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BackgroundCOVID-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. ObjectiveThis 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. MethodsWe 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. ResultsWe 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. ConclusionsThere 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.

BackgroundProjects to implement health care and social care innovations involving technologies are typically ambitious and complex. Many projects fail. Greenhalgh et al’s nonadoption, abandonment, scale-up, spread, and sustainability (NASSS) framework was developed to analyze the varied outcomes of such projects. ObjectiveWe sought to extend the NASSS framework to produce practical tools for understanding, guiding, monitoring, and researching technology projects in health care or social care settings. MethodsBuilding on NASSS and a complexity assessment tool (CAT), the NASSS-CAT tools were developed (in various formats) in seven co-design workshops involving 50 stakeholders (industry executives, technical designers, policymakers, managers, clinicians, and patients). Using action research, they were and are being tested prospectively on a sample of case studies selected for variety in conditions, technologies, settings, scope and scale, policy context, and project goals. ResultsThe co-design process resulted in four tools, available as free downloads. NASSS-CAT SHORT is a taster to introduce the instrument and gauge interest. NASSS-CAT LONG is intended to support reflection, due diligence, and preliminary planning. It maps complexity through stakeholder discussion across six domains, using free-text open questions (designed to generate a rich narrative and surface uncertainties and interdependencies) and a closed-question checklist; this version includes an action planning section. NASSS-CAT PROJECT is a 35-item instrument for monitoring how subjective complexity in a technology implementation project changes over time. NASSS-CAT INTERVIEW is a set of prompts for conducting semistructured research or evaluation interviews. Preliminary data from empirical case studies suggest that the NASSS-CAT tools can potentially identify, but cannot always help reconcile, contradictions and conflicts that block projects’ progress. ConclusionsThe NASSS-CAT tools are a useful addition to existing implementation tools and frameworks. Further support of the implementation projects is ongoing. We are currently producing digital versions of the tools, and plan (subject to further funding) to establish an online community of practice for people interested in using and improving the tools, and hold workshops for building cross-project collaborations. International Registered Report Identifier (IRRID)DERR1-10.2196/16861

BackgroundStar 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). ObjectiveOur 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. MethodsIn 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. ResultsWe 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. ConclusionsInnovators 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.

BackgroundThe development and implementation of electronic health records (EHRs) remains an international challenge. Better understanding of patient and public attitudes and the factors that influence overall levels of support toward EHRs is needed to inform policy. ObjectiveTo explore patient and public attitudes toward integrated EHRs used simultaneously for health care provision, planning and policy, and health research. MethodsCross-sectional questionnaire survey administered to patients and members of the public who were recruited from a stratified cluster random sample of 8 outpatient clinics of a major teaching hospital and 8 general practices in London (United Kingdom). Results5331 patients and members of the public responded to the survey, with 2857 providing complete data for the analysis presented here. There were moderately high levels of support for integrated EHRs used simultaneously for health care provision, planning and policy, and health research (1785/2857, 62.47%), while 27.93% (798/2857) of participants reported being undecided about whether or not they would support EHR use. There were higher levels of support for specific uses of EHRs. Most participants were in favor of EHRs for personal health care provision (2563/2857, 89.71%), with 66.75% (1907/2857) stating that they would prefer their complete, rather than limited, medical history to be included. Of those “undecided” about integrated EHRs, 87.2% (696/798) were nevertheless in favor of sharing their full (373/798, 46.7%) or limited (323/798, 40.5%) records for health provision purposes. There were similar high levels of support for use of EHRs in health services policy and planning (2274/2857, 79.59%) and research (2325/2857, 81.38%), although 59.75% (1707/2857) and 67.10% (1917/2857) of respondents respectively would prefer their personal identifiers to be removed. Multivariable analysis showed levels of overall support for EHRs decreasing with age. Respondents self-identifying as Black British were more likely to report being undecided or unsupportive of national EHