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Health and care information technologies can improve service delivery, but unfortunately many fail to realise their potential. This is because tools fail to effectively integrate with user and organisational practices. We here draw on two decades and an extensive body of practical and theoretical experience of conducting formative evaluations in health service settings to extract seven essential principles for planning and developing digital tools. Firstly, it is important to determine if digitalisation is the right approach for the desired change and to view these tools as complex interventions needing careful planning. The development process should embrace varying levels of co-creation and adapt to different needs and contexts. Ensuring that tools integrate well with existing information infrastructures and striking a balance between being widely applicable and locally relevant is essential. Furthermore, planning for how these interventions will fit into broader health and care pathways is vital. By considering these factors, decision-makers can significantly improve the chances of successful implementation, adoption and scaling of health and care technologies., Competing Interests: Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

Introduction: Remote monitoring can strengthen postoperative care in the community and minimise the burden of complications. However, implementation requires a clear understanding of how to sustainably integrate such complex interventions into existing care pathways. This study aimed to explore perceptions of potential facilitators and barriers to the implementation of digital remote postoperative monitoring from key stakeholders and derive recommendations for an implementable service., Methods: A qualitative implementation study was conducted of digital remote postoperative wound monitoring across two UK tertiary care hospitals. All enrolled patients undergoing general surgery, and all staff involved in postoperative care were eligible. Criterion-based purposeful sampling was used to select stakeholders for semi-structured interviews on their perspectives and experiences of digital remote postoperative monitoring. A theory-informed deductive-inductive qualitative analysis was conducted; drawing on normalisation process theory (NPT) to determine facilitators for and barriers to implementation within routine care., Results: There were 28 semi-structured interviews conducted with patients (n = 14) and healthcare professionals (n = 14). Remote postoperative monitoring was perceived to fulfil an unmet need in facilitating the diagnosis and treatment of postoperative complications. Participants perceived clear benefit to both the delivery of health services, and patient outcomes and experience, but some were concerned that this may not be equally shared due to potential issues with accessibility. The COVID-19 pandemic demonstrated telemedicine services are feasible to deliver and acceptable to participants, with examples of nurse-led remote postoperative monitoring currently supported within local care pathways. However, there was a discrepancy between patients' expectations regarding digital health to provide more personalised care, and the capacity of healthcare staff to deliver on these. Without further investment into IT infrastructure and allocation of staff, healthcare staff felt remote postoperative monitoring should be prioritised only for patients at the highest risk of complications., Conclusion: The COVID-19 pandemic has sparked the digital transformation of international health systems, yet the potential of digital health interventions has yet to be realised. The benefits to stakeholders are clear, and if health systems seek to meet governmental policy and patient expectations, there needs to be greater organisational strategy and investment to ensure appropriate deployment and adoption into routine care., Trial Registration: NCT05069103., (© 2024. The Author(s).)

Background: Antibiotic resistant infections cause over 700,000 deaths worldwide annually. As antimicrobial stewardship (AMS) helps minimise the emergence of antibiotic resistance resulting from inappropriate use of antibiotics in healthcare, we developed ePAMS+ (ePrescribing-based Anti-Microbial Stewardship), an ePrescribing and Medicines Administration (EPMA) system decision-support tool complemented by educational, behavioural and organisational elements., Methods: We conducted a non-randomised before-and-after feasibility trial, implementing ePAMS+ in two English hospitals using the Cerner Millennium EPMA system. Wards of several specialties were included. Patient participants were blinded to whether ePAMS+ was in use; prescribers were not. A mixed-methods evaluation aimed to establish: acceptability and usability of ePAMS+ and trial processes; feasibility of ePAMS+ implementation and quantitative outcome recording; and a Fidelity Index measuring the extent to which ePAMS+ was delivered as intended. Longitudinal semi-structured interviews of doctors, nurses and pharmacists, alongside non-participant observations, gathered qualitative data; we extracted quantitative prescribing data from the EPMA system. Normal linear modelling of the defined daily dose (DDD) of antibiotic per admission quantified its variability, to inform sample size calculations for a future trial of ePAMS+ effectiveness., Results: The research took place during the SARS-CoV-2 pandemic, from April 2021 to November 2022. 60 qualitative interviews were conducted (33 before ePAMS+ implementation, 27 after). 1,958 admissions (1,358 before ePAMS+ implementation; 600 after) included 24,884 antibiotic orders. Qualitative interviews confirmed that some aspects of ePAMS+ , its implementation and training were acceptable, while other features (e.g. enabling combinations of antibiotics to be prescribed) required further development. ePAMS+ uptake was low (28 antibiotic review records from 600 admissions; 0.047 records per admission), preventing full development of a Fidelity Index. Normal linear modelling of antibiotic DDD per admission showed a residual variance of 1.086 (log-transformed scale). Unavailability of indication data prevented measurement of some outcomes (e.g. number of antibiotic courses per indication)., Conclusions: This feasibility trial encountered unforeseen circumstances due to contextual factors and a global pandemic, highlighting the need for careful adaptation of complex intervention implementations to the local setting. We identified key refinements to ePAMS+ to support its wider adoption in clinical practice, requiring further piloting before a confirmatory effectiveness trial., Trial Registration: ISRCTN Registry ISRCTN13429325, 24 March 2022., (© 2024. The Author(s).)

Given the requirement to minimize the risks and maximize the benefits of technology applications in health care provision, there is an urgent need to incorporate theory-informed health IT (HIT) evaluation frameworks into existing and emerging guidelines for the evaluation of artificial intelligence (AI). Such frameworks can help developers, implementers, and strategic decision makers to build on experience and the existing empirical evidence base. We provide a pragmatic conceptual overview of selected concrete examples of how existing theory-informed HIT evaluation frameworks may be used to inform the safe development and implementation of AI in health care settings. The list is not exhaustive and is intended to illustrate applications in line with various stakeholder requirements. Existing HIT evaluation frameworks can help to inform AI-based development and implementation by supporting developers and strategic decision makers in considering relevant technology, user, and organizational dimensions. This can facilitate the design of technologies, their implementation in user and organizational settings, and the sustainability and scalability of technologies., (©Kathrin Cresswell, Nicolette de Keizer, Farah Magrabi, Robin Williams, Michael Rigby, Mirela Prgomet, Polina Kukhareva, Zoie Shui-Yee Wong, Philip Scott, Catherine K Craven, Andrew Georgiou, Stephanie Medlock, Jytte Brender McNair, Elske Ammenwerth. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 07.08.2024.)

Background: Antimicrobial resistance (AMR) represents a growing concern for public health., Objective: We sought to explore the challenges associated with development and implementation of a complex intervention designed to improve AMS in hospitals., Methods: We conducted a qualitative evaluation of a complex AMS intervention with educational, behavioral, and technological components in 5 wards of an English hospital. At 2 weeks and 7 weeks after initiating the intervention, we interviewed 25 users of the intervention, including senior and junior prescribers, a senior nurse, a pharmacist, and a microbiologist. Topics discussed included perceived impacts of different elements of the intervention and facilitators and barriers to effective use. Interviews were supplemented by 2 observations of ward rounds to gain insights into AMS practices. Data were audio-recorded, transcribed, and inductively and deductively analyzed thematically using NVivo12., Results: Tracing the adoption and impact of the various components of the intervention was difficult, as it had been introduced into a setting with competing pressures. These particularly affected behavioral and educational components (eg, training, awareness-building activities), which were often delivered ad hoc. We found that the participatory intervention design had addressed typical use cases but had not catered for edge cases that only became visible when the intervention was delivered in real-world settings (eg, variations in prescribing workflows across different specialties and conditions)., Conclusions: Effective user-focused design of complex interventions to promote AMS can support acceptance and use. However, not all requirements and potential barriers to use can be fully anticipated or tested in advance of full implementation in real-world settings., (©Kathrin Cresswell, Susan Hinder, Aziz Sheikh, Neil Watson, David Price, Andrew Heed, Sarah Katie Pontefract, Jamie Coleman, Jillian Beggs, Antony Chuter, Ann Slee, Robin Williams. Originally published in JMIR Formative Research (https://formative.jmir.org), 26.07.2024.)

Objectives: Adverse childhood experiences (ACEs) can affect individuals' resilience to stressors and their vulnerability to mental, physical and social harms. This study explored associations between ACEs, financial coping during the cost-of-living crisis and perceived impacts on health and well-being., Design: National cross-sectional face-to-face survey. Recruitment used a random quota sample of households stratified by health region and deprivation quintile., Setting: Households in Wales, UK., Participants: 1880 Welsh residents aged ≥18 years., Measures: Outcome variables were perceived inability to cope financially during the cost-of-living crisis; rising costs of living causing substantial distress and anxiety; and self-reported negative impact of rising costs of living on mental health, physical health, family relationships, local levels of antisocial behaviour and violence, and community support. Nine ACEs were measured retrospectively. Socioeconomic and demographic variables included low household income, economic inactivity, residential deprivation and activity limitation., Results: The prevalence of all outcomes increased strongly with ACE count. Perceived inability to cope financially during the cost-of-living crisis increased from 14.0% with 0 ACEs to 51.5% with 4+ ACEs. Relationships with ACEs remained after controlling for socioeconomic and demographic factors. Those with 4+ ACEs (vs 0 ACEs) were over three times more likely to perceive they would be unable to cope financially and, correspondingly, almost three times more likely to report substantial distress and anxiety and over three times more likely to report negative impacts on mental health, physical health and family relationships., Conclusions: Socioeconomically deprived populations are recognised to be disproportionately impacted by rising costs of living. Our study identifies a history of ACEs as an additional vulnerability that can affect all socioeconomic groups. Definitions of vulnerability during crises and communications with services on who is most likely to be impacted should consider childhood adversity and history of trauma., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Objectives: With an increasing focus on the digitalization of health and care settings, there is significant scope to learn from international approaches to promote concerted adoption of electronic health records., Materials and Methods: We review three large-scale initiatives from Australia, Canada, and England, and extract common lessons for future health and social care transformation strategy., Results: We discuss how, despite differences in contexts, concerted adoption enables sharing of experience and learning to streamline the digital transformation of health and care., Discussion and Conclusion: Concerted adoption can be accelerated through building communities of expertise and partnerships promoting knowledge transfer and circulation of expertise; commonalities in geographical and cultural contexts; and commonalities in technological systems., (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Objectives: Artificial intelligence (AI)-based clinical decision support systems to aid diagnosis are increasingly being developed and implemented but with limited understanding of how such systems integrate with existing clinical work and organizational practices. We explored the early experiences of stakeholders using an AI-based imaging software tool Veye Lung Nodules (VLN) aiding the detection, classification, and measurement of pulmonary nodules in computed tomography scans of the chest., Materials and Methods: We performed semistructured interviews and observations across early adopter deployment sites with clinicians, strategic decision-makers, suppliers, patients with long-term chest conditions, and academics with expertise in the use of diagnostic AI in radiology settings. We coded the data using the Technology, People, Organizations, and Macroenvironmental factors framework., Results: We conducted 39 interviews. Clinicians reported VLN to be easy to use with little disruption to the workflow. There were differences in patterns of use between experts and novice users with experts critically evaluating system recommendations and actively compensating for system limitations to achieve more reliable performance. Patients also viewed the tool positively. There were contextual variations in tool performance and use between different hospital sites and different use cases. Implementation challenges included integration with existing information systems, data protection, and perceived issues surrounding wider and sustained adoption, including procurement costs., Discussion: Tool performance was variable, affected by integration into workflows and divisions of labor and knowledge, as well as technical configuration and infrastructure., Conclusion: The socio-organizational factors affecting performance of diagnostic AI are under-researched and require attention and further research., (© The Author(s) 2023. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Background: There is growing evidence to suggest that EHRs may be associated with clinician stress and burnout, which could hamper their effective use and introduce risks to patient safety., Objective: This systematic review aimed to examine the association between EHR use and clinicians' stress and burnout in hospital settings, and to identify the contributing factors influencing this relationship., Methods: The search included peer-reviewed published studies between 2000 and 2023 in English in CINAHL, Ovid Medline, Embase, and PsychINFO. Studies that provided specific data regarding clinicians' stress and/or burnout related to EHRs in hospitals were included. A quality assessment of included studies was conducted., Results: Twenty-nine studies were included (25 cross-sectional surveys, one qualitative study, and three mixed methods), which focused on physicians (n = 18), nurses (n = 10) and mixed professions (n = 3). Usability issues and the amount of time spent on the EHR were the most significant predictors, but intensity of the working environment influenced high EHR-related workload and thereby also contributed to stress and burnout. The differences in clinicians' specialties influenced the levels of stress and burnout related to EHRs., Conclusions: This systematic review showed that EHR use was a perceived contributor to clinicians' stress and burnout in hospitals, primarily driven by poor usability and excessive time spent on EHRs. Addressing these issues requires tailored EHR systems, rigorous usability testing, support for the needs of different specialities, qualitative research on EHR stressors, and expanded research in Non-Western contexts., Competing Interests: The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2023.)

Background: Artificial Intelligence (AI) based clinical decision support systems to aid diagnosis are increasingly being developed and implemented but with limited understanding of how such systems integrate with existing clinical work and organizational practices. We explored the early experiences of stakeholders using an AI-based e-learning imaging software tool Veye Lung Nodules (VLN) aiding the detection, classification, and measurement of pulmonary nodules in computed tomography scans of the chest. We performed semi-structured interviews and observations across early adopter deployment sites with clinicians, strategic decision-makers, suppliers, patients with long-term chest conditions, and academics with expertise in the use of diagnostic AI in radiology settings. We coded the data using the Technology, People, Organizations and Macro-environmental factors framework (TPOM). We conducted 39 interviews. Clinicians reported VLN to be easy to use with little disruption to the workflow. There were differences in patterns of use between experts and novice users with experts critically evaluating system recommendations and actively compensating for system limitations to achieve more reliable performance. Patients also viewed the tool positively. There were contextual variations in tool performance and use between different hospital sites and different use cases. Implementation challenges included integration with existing information systems, data protection, and perceived issues surrounding wider and sustained adoption, including procurement costs. Tool performance was variable, affected by integration into workflows and divisions of labor and knowledge, as well as technical configuration and infrastructure. These under-researched factors require attention and further research.

Background: Investment in the implementation of hospital ePrescribing systems has been a priority in many economically-developed countries in order to modernise the delivery of healthcare. However, maximum gains in the safety, quality and efficiency of care are unlikely to be fully realised unless ePrescribing systems are further optimised in a local context. Typical barriers to optimal use are often encountered in relation to a lack of systemic capacity and preparedness to meet various levels of interoperability requirements, including at the data, systems and services levels. This lack of systemic interoperability may in turn limit the opportunities and benefits potentially arising from implementing novel digital heath systems., Methods: We undertook n = 54 qualitative interviews with key stakeholders at nine digitally advanced hospital sites across the UK, US, Norway and the Netherlands. We included hospitals featuring 'standalone, best of breed' systems, which were interfaced locally, and multi-component and integrated electronic health record enterprise systems. We analysed the data inductively, looking at strategies and constraints for ePrescribing interoperability within and beyond hospital systems., Results: Our thematic analysis identified 4 main drivers for increasing ePrescribing systems interoperability: (1) improving patient safety (2) improving integration & continuity of care (3) optimising care pathways and providing tailored decision support to meet local and contextualised care priorities and (4) to enable full patient care services interoperability in a variety of settings and contexts. These 4 interoperability dimensions were not always pursued equally at each implementation site, and these were often dependent on the specific national, policy, organisational or technical contexts of the ePrescribing implementations. Safety and efficiency objectives drove optimisation targeted at infrastructure and governance at all levels. Constraints to interoperability came from factors such as legacy systems, but barriers to interoperability of processes came from system capability, hospital policy and staff culture., Conclusions: Achieving interoperability is key in making ePrescribing systems both safe and useable. Data resources exist at macro, meso and micro levels, as do the governance interventions necessary to achieve system interoperability. Strategic objectives, most notably improved safety, often motivated hospitals to push for evolution across the entire data architecture of which they formed a part. However, hospitals negotiated this terrain with varying degrees of centralised coordination. Hospitals were heavily reliant on staff buy-in to ensure that systems interoperability was built upon to achieve effective data sharing and use. Positive outcomes were founded on a culture of agreement about the usefulness of access by stakeholders, including prescribers, policymakers, vendors and lab technicians, which was reflected in an alignment of governance goals with system design., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Competing Interests: Competing interests: None declared.

Despite the renewed interest in Artificial Intelligence-based clinical decision support systems (AI-CDS), there is still a lack of empirical evidence supporting their effectiveness. This underscores the need for rigorous and continuous evaluation and monitoring of processes and outcomes associated with the introduction of health information technology. We illustrate how the emergence of AI-CDS has helped to bring to the fore the critical importance of evaluation principles and action regarding all health information technology applications, as these hitherto have received limited attention. Key aspects include assessment of design, implementation and adoption contexts; ensuring systems support and optimise human performance (which in turn requires understanding clinical and system logics); and ensuring that design of systems prioritises ethics, equity, effectiveness, and outcomes. Going forward, information technology strategy, implementation and assessment need to actively incorporate these dimensions. International policy makers, regulators and strategic decision makers in implementing organisations therefore need to be cognisant of these aspects and incorporate them in decision-making and in prioritising investment. In particular, the emphasis needs to be on stronger and more evidence-based evaluation surrounding system limitations and risks as well as optimisation of outcomes, whilst ensuring learning and contextual review. Otherwise, there is a risk that applications will be sub-optimally embodied in health systems with unintended consequences and without yielding intended benefits., (Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.)

Adverse childhood experiences (ACEs) encompass various adversities, e.g., physical and/or emotional abuse. Understanding the effects of different ACE types on various health outcomes can guide targeted prevention and intervention. We estimated the association between three categories of ACEs in isolation and when they co-occurred. Specifically, the relationship between child maltreatment, witnessing violence, and household dysfunction and the risk of being involved in violence, engaging in health-harming behaviors, and experiencing mental ill-health. Data were from eight cross-sectional surveys conducted in England and Wales between 2012 and 2022. The sample included 21,716 adults aged 18-69 years; 56.6% were female. Exposure to child maltreatment and household dysfunction in isolation were strong predictors of variant outcomes, whereas witnessing violence was not. However, additive models showed that witnessing violence amplified the measured risk beyond expected levels for being a victim or perpetrator of violence. The multiplicative effect of all three ACE categories demonstrated the highest level of risk (RRs from 1.7 to 7.4). Given the increased risk associated with co-occurring ACEs, it is crucial to target individuals exposed to any ACE category to prevent their exposure to additional harm. Implementing universal interventions that safeguard children from physical, emotional, and sexual violence is likely to mitigate a range of subsequent issues, including future involvement in violence.

Background: Antimicrobial resistance, the ability of microorganisms to survive antimicrobial drugs, is a public health emergency. Although electronic prescribing (ePrescribing)-based interventions designed to reduce unnecessary antimicrobial usage exist, these often do not integrate effectively with existing workflows. As a result, ePrescribing-based interventions may have limited impact in addressing antimicrobial resistance., Objective: We sought to understand the existing ePrescribing-based antimicrobial stewardship (AMS) practices in an English hospital preceding the implementation of functionality designed to improve AMS., Methods: We conducted 18 semistructured interviews with medical prescribers and pharmacists with varying levels of seniority exploring current AMS practices and investigating potential areas for improvement. Participants were recruited with the help of local gatekeepers. Topic guides sought to explore both formal and informal practices surrounding AMS, and challenges and opportunities for ePrescribing-based intervention. We coded audio-recorded and transcribed data with the help of the Technology, People, Organizations, and Macroenvironmental factors framework, allowing emerging themes to be added inductively. We used NVivo 12 (QSR International) to facilitate coding., Results: Antimicrobial prescribing and review processes were characterized by competing priorities and uncertainty of prescribers and reviewers around prescribing decisions. For example, medical prescribers often had to face trade-offs between individual patient benefit and more diffuse population health benefits, and the rationale for prescribing decisions was not always clear. Prescribing involved a complex set of activities carried out by various health care practitioners who each only had a partial and temporary view of the whole process, and whose relationships were characterized by deeply engrained hierarchies that shaped interactions and varied across specialties. For example, newly qualified doctors and pharmacists were hesitant to change a consultant's prescribing decision when reviewing prescriptions. Multidisciplinary communication, collaboration, and coordination promoted good AMS practices by reducing uncertainty., Conclusions: Design of ePrescribing-based interventions to improve AMS needs to take into account the multitude of actors and organizational complexities involved in the prescribing and review processes. Interventions that help reduce prescriber or reviewer uncertainty and improve multidisciplinary collaboration surrounding initial antimicrobial prescribing and subsequent prescription review are most likely to be effective. Without such attention, interventions are unlikely to fulfill their goal of improving patient outcomes and combatting antimicrobial resistance., (©Kathrin Cresswell, Susan Hinder, Aziz Sheikh, Sarah Pontefract, Neil W Watson, David Price, Andrew Heed, Jamie Coleman, Holly Ennis, Jillian Beggs, Antony Chuter, Robin Williams. Originally published in JMIR Formative Research (https://formative.jmir.org), 06.06.2023.)

Background: Patient and public involvement and engagement (PPIE) can improve the relevance, quality, ethics and impact of research thus contributing to high quality research. Currently in the UK, people who get involved in research tend to be aged 61 years or above, White and female. Calls for greater diversity and inclusion in PPIE have become more urgent especially since the COVID-19 pandemic, so that research can better address health inequalities and be relevant for all sectors of society. Yet, there are currently no routine systems or requirements to collect or analyse the demographics of people who get involved in health research in the UK. The aim of this study was to develop to capture and analyse the characteristics of who does and doesn't take part in patient and public involvement and engagement (PPIE) activities., Methods: As part of its strategic focus on diversity and inclusion, Vocal developed a questionnaire to assess the demographics of people taking part in its PPIE activities. Vocal is a non-profit organisation which supports PPIE in health research across the region of Greater Manchester in England. The questionnaire was implemented across Vocal activities between December 2018 and March 2022. In that time. Vocal was working with approximately 935 public contributors. 329 responses were received: a return rate of 29.3%. Analysis of findings and comparison against local population demographic data, and available national data related to public contributors to health research, was performed., Results: Results show that it is feasible to assess the demographics of people who take part in PPIE activities, through a questionnaire system. Further, our emerging data indicate that Vocal are involving people from a wider range of ages and with a greater diversity of ethnic backgrounds in health research, as compared to available national data. Specifically, Vocal involves more people of Asian, African and Caribbean heritage, and includes a wider range of ages in its PPIE activities. More women than men are involved in Vocal's work., Conclusion: Our 'learn by doing' approach to assessing who does and doesn't take part in Vocal's PPIE activities has informed our practice and continues influence our strategic priorities for PPIE. Our system and learning reported here may be applicable and transferable to other similar settings in which PPIE is carried out. We attribute the greater diversity of our public contributors to our strategic priority and activities to promote more inclusive research since 2018., (© 2023. The Author(s).)

Objectives: Adverse childhood experiences (ACEs) show strong cumulative associations with ill-health across the life course. Harms can arise even in those exposed to a single ACE type but few studies examine such exposure. For individuals experiencing a single ACE type, we examine which ACEs are most strongly related to different health harms., Design: Secondary analysis of combined data from eight cross-sectional general population ACE surveys., Setting: Households in England and Wales., Participants: 20 556 residents aged 18-69 years., Measures: Ten self-reported outcomes were examined: smoking, cannabis use, binge drinking, obesity, sexually transmitted infection, teenage pregnancy, mental well-being, violence perpetration, violence victimisation and incarceration. Adjusted ORs and percentage changes in outcomes were calculated for each type of ACE exposure., Results: Significance and magnitude of associations between each ACE and outcome varied. Binge drinking was associated with childhood verbal abuse (VA), parental separation (PS) and household alcohol problem (AP), while obesity was linked to sexual abuse (SA) and household mental illness. SA also showed the biggest increase in cannabis use (25.5% vs 10.8%, no ACEs). Household AP was the ACE most strongly associated with violence and incarceration. PS was associated with teenage pregnancy (9.1% vs 3.7%, no ACEs) and 5 other outcomes. VA was associated with 7 of the 10 outcomes examined., Conclusion: Exposure to a single ACE increases risks of poorer outcomes across health-harming behaviours, sexual health, mental well-being and criminal domains. Toxic stress can arise from ACEs such as physical and SA but other more prevalent ACEs (eg, VA, PS) may also contribute substantively to poorer life course health., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

The European Commission's Innovative Medicines Initiative (IMI) has funded many projects focusing on neurodegenerative disorders (ND) that aimed to improve the diagnosis, prevention, treatment and understanding of NDs. To facilitate collaboration across this project portfolio, the IMI funded the "NEURONET" project between March 2019 and August 2022 with the aim of connecting these projects and promoting synergies, enhancing the visibility of their findings, understanding the impact of the IMI funding and identifying research gaps that warrant more/new funding. The IMI ND portfolio currently includes 20 projects consisting of 270 partner organizations across 25 countries. The NEURONET project conducted an impact analysis to assess the scientific and socio-economic impact of the IMI ND portfolio. This was to better understand the perceived areas of impact from those directly involved in the projects. The impact analysis was conducted in two stages: an initial stage developed the scope of the project, defined the impact indicators and measures to be used. A second stage designed and administered the survey amongst partners from European Federation of Pharmaceutical Industries and Associations (EFPIA) organizations and other partners (hereafter, referred to as "non-EFPIA" organizations). Responses were analyzed according to areas of impact: organizational, economic, capacity building, collaborations and networking, individual, scientific, policy, patient, societal and public health impact. Involvement in the IMI ND projects led to organizational impact, and increased networking, collaboration and partnerships. The key perceived disadvantage to project participation was the administrative burden. These results were true for both EFPIA and non-EFPIA respondents. The impact for individual, policy, patients and public health was less clear with people reporting both high and low impact. Overall, there was broad alignment between EFPIA and non-EFPIA participants' responses apart from for awareness of project assets, as part of scientific impact, which appeared to be slightly higher among non-EFPIA respondents. These results identified clear areas of impact and those that require improvement. Areas to focus on include promoting asset awareness, establishing the impact of the IMI ND projects on research and development, ensuring meaningful patient involvement in these public-private partnership projects and reducing the administrative burden associated with participation in them., Competing Interests: CH, FS, KC, and DD were employed by the National Institute for Health and Care Excellence. CD and LK were employed by SYNAPSE Research Management Partners. AB was employed by Alzheimer Europe. LP was employed by Sanofi. LS was employed by Janssen Pharmaceuticals NV., (Copyright © 2023 Hawksworth, Salih, Cresswell, Steukers, Diaz, Killin, Pradier, Bradshaw and Dawoud.)

Background: Antimicrobial resistance is a leading global public health threat, with inappropriate use of antimicrobials in healthcare contributing to its development. Given this urgent need, we developed a complex ePrescribing-based Anti-Microbial Stewardship intervention (ePAMS+)., Methods: ePAMS+ includes educational and organisational behavioural elements, plus guideline-based clinical decision support to aid optimal antimicrobial use in hospital inpatients. ePAMS+ particularly focuses on prompt initiation of antimicrobials, followed by early review once test results are available to facilitate informed decision-making on stopping or switching where appropriate. A mixed-methods feasibility trial of ePAMS+ will take place in two NHS acute hospital care organisations. Qualitative staff interviews and observation of practice will respectively gather staff views on the technical component of ePAMS+ and information on their use of ePAMS+ in routine work. Focus groups will elicit staff and patient views on ePAMS+; one-to-one interviews will discuss antimicrobial stewardship with staff and will record patient experiences of receiving antibiotics and their thoughts on inappropriate prescribing. Qualitative data will be analysed thematically. Fidelity Index development will enable enactment of ePAMS+ to be measured objectively in a subsequent trial assessing the effectiveness of ePAMS+. Quantitative data collection will determine the feasibility of extracting data and deriving key summaries of antimicrobial prescribing; we will quantify variability in the primary outcome, number of antibiotic defined daily doses, to inform the future larger-scale trial design., Discussion: This trial is essential to determine the feasibility of implementing the ePAMS+ intervention and measuring relevant outcomes, prior to evaluating its clinical and cost-effectiveness in a full scale hybrid cluster-randomised stepped-wedge clinical trial. Findings will be shared with study sites and with qualitative research participants and will be published in peer-reviewed journals and presented at academic conferences., Trial Registration: The qualitative and Fidelity Index research were approved by the Health and Research Authority and the North of Scotland Research Ethics Service (ref: 19/NS/0174). The feasibility trial and quantitative analysis (protocol v1.0, 15 December 2021) were approved by the London South East Research Ethics Committee (ref: 22/LO/0204) and registered with ISRCTN ( ISRCTN 13429325 ) on 24 March 2022., (© 2022. The Author(s).)

Integrating health and social care delivery with the help of digital technologies is a grand challenge. We argue that previous attempts have largely failed to achieve their objectives because implementers and decision makers disregard the complex socio-organizational dimensions of change associated with initiatives. These include structural and organizational complexity inhibiting the development of shared care pathways; professional jurisdictions, interests, and expertise; and existing data and governance structures. We provide an overview of those dimensions that can inform strategic decisions going forward, thereby contributing to the chances of success of shared care initiatives., (©Kathrin Cresswell, Stuart Anderson, Hajar Mozaffar, Andrey Elizondo, Marcia Geiger, Robin Williams. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 26.01.2023.)

Unintentional injury is a significant cause of disease burden and death. There are known inequalities in the experience of unintentional injuries; however, to date only a limited body of re-search has explored the relationship between exposure to adverse childhood experiences (ACEs) and unintentional injury. Using a cross-sectional sample of the adult general public ( n = 4783) in Wales (national) and England (Bolton Local Authority), we identify relationships between ACE exposure and experience of car crashes and burns requiring medical attention across the life course. Individuals who had experienced 4+ ACEs were at significantly increased odds of having ever had each outcome measured. Furthermore, compared to those with no ACEs, those with 4+ were around two times more likely to report having had multiple (i.e., 2+) car crashes and over four times more likely to report having had burns multiple times. Findings expand the evidence base for the association between ACEs and negative health consequences and emphasise the need for effective interventions to prevent ACEs and their impact on life course health and well-being. Such knowledge can also be used to develop a multifaceted approach to injury prevention.

The Digital Health Leadership Programme is commissioned by Health Education England and part of the wider NHS Digital Academy. The Programme is a consortium of Imperial College London's Institute of Global Health Innovation, The University of Edinburgh's Usher Institute and Harvard Medical School. In 2021, Health Data Research UK joined Imperial and Edinburgh to deliver phase 2. The aim is to develop a new generation of digital health leaders to drive transformation of the NHS through digitisation. Participants gain the skills and knowledge to create change so that patient care and organisational operations can benefit from the many improvements and innovations modern technology has to offer.

