10 different video consultation services in 6 regions, covering the following: (1) video-to-home services, connecting providers directly to the patient; (2) hub-and-spoke models, connecting a provider at a central hub to a patient at a rural center; and (3) large-scale top-down evaluations scaled up or spread across a national health administration. Services covered rehabilitation, geriatrics, cancer surgery, diabetes, and mental health, as well as general specialist care and primary care. Potential enablers of spread and scale-up included embedded leadership and the presence of a telehealth champion, appropriate reimbursement mechanisms, user-friendly technology, pre-existing staff relationships, and adaptation (of technology and services) over time. Challenges tended to be related to service development, such as the absence of a long-term strategic plan, resistance to change, cost and reimbursement issues, and the technical experience of staff. There was limited articulation of the challenges to scale-up and spread of video consultations. This was combined with a lack of theorization, with papers tending to view spread and scale-up as the sum of multiple technical implementations, rather than theorizing the distinct processes required to achieve widespread adoption. CONCLUSIONS: There remains a significant lack of evidence that can support the spread and scale-up of video consulting. Given the recent pace of change due to COVID-19, a more definitive evidence base is urgently needed to support global efforts and match enthusiasm for extending use.

We Need to Talk About Complexity in Health Research: Findings From a Focused Ethnography.

There is increasing focus on complexity-informed approaches across health disciplines. This attention takes several forms, but commonly involves framing research topics as "complex" to justify use of particular methods (e.g., qualitative). Little emphasis is placed on how divergent and convergent ways of knowing complexity become negotiated within academic communities. Drawing on findings from a focused ethnography of an international workshop, we illustrate how health researchers employ "boundary-ordering devices" to navigate different meanings ascribed to complexity while they attempt to sustain interdisciplinary communication and collaboration. These include (a) surfacing (but not resolving) tensions between philosophical grounding of knowledge claims and need for practical purchase, (b) employing techniques of representation and abstraction, and (c) drawing on the fluid, ongoing accomplishment of complexity for different audiences and purposes. Our findings have implications for progressing complexity-informed health research, particularly with respect to qualitative approaches.

'From disaster, miracles are wrought': a narrative analysis of UK media depictions of remote GP consulting in the COVID-19 pandemic using Burke's pentad.

During crises (major events characterised by uncertainty, urgency and threat), society must make sense of rapidly unfolding events. This happens mainly through narrativising-depicting a setting, characters and a meaningful sequence of events and actions unfolding over time. In the early months of the pandemic, UK general practice shifted from face-to-face consultations to a remote-by-default model (telephone, video or e-consultation). This shift was initially widely accepted by press and public, but support waned after a politician declared that the change would be permanent. We invoke Burke's dramatistic pentad of act, scene, agent, agency and purpose to theorise findings from a detailed analysis of media coverage of the remote-by-default policy and reactions to it. We consider the 12 weeks from March to June 2020 (first lockdown, when remote-by-default services had just been introduced) and 1 week from late July 2020 (following the ministerial announcement). The initial introduction of remote consulting had strong narrative coherence in which all parts of the pentad were balanced: scene (a deadly virus threatening the country) aligned with act (lockdown, including avoiding face-to-face appointments unless essential), agents (the National Health Service and digital technology as heroic macro-actors), agency (general practitioners 'deployed') and purpose (to control the pandemic). The later period, however, was characterised by a mismatch between scene (a country emerging from lockdown and resuming normal life), act (imposition of the remote model), agent (a politician known for his enthusiasm for technology), agency (top-down directive) and purpose (modernisation). Whereas media narratives in the first period aligned with the genre of heroic adventure (suggesting a worthy battle, bravely fought), those of the second had characteristics of farce (something both comic and grotesque). We conclude that close reading of media narratives may surface potential misalignments between policy decisions and the context in which they must be implemented.

Case study research for better evaluations of complex interventions: rationale and challenges.

BACKGROUND: The need for better methods for evaluation in health research has been widely recognised. The 'complexity turn' has drawn attention to the limitations of relying on causal inference from randomised controlled trials alone for understanding whether, and under which conditions, interventions in complex systems improve health services or the public health, and what mechanisms might link interventions and outcomes. We argue that case study research-currently denigrated as poor evidence-is an under-utilised resource for not only providing evidence about context and transferability, but also for helping strengthen causal inferences when pathways between intervention and effects are likely to be non-linear. MAIN BODY: Case study research, as an overall approach, is based on in-depth explorations of complex phenomena in their natural, or real-life, settings. Empirical case studies typically enable dynamic understanding of complex challenges and provide evidence about causal mechanisms and the necessary and sufficient conditions (contexts) for intervention implementation and effects. This is essential evidence not just for researchers concerned about internal and external validity, but also research users in policy and practice who need to know what the likely effects of complex programmes or interventions will be in their settings. The health sciences have much to learn from scholarship on case study methodology in the social sciences. However, there are multiple challenges in fully exploiting the potential learning from case study research. First are misconceptions that case study research can only provide exploratory or descriptive evidence. Second, there is little consensus about what a case study is, and considerable diversity in how empirical case studies are conducted and reported. Finally, as case study researchers typically (and appropriately) focus on thick description (that captures contextual detail), it can be challenging to identify the key messages related to intervention evaluation from case study reports. CONCLUSION: Whilst the diversity of published case studies in health services and public health research is rich and productive, we recommend further clarity and specific methodological guidance for those reporting case study research for evaluation audiences.