Objectives: Patient portals are increasingly implemented to improve patient involvement and engagement. We here seek to provide an overview of ways to mitigate existing concerns that these technologies increase inequity and bias and do not reach those who could benefit most from them., Methods: Based on the current literature, we review the limitations of existing evaluations of patient portals in relation to addressing health equity, literacy and bias; outline challenges evaluators face when conducting such evaluations; and suggest methodological approaches that may address existing shortcomings., Results: Various stakeholder needs should be addressed before deploying patient portals, involving vulnerable groups in user-centred design, and studying unanticipated consequences and impacts of information systems in use over time., Conclusions: Formative approaches to evaluation can help to address existing shortcomings and facilitate the development and implementation of patient portals in an equitable way thereby promoting the creation of resilient health systems., Competing Interests: Disclosure The authors report no conflicts of interest in this work., (IMIA and Thieme. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).)

Objectives: To identify interventions implemented in hospital electronic prescribing systems and the outcome measures used to monitor their impact., Methods: We systematically searched CINAHL, EMBASE, Google Scholar and Medline using keywords in three strands: (i) population: hospital inpatient or emergency department; (ii) intervention: electronic prescribing functionality; and (iii) outcome: antimicrobial stewardship. The interventions were grouped into six themes: alerts, order sets, restriction of access, mandated documentation, embedded guidelines and automatic prescription stop. The outcome measures were organized into those that measure the quality or quantity of prescribing or clinical decision support (CDS) activity. The impact of each intervention reported was grouped into a positive, negative or no change., Results: A total of 28 studies were eligible for inclusion. There were 28 different interventions grouped into the six themes. Alerts visible to the practitioner in the electronic health record (EHR) were most frequently implemented ( n  = 11/28). Twenty different outcome measures were identified, divided into quality ( n  = 13/20) and quantity outcomes ( n  = 4/20) and CDS activity ( n  = 3/20). One-third of outcomes reported across the 28 studies showed positive change (34.4%, n  = 42/122) and 61.4% ( n  = 75/122) showed no change., Conclusions: The most frequently implemented interventions were alerts, the majority of which were to influence behaviour or decision-making of the practitioner within the EHR. Quality outcomes were most frequently selected by researchers. The review supports previous research that larger well-designed randomized studies are needed to investigate the impact of interventions on AMS and outcome measures to be standardized., (© The Author(s) 2022. Published by Oxford University Press on behalf of British Society for Antimicrobial Chemotherapy.)

Background: The Global Digital Exemplar (GDE) Programme is a national initiative to promote digitally enabled transformation in English provider organizations. The Programme applied benefits realization management techniques to promote and demonstrate transformative outcomes. This work was part of an independent national evaluation of the GDE Programme., Aims: We explored how benefits realization management was approached and conceptualized in the GDE Programme., Methods: We conducted a series of 36 longitudinal case studies of provider organizations participating in the GDE Programme, 12 of which were in depth. Data collection included a combination of 628 interviews (with implementation staff in provider organizations, national programme management staff, and suppliers), 499 documents (of national and local implementation plans and lessons learned), and 190 nonparticipant observations (of national and local programme management meetings to develop insights into the broader context of benefits realization activities, tensions arising, and how these were negotiated). Data were coded drawing on a sociotechnical framework developed in related work and thematically analyzed, initially within and then across cases, with the help of NVivo 11 software., Results: Most stakeholders broadly agreed with the rationale of benefits realization in the GDE Programme to show due diligence that public money was appropriately spent, and to develop an evidence base supporting the value of digitally enabled transformation. Differing national and local reporting purposes, however, created tensions. Central requirements, for progress reporting and tracking high-level benefits, had limited perceived local value and were seen to impose an unnecessary burden on provider organizations. This was accentuated by the lack of harmonization of reporting requirements to different stakeholders (which differed in content and timing). There were tensions between the desire for early evidence of outcomes and the slow processes of infrastructural change (which created problems of attribution of benefits to causes as benefits emerged gradually and over long timeframes), and also between reporting immediately visible local changes and showing how these flowed through to high level organization wide benefits (eg, in terms of health outcomes or cost savings/return on investment). The attempt to fulfill these diverging agendas and informational needs within a single reporting tool had limited success. These difficulties were mitigated by efforts to simplify reporting requirements and to support targeted collection of key national outcome measures. Although progress was hampered by an initial lack of benefits realization expertise in provider organizations, some providers subsequently retained these skills for their own change management purposes., Conclusions: There is a need to recognize the limitations and cost of benefits realization management practices in the context of healthcare digitalization where benefits may materialize over long timeframes and in unanticipated ways. Although diverse stakeholder information needs may create tensions, prior agreement about rationales for collecting information and a targeted approach to tracking local and high-level benefits may enhance local relevance, reduce perceived reporting burdens, and improve acceptance/effectiveness. A single integrated reporting mechanism is unlikely to fulfill both national and local requirements., (© The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Background: The use of cloud computing (involving storage and processing of data on the internet) in health care has increasingly been highlighted as having great potential in facilitating data-driven innovations. Although some provider organizations are reaping the benefits of using cloud providers to store and process their data, others are lagging behind., Objective: We aim to explore the existing challenges and barriers to the use of cloud computing in health care settings and investigate how perceived risks can be addressed., Methods: We conducted a qualitative case study of cloud computing in health care settings, interviewing a range of individuals with perspectives on supply, implementation, adoption, and integration of cloud technology. Data were collected through a series of in-depth semistructured interviews exploring current applications, implementation approaches, challenges encountered, and visions for the future. The interviews were transcribed and thematically analyzed using NVivo 12 (QSR International). We coded the data based on a sociotechnical coding framework developed in related work., Results: We interviewed 23 individuals between September 2020 and November 2020, including professionals working across major cloud providers, health care provider organizations, innovators, small and medium-sized software vendors, and academic institutions. The participants were united by a common vision of a cloud-enabled ecosystem of applications and by drivers surrounding data-driven innovation. The identified barriers to progress included the cost of data migration and skill gaps to implement cloud technologies within provider organizations, the cultural shift required to move to externally hosted services, a lack of user pull as many benefits were not visible to those providing frontline care, and a lack of interoperability standards and central regulations., Conclusions: Implementations need to be viewed as a digitally enabled transformation of services, driven by skill development, organizational change management, and user engagement, to facilitate the implementation and exploitation of cloud-based infrastructures and to maximize returns on investment., (©Kathrin Cresswell, Andrés Domínguez Hernández, Robin Williams, Aziz Sheikh. Originally published in JMIR Human Factors (https://humanfactors.jmir.org), 06.01.2022.)

Background: In recent decades, there has been considerable international attention aimed at improving the safety of hospital care, and more recently, this attention has broadened to include primary medical care. In contrast, the safety profile of primary care dentistry remains poorly characterized., Objectives: We aimed to describe the types of primary care dental patient safety incidents reported within a national incident reporting database and understand their contributory factors and consequences., Methods: We undertook a cross-sectional mixed-methods study, which involved analysis of a weighted randomized sample of the most severe incident reports from primary care dentistry submitted to England and Wales' National Reporting and Learning System. Drawing on a conceptual literature-derived model of patient safety threats that we previously developed, we developed coding frameworks to describe and conduct thematic analysis of free text incident reports and determine the relationship between incident types, contributory factors, and outcomes., Results: Of 2000 reports sampled, 1456 were eligible for analysis. Sixty types of incidents were identified and organized across preoperative (40.3%, n = 587), intraoperative (56.1%, n = 817), and postoperative (3.6%, n = 52) stages. The main sources of unsafe care were delays in treatment (344/1456, 23.6%), procedural errors (excluding wrong-tooth extraction) (227/1456; 15.6%), medication-related adverse incidents (161/1456, 11.1%), equipment failure (90/1456, 6.2%) and x-ray related errors (87/1456, 6.0%). Of all incidents that resulted in a harmful outcome (n = 77, 5.3%), more than half were due to wrong tooth extractions (37/77, 48.1%) mainly resulting from distraction of the dentist. As a result of this type of incident, 34 of the 37 patients (91.9%) examined required further unnecessary procedures., Conclusions: Flaws in administrative processes need improvement because they are the main cause for patients experiencing delays in receiving treatment. Checklists and standardization of clinical procedures have the potential to reduce procedural errors and avoid overuse of services. Wrong-tooth extractions should be addressed through focused research initiatives and encouraging policy development to mandate learning from serious dental errors like never events., Competing Interests: The authors disclose no conflict of interest., (Copyright © 2018 Wolters Kluwer Health, Inc. All rights reserved.)