Optimising strategies to address mental ill-health in doctors and medical students: 'Care Under Pressure' realist review and implementation guidance.

BACKGROUND: Mental ill-health in health professionals, including doctors, is a global and growing concern. The existing literature on interventions that offer support, advice and/or treatment to sick doctors has not yet been synthesised in a way that considers the complexity and heterogeneity of the interventions, and the many dimensions of the problem. We (1) reviewed interventions to tackle doctors' and medical students' mental ill-health and its impacts on the clinical workforce and patient care-drawing on diverse literature sources and engaging iteratively with diverse stakeholder perspectives-and (2) produced recommendations that support the tailoring, implementation, monitoring and evaluation of contextually sensitive strategies to tackle mental ill-health and its impacts. METHODS: Realist literature review consistent with the RAMESES quality and reporting standards. Sources for inclusion were identified through bibliographic database searches supplemented by purposive searches-resulting also from engagement with stakeholders. Data were extracted from included articles and subjected to realist analysis to identify (i) mechanisms causing mental ill-health in doctors and medical students and relevant contexts or circumstances when these mechanisms were likely to be 'triggered' and (ii) 'guiding principles' and features underpinning the interventions and recommendations discussed mostly in policy document, reviews and commentaries. RESULTS: One hundred seventy-nine records were included. Most were from the USA (45%) and were published since 2009 (74%). The analysis showed that doctors were more likely to experience mental ill-health when they felt isolated or unable to do their job and when they feared repercussions of help-seeking. Healthy staff were necessary for excellent patient care. Interventions emphasising relationships and belonging were more likely to promote wellbeing. Interventions creating a people-focussed working culture, balancing positive/negative performance and acknowledging positive/negative aspects of a medical career helped doctors to thrive. The way that interventions were implemented seemed critically important. Doctors and medical students needed to have confidence in an intervention for the intervention to be effective. CONCLUSIONS: Successful interventions to tackle doctors' and students' mental ill-health are likely to be multidimensional and multilevel and involve multiple stakeholders. Evaluating and improving existing interventions is likely to be more effective than developing new ones. Our evidence synthesis provides a basis on which to do this. STUDY REGISTRATION: PROSPERO CRD42017069870. Research project webpage http://sites.exeter.ac.uk/cup/.

Optimising feedback for early career professionals: a scoping review and new framework.

CONTEXT: Meta-analyses have shown that feedback can be a powerful intervention to increase learning and performance but there is significant variability in impact. New trials are adding little to the question of whether feedback interventions are effective, so the focus now is how to optimise the effect. Early career professionals (ECPs) in busy work environments are a particularly important target group. This literature review aimed to synthesise information to support the optimal design of feedback interventions for ECPs. METHODS: We undertook a scoping literature review, using search terms such as 'feedback' and 'effectiveness' in MEDLINE, MEDLINE-In-Process, PsycINFO, CINAHL, Education Research Complete, Education Resources Information Center, the Cochrane Database of Systematic Reviews, the Social Sciences Citation Index and Applied Social Sciences Index and Abstracts, to identify empirical studies describing feedback interventions in busy workplaces published in English since 1990. We applied inclusion criteria to identify studies for the mapping stage and extracted key data to inform the next stage. We then selected a subset of papers for the framework development stage, which were subjected to a thematic synthesis by three authors, leading to a new feedback framework and a modified version of feedback intervention theory specifically for ECPs. RESULTS: A total of 80 studies were included in the mapping stage, with roughly equal studies from hospital settings and school classrooms, and 17 papers were included in the framework development stage. The feedback framework comprised three main categories (audit, feedback and goal setting) and 22 subcategories. The review highlighted the limited empirical research focusing solely on feedback for ECPs, which was surprising given the particular nuances in feedback for ECPs identified through this study. CONCLUSIONS: We offer the feedback framework to optimise the design of future feedback interventions for early career professionals and encourage future feedback research to move away from generic models and tailor work to specific target audiences.

Infrastructure Revisited: An Ethnographic Case Study of how Health Information Infrastructure Shapes and Constrains Technological Innovation.