Background: There is currently a strong drive internationally towards creating digitally advanced healthcare systems through coordinated efforts at a national level. The English Global Digital Exemplar (GDE) programme is a large-scale national health information technology change programme aiming to promote digitally-enabled transformation in secondary healthcare provider organisations by supporting relatively digitally mature provider organisations to become international centres of excellence., Aim: To qualitatively evaluate the impact of the GDE programme in promoting digital transformation in provider organisations that took part in the programme., Methods: We conducted a series of in-depth case studies in 12 purposively selected provider organisations and a further 24 wider case studies of the remaining organisations participating in the GDE programme. Data collected included 628 interviews, non-participant observations of 190 meetings and workshops and analysis of 9 documents. We used thematic analysis aided by NVivo software and drew on sociotechnical theory to analyse the data., Results: We found the GDE programme accelerated digital transformation within participating provider organisations. This acceleration was triggered by: (1) dedicated funding and the associated requirement for matched internal funding, which in turn helped to prioritise digital transformation locally; (2) governance requirements put in place by the programme that helped strengthen existing local governance and project management structures and supported the emergence of a cadre of clinical health informatics leaders locally; and (3) reputational benefits associated with being recognised as a centre of digital excellence, which facilitated organisational buy-in for digital transformation and increased negotiating power with vendors., Conclusion: The GDE programme has been successful in accelerating digital transformation in participating provider organisations. Large-scale digital transformation programmes in healthcare can stimulate local progress through protected funding, putting in place governance structures and leveraging reputational benefits for participating provider organisations, around a coherent vision of transformation., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Novel machine learning methods open the door to advances in rheumatology through application to complex, high-dimensional data, otherwise difficult to analyse. Results from such efforts could provide better classification of disease, decision support for therapy selection, and automated interpretation of clinical images. Nevertheless, such data-driven approaches could potentially model noise, or miss true clinical phenomena. One proposed solution to ensure clinically meaningful machine learning models is to involve primary stakeholders in their development and interpretation. Including patient and health care professionals' input and priorities, in combination with statistical fit measures, allows for any resulting models to be well fit, meaningful, and fit for practice in the wider rheumatological community. Here we describe outputs from workshops that involved healthcare professionals, and young people from the Your Rheum Young Person's Advisory Group, in the development of complex machine learning models. These were developed to better describe trajectory of early juvenile idiopathic arthritis disease, as part of the CLUSTER consortium. We further provide key instructions for reproducibility of this process.Involving people living with, and managing, a disease investigated using machine learning techniques, is feasible, impactful and empowering for all those involved., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ.)

Objective: To explore synergistic effects related to skin regeneration, peptides with distinct biological mechanisms of action were evaluated in combination with different skin cell lines in the presence or absence of niacinamide (Nam). Furthermore, the synergistic responses of peptide combinations on global gene expression were compared with the changes that occur with fractional laser resurfacing treatment, a gold standard approach for skin rejuvenation, to further define optimal peptide combinations., Methods: Microarray profiling was used to characterize the biological responses of peptide combinations (+/- Nam) relative to the individual components in epidermal keratinocyte and dermal fibroblast cell lines. Cellular functional assays were utilized to confirm the synergistic effects of peptide combinations. Bioinformatics approaches were used to link the synergistic effects of peptide combinations on gene expression to the transcriptomics of the skin rejuvenation response from fractional laser treatment., Results: Microarray analysis of skin cells treated with peptide combinations revealed synergistic changes in gene expression compared with individual peptide controls. Bioinformatic analysis of synergy genes in keratinocytes revealed the activation of NRF2-mediated oxidative stress responses by a combination of Ac-PPYL, Pal-KTTKS and Nam. Additional analysis revealed direct downstream transcriptional targets of NRF2/ARE exhibiting synergistic regulation by this combination of materials, which was corroborated by a cellular reporter assay. NRF2-mediated oxidative stress response pathways were also found to be activated in the transcriptomics of the early skin rejuvenation response to fractional laser treatment, suggesting the importance of this biology in the early stages of tissue repair. Additionally, the second combination of peptides (pal-KT and Ac-PPYL) was found to synergistically restore cellular ATP levels that had been depleted due to the presence of ROS, indicating an additional mechanism, whereby peptide synergies may accelerate skin repair., Conclusion: Through combinatorial synergy studies, we have identified additional in vitro skin repair mechanisms beyond the previously described functions of individual peptides and correlated these to the transcriptomics of the skin rejuvenation response of fractional laser treatment. These findings suggest that specific peptides can act together, via complementary and synergistic mechanisms, to holistically enhance the regenerative capacity of in vitro skin cells., (© 2021 The Authors. International Journal of Cosmetic Science published by John Wiley & Sons Ltd on behalf of Society of Cosmetic Scientists and Societe Francaise de Cosmetologie.)

Background: The English Global Digital Exemplar (GDE) program is one of the first concerted efforts to create a digital health learning ecosystem across a national health service., Objective: This study aims to explore mechanisms that support or inhibit the exchange of interorganizational digital transformation knowledge., Methods: We conducted a formative qualitative evaluation of the GDE program. We used semistructured interviews with clinical, technical, and managerial staff; national program managers and network leaders; nonparticipant observations of knowledge transfer activities through attending meetings, workshops, and conferences; and documentary analysis of policy documents. The data were thematically analyzed by drawing on a theory-informed sociotechnical coding framework. We used a mixture of deductive and inductive methods, supported by NVivo software, to facilitate coding., Results: We conducted 341 one-on-one and 116 group interviews, observed 86 meetings, and analyzed 245 documents from 36 participating provider organizations. We also conducted 51 high-level interviews with policy makers and vendors; performed 77 observations of national meetings, workshops, and conferences; and analyzed 80 national documents. Formal processes put in place by the GDE program to initiate and reinforce knowledge transfer and learning have accelerated the growth of informal knowledge networking and helped establish the foundations of a learning ecosystem. However, formal networks were most effective when supported by informal networking. The benefits of networking were enhanced (and costs reduced) by geographical proximity, shared culture and context, common technological functionality, regional and strategic alignments, and professional agendas., Conclusions: Knowledge exchange is most effective when sustained through informal networking driven by the mutual benefits of sharing knowledge and convergence between group members in their organizational and technological setting and goals. Policy interventions need to enhance incentives and reduce barriers to sharing across the ecosystem, be flexible in tailoring formal interventions to emerging needs, and promote informal knowledge sharing., (©Kathrin Cresswell, Aziz Sheikh, Bryony Dean Franklin, Marta Krasuska, Hung The Nguyen, Susan Hinder, Wendy Lane, Hajar Mozaffar, Kathy Mason, Sally Eason, Henry Potts, Robin Williams. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 19.08.2021.)