BACKGROUND: Star defined infrastructure as something other things "run on"; it consists mainly of "boring things." Building on her classic 1999 paper, and acknowledging contemporary developments in technologies, services, and systems, we developed a new theorization of health information infrastructure with five defining characteristics: (1) a material scaffolding, backgrounded when working and foregrounded upon breakdown; (2) embedded, relational, and emergent; (3) collectively learned, known, and practiced (through technologically-supported cooperative work and organizational routines); (4) patchworked (incrementally built and fixed) and path-dependent (influenced by technical and socio-cultural legacies); and (5) institutionally supported and sustained (eg, embodying standards negotiated and overseen by regulatory and professional bodies). OBJECTIVE: Our theoretical objective was, in a health care context, to explore what information infrastructure is and how it shapes, supports, and constrains technological innovation. Our empirical objective was to examine the challenges of implementing and scaling up video consultation services. METHODS: In this naturalistic case study, we collected a total of 450 hours of ethnographic observations, over 100 interviews, and about 100 local and national documents over 54 months. Sensitized by the characteristics of infrastructure, we sought examples of infrastructural challenges that had slowed implementation and scale-up. We arranged data thematically to gain familiarity before undertaking an analysis informed by strong structuration, neo-institutional, and social practice theories, together with elements taken from the actor-network theory. RESULTS: We documented scale-up challenges at three different sites in our original case study, all of which relate to "boring things": the selection of a platform to support video-mediated consultations, the replacement of desktop computers with virtual desktop infrastructure profiles, and problems with call quality. In a fourth subcase, configuration issues with licensed video-conferencing software limited the spread of the innovation to another UK site. In all four subcases, several features of infrastructure were evident, including: (1) intricacy and lack of dependability of the installed base; (2) interdependencies of technologies, processes, and routines, such that a fix for one problem generated problems elsewhere in the system; (3) the inertia of established routines; (4) the constraining (and, occasionally, enabling) effect of legacy systems; and (5) delays and conflicts relating to clinical quality and safety standards. CONCLUSIONS: Innovators and change agents who wish to introduce new technologies in health services and systems should: (1) attend to materiality (eg, expect bugs and breakdowns, and prioritize basic dependability over advanced functionality); (2) take a systemic and relational view of technologies (versus as an isolated tool or function); (3) remember that technology-supported work is cooperative and embedded in organizational routines, which are further embedded in other routines; (4) innovate incrementally, taking account of technological and socio-cultural legacies; (5) consider standards but also where these standards come from and what priorities and interests they represent; and (6) seek to create leeway for these standards to be adapted to different local conditions.

Studying complexity in health services research: desperately seeking an overdue paradigm shift.

Complexity is much talked about but sub-optimally studied in health services research. Although the significance of the complex system as an analytic lens is increasingly recognised, many researchers are still using methods that assume a closed system in which predictive studies in general, and controlled experiments in particular, are possible and preferred. We argue that in open systems characterised by dynamically changing inter-relationships and tensions, conventional research designs predicated on linearity and predictability must be augmented by the study of how we can best deal with uncertainty, unpredictability and emergent causality. Accordingly, the study of complexity in health services and systems requires new standards of research quality, namely (for example) rich theorising, generative learning, and pragmatic adaptation to changing contexts. This framing of complexity-informed health services research provides a backdrop for a new collection of empirical studies. Each of the initial five papers in this collection illustrates, in different ways, the value of theoretically grounded, methodologically pluralistic, flexible and adaptive study designs. We propose an agenda for future research and invite researchers to contribute to this on-going series.

Analysing the role of complexity in explaining the fortunes of technology programmes: empirical application of the NASSS framework.

BACKGROUND: Failures and partial successes are common in technology-supported innovation programmes in health and social care. Complexity theory can help explain why. Phenomena may be simple (straightforward, predictable, few components), complicated (multiple interacting components or issues) or complex (dynamic, unpredictable, not easily disaggregated into constituent components). The recently published NASSS framework applies this taxonomy to explain Non-adoption or Abandonment of technology by individuals and difficulties achieving Scale-up, Spread and Sustainability. This paper reports the first empirical application of the NASSS framework. METHODS: Six technology-supported programmes were studied using ethnography and action research for up to 3 years across 20 health and care organisations and 10 national-level bodies. They comprised video outpatient consultations, GPS tracking technology for cognitive impairment, pendant alarm services, remote biomarker monitoring for heart failure, care organising software and integrated case management via data warehousing. Data were collected at three levels: micro (individual technology users), meso (organisational processes and systems) and macro (national policy and wider context). Data analysis and synthesis were guided by socio-technical theories and organised around the seven NASSS domains: (1) the condition or illness, (2) the technology, (3) the value proposition, (4) the adopter system (professional staff, patients and lay carers), (5) the organisation(s), (6) the wider (institutional and societal) system and (7) interaction and mutual adaptation among all these domains over time. RESULTS: The study generated more than 400 h of ethnographic observation, 165 semi-structured interviews and 200 documents. The six case studies raised multiple challenges across all seven domains. Complexity was a common feature of all programmes. In particular, individuals' health and care needs were often complex and hence unpredictable and 'off algorithm'. Programmes in which multiple domains were complicated proved difficult, slow and expensive to implement. Those in which multiple domains were complex did not become mainstreamed (or, if mainstreamed, did not deliver key intended outputs). CONCLUSION: The NASSS framework helped explain the successes, failures and changing fortunes of this diverse sample of technology-supported programmes. Since failure is often linked to complexity across multiple NASSS domains, further research should systematically address ways to reduce complexity and/or manage programme implementation to take account of it.