Background: The Global Digital Exemplar (GDE) Programme was designed to promote the digitisation of hospital services in England. Selected provider organisations that were reasonably digitally-mature were funded with the expectation that they would achieve internationally recognised levels of excellence and act as exemplars ('GDE sites') and share their learning with somewhat less digitally-mature Fast Follower (FF) sites., Aims: This paper explores how partnerships between GDE and FF sites have promoted knowledge sharing and learning between organisations., Methods: We conducted an independent qualitative longitudinal evaluation of the GDE Programme, collecting data across 36 provider organisations (including acute, mental health and speciality), 12 of which we studied as in-depth ethnographic case studies. We used a combination of semi-structured interviews with programme leads, vendors and national policy leads, non-participant observations of meetings and workshops, and analysed national and local documents. This allowed us to explore both how inter-organisational learning and knowledge sharing was planned, and how it played out in practice. Thematic qualitative analysis, combining findings from diverse data sources, was facilitated by NVivo 11 and drew on sociotechnical systems theory., Results: Formally established GDE and FF partnerships were perceived to enhance learning and accelerate adoption of technologies in most pairings. They were seen to be most successful where they had encouraged, and were supported by, informal knowledge networking, driven by the mutual benefits of information sharing. Informal networking was enhanced where the benefits were maximised (for example where paired sites had implemented the same technological system) and networking costs minimised (for example by geographical proximity, prior links and institutional alignment). Although the intervention anticipated uni-directional learning between exemplar sites and 'followers', in most cases we observed a two-way flow of information, with GDEs also learning from FFs, through informal networking which also extended to other health service providers outside the Programme. The efforts of the GDE Programme to establish a learning ecosystem has enhanced the profile of shared learning within the NHS., Conclusions: Inter-organisational partnerships have produced significant gains for both follower (FF) and exemplar (GDE) sites. Formal linkages were most effective where they had facilitated, and were supported by, informal networking. Informal networking was driven by the mutual benefits of information sharing and was optimised where sites were well aligned in terms of technology, geography and culture. Misalignments that created barriers to networking between organisations in a few cases were attributed to inappropriate choice of partners. Policy makers seeking to promote learning through centrally directed mechanisms need to create a framework that enables networking and informal knowledge transfer, allowing local organisations to develop bottom-up collaboration and exchanges, where they are productive, in an organic manner., Competing Interests: All authors are investigators on the evaluation of the Global Digital Exemplars Programme (http://www.ed.ac.uk/usher) AS was a member of the Working Group that produced “Making IT Work” and was an assessor in selecting GDE sites. BDF supervises a PhD partly financed by Cerner, unrelated to this paper. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Background: There have been efforts to understand the epidemiology of iatrogenic harm in hospitals and primary care and to improve the safety of care provision. There has in contrast been very limited progress in relation to the safety of ambulatory dental care., Objectives: To provide a comprehensive overview of the range and frequencies of existing evidence on patient safety incidents and adverse events in ambulatory dentistry., Methods: We searched MEDLINE and EMBASE for articles reporting events that could have or did result in unnecessary harm in ambulatory dental care. We extracted and synthesized data on the types and frequencies of patient safety incidents and adverse events., Results: Forty articles were included. We found that the frequencies varied very widely between studies; this reflected differences in definitions, populations studied, and sampling strategies. The main 5 PSIs we identified were errors in diagnosis and examination, treatment planning, communication, procedural errors, and the accidental ingestion or inhalation of foreign objects. However, little attention was paid to wider organizational issues., Conclusions: Patient safety research in dentistry is immature because current evidence cannot provide reliable estimates on the frequency of patient safety incidents in ambulatory dental care or the associated disease burden. Well-designed epidemiological investigations are needed that also investigate contributory factors., Competing Interests: The authors disclose no conflict of interest., (Copyright © 2016 Wolters Kluwer Health, Inc. All rights reserved.)

Objectives: To highlight the role of technology assessment in the management of the COVID-19 pandemic., Method: An overview of existing research and evaluation approaches along with expert perspectives drawn from the International Medical Informatics Association (IMIA) Working Group on Technology Assessment and Quality Development in Health Informatics and the European Federation for Medical Informatics (EFMI) Working Group for Assessment of Health Information Systems., Results: Evaluation of digital health technologies for COVID-19 should be based on their technical maturity as well as the scale of implementation. For mature technologies like telehealth whose efficacy has been previously demonstrated, pragmatic, rapid evaluation using the complex systems paradigm which accounts for multiple sociotechnical factors, might be more suitable to examine their effectiveness and emerging safety concerns in new settings. New technologies, particularly those intended for use on a large scale such as digital contract tracing, will require assessment of their usability as well as performance prior to deployment, after which evaluation should shift to using a complex systems paradigm to examine the value of information provided. The success of a digital health technology is dependent on the value of information it provides relative to the sociotechnical context of the setting where it is implemented., Conclusion: Commitment to evaluation using the evidence-based medicine and complex systems paradigms will be critical to ensuring safe and effective use of digital health technologies for COVID-19 and future pandemics. There is an inherent tension between evaluation and the imperative to urgently deploy solutions that needs to be negotiated., Competing Interests: Disclosure The authors report no conflicts of interest in this work., (IMIA and Thieme. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).)

Objective: The Global Digital Exemplar (GDE) Program is a national attempt to accelerate digital maturity in healthcare providers through promoting knowledge transfer across the English National Health Service (NHS). "Blueprints"-documents capturing implementation experience-were intended to facilitate this knowledge transfer. Here we explore how Blueprints have been conceptualized, produced, and used to promote interorganizational knowledge transfer across the NHS., Materials and Methods: We undertook an independent national qualitative evaluation of the GDE Program. This involved collecting data using semistructured interviews with implementation staff and clinical leaders in provider organizations, nonparticipant observation of meetings, and key documents. We also attended a range of national meetings and conferences, interviewed national program managers, and analyzed a range of policy documents. Our analysis drew on sociotechnical principles, combining deductive and inductive methods., Results: Data comprised 508 interviews, 163 observed meetings, and analysis of 325 documents. We found little evidence of Blueprints being adopted in the manner originally conceived by national program managers. However, they proved effective in different ways to those planned. As well as providing a helpful initial guide to a topic, we found that Blueprints served as a method of identifying relevant expertise that paved the way for subsequent discussions and richer knowledge transfers amongst provider organizations. The primary value of Blueprinting, therefore, seemed to be its role as a networking tool. Members of different organizations came together in developing, applying, and sustaining Blueprints through bilateral conversations-in some circumstances also fostering informal communities of practice., Conclusions: Blueprints may be effective in facilitating knowledge transfer among healthcare organizations, but need to be accompanied by other evolving methods, such as site visits and other networking activities, to iteratively transfer knowledge and experience., (© The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Background: The emergence of SARS-CoV-2 in late 2019 and its subsequent spread worldwide continues to be a global health crisis. Many governments consider contact tracing of citizens through apps installed on mobile phones as a key mechanism to contain the spread of SARS-CoV-2., Objective: In this study, we sought to explore the suitability of artificial intelligence (AI)-enabled social media analyses using Facebook and Twitter to understand public perceptions of COVID-19 contact tracing apps in the United Kingdom., Methods: We extracted and analyzed over 10,000 relevant social media posts across an 8-month period, from March 1 to October 31, 2020. We used an initial filter with COVID-19-related keywords, which were predefined as part of an open Twitter-based COVID-19 dataset. We then applied a second filter using contract tracing app-related keywords and a geographical filter. We developed and utilized a hybrid, rule-based ensemble model, combining state-of-the-art lexicon rule-based and deep learning-based approaches., Results: Overall, we observed 76% positive and 12% negative sentiments, with the majority of negative sentiments reported in the North of England. These sentiments varied over time, likely influenced by ongoing public debates around implementing app-based contact tracing by using a centralized model where data would be shared with the health service, compared with decentralized contact-tracing technology., Conclusions: Variations in sentiments corroborate with ongoing debates surrounding the information governance of health-related information. AI-enabled social media analysis of public attitudes in health care can help facilitate the implementation of effective public health campaigns., (©Kathrin Cresswell, Ahsen Tahir, Zakariya Sheikh, Zain Hussain, Andrés Domínguez Hernández, Ewen Harrison, Robin Williams, Aziz Sheikh, Amir Hussain. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 17.05.2021.)

Torsade de points (TdP), a life-threatening arrhythmia that can increase the risk of sudden cardiac death, is associated with drug-induced QT-interval prolongation on the electrocardiogram (ECG). While many modern ECG machines provide automated measurements of the QT-interval, these automated QT values are usually correct only for a noise-free normal sinus rhythm, in which the T-wave morphology is well defined. As QT-prolonging drugs often affect the morphology of the T-wave, automated QT measurements taken under these circumstances are easily invalidated. An additional challenge is that the QT-value at risk of TdP varies with heart rate, with the slower the heart rate, the greater the risk of TdP. This paper presents an explainable algorithm that uses an understanding of human visual perception and expert ECG interpretation to automate the detection of QT-prolongation at risk of TdP regardless of heart rate and T-wave morphology. It was tested on a large number of ECGs (n=5050) with variable QT-intervals at varying heart rates, acquired from a clinical trial that assessed the effect of four known QT-prolonging drugs versus placebo on healthy subjects. The algorithm yielded a balanced accuracy of 0.97, sensitivity of 0.94, specificity of 0.99, F1-score of 0.88, ROC (AUC) of 0.98, precision-recall (AUC) of 0.88, and Matthews correlation coefficient (MCC) of 0.88. The results indicate that a prolonged ventricular repolarisation area can be a significant risk predictor of TdP, and detection of this is potentially easier and more reliable to automate than measuring the QT-interval distance directly. The proposed algorithm can be visualised using pseudo-colour on the ECG trace, thus intuitively 'explaining' how its decision was made, which results of a focus group show may help people to self-monitor QT-prolongation, as well as ensuring clinicians can validate its results., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Creating a learning health system could help reduce variations in quality of care. Success is dependent on timely access to health data. To explore the barriers and facilitators to timely access to patients' data, we conducted in-depth semi-structured interviews with 37 purposively sampled participants from government, the NHS and academia across Scotland. Interviews were analysed using the framework approach. Participants were of the view that Scotland could play a leading role in the exploitation of routine data to drive forward service improvements, but highlighted major impediments: (i) persistence of paper-based records and a variety of information systems; (ii) the need for a proportionate approach to managing information governance; and (iii) the need for support structures to facilitate accrual, processing, linking, analysis and timely use and reuse of data for patient benefit. There is a pressing need to digitise and integrate existing health information infrastructures, guided by a nationwide proportionate information governance approach and the need to enhance technological and human capabilities to support these efforts.

Background: Long noncoding RNA (lncRNA) have been implicated in the etiology of alcohol use. Since lncRNA provide another layer of complexity to the transcriptome, assessing their expression in the brain is the first critical step toward understanding lncRNA functions in alcohol use and addiction. Thus, we sought to profile lncRNA expression in the nucleus accumbens (NAc) in a large postmortem alcohol brain sample., Methods: LncRNA and protein-coding gene (PCG) expressions in the NAc from 41 subjects with alcohol dependence (AD) and 41 controls were assessed via a regression model. Weighted gene coexpression network analysis was used to identify lncRNA and PCG networks (i.e., modules) significantly correlated with AD. Within the significant modules, key network genes (i.e., hubs) were also identified. The lncRNA and PCG hubs were correlated via Pearson correlations to elucidate the potential biological functions of lncRNA. The lncRNA and PCG hubs were further integrated with GWAS data to identify expression quantitative trait loci (eQTL)., Results: At Bonferroni adj. p-value ≤ 0.05, we identified 19 lncRNA and 5 PCG significant modules, which were enriched for neuronal and immune-related processes. In these modules, we further identified 86 and 315 PCG and lncRNA hubs, respectively. At false discovery rate (FDR) of 10%, the correlation analyses between the lncRNA and PCG hubs revealed 3,125 positive and 1,860 negative correlations. Integration of hubs with genotype data identified 243 eQTLs affecting the expression of 39 and 204 PCG and lncRNA hubs, respectively., Conclusions: Our study identified lncRNA and gene networks significantly associated with AD in the NAc, coordinated lncRNA and mRNA coexpression changes, highlighting potentially regulatory functions for the lncRNA, and our genetic (cis-eQTL) analysis provides novel insights into the etiological mechanisms of AD., (© 2020 The Authors. Alcoholism: Clinical & Experimental Research published by Wiley Periodicals LLC on behalf of Research Society on Alcoholism.)

Competing Interests: Competing interests: The authors completed the ICMJE Unified Competing Interest form (available upon request from the corresponding author), and declare no conflicts of interest.

Background: Wearable sensors connected via networked devices have the potential to generate data that may help to automate processes of care, engage patients, and increase health care efficiency. The evidence of effectiveness of such technologies is, however, nascent and little is known about unintended consequences., Objective: Our objective was to explore the opportunities and challenges surrounding the use of data from wearable sensor devices in health care., Methods: We conducted a qualitative, theoretically informed, interview-based study to purposefully sample international experts in health care, technology, business, innovation, and social sciences, drawing on sociotechnical systems theory. We used in-depth interviews to capture perspectives on development, design, and use of data from wearable sensor devices in health care, and employed thematic analysis of interview transcripts with NVivo to facilitate coding., Results: We interviewed 16 experts. Although the use of data from wearable sensor devices in health and care has significant potential in improving patient engagement, there are a number of issues that stakeholders need to negotiate to realize these benefits. These issues include the current gap between data created and meaningful interpretation in health and care contexts, integration of data into health care professional decision making, negotiation of blurring lines between consumer and medical care, and pervasive monitoring of health across previously disconnected contexts., Conclusions: Stakeholders need to actively negotiate existing challenges to realize the integration of data from wearable sensor devices into electronic health records. Viewing wearables as active parts of a connected digital health and care infrastructure, in which various business, personal, professional, and health system interests align, may help to achieve this., (©Ijeoma Azodo, Robin Williams, Aziz Sheikh, Kathrin Cresswell. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 22.10.2020.)

Introduction: Many countries are launching large-scale, digitally enabled change programmes as part of efforts to improve the quality, safety and efficiency of care. We have been commissioned to conduct an independent evaluation of a major national change programme, the Global Digital Exemplar (GDE) Programme, which aims to develop exemplary digital health solutions and encourage their wider adoption by creating a learning ecosystem across English National Health Service (NHS) provider organisations., Methods and Analysis: This theoretically informed, qualitative, longitudinal formative evaluation comprises five inter-related work packages. We will conduct a combination of 12 in-depth and 24 broader qualitative case studies in GDE sites exploring digital transformation, local learning and mechanisms of spread of knowledge within the Programme and across the wider NHS. Data will be collected through a combination of semistructured interviews with managers, implementation staff (clinical and non-clinical), vendors and policymakers, plus non-participant observations of meetings, site visits, workshops and documentary analysis of strategic local and national plans. Data will be analysed through inductive and deductive methods, beginning with in-depth case study sites and testing the findings against data from the wider sample and national stakeholders., Ethics and Dissemination: This work is commissioned as part of a national change programme and is therefore a service evaluation. We have ethical approval from the University of Edinburgh. Results will be disseminated at six monthly intervals to national policymakers, and made available via our publicly accessible website. We will also identify lessons for the management and evaluation of large-scale evolving digital health change programmes that are of international relevance., Competing Interests: Competing interests: All authors are investigators on the evaluation of the GDE Programme (https://www.ed.ac.uk/usher/digital-exemplars). AS was a member of the Working Group that produced Making IT Work, and was an assessor in selecting GDE sites. BDF supervises a PhD student partly funded by Cerner, unrelated to this paper., (© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY. Published by BMJ.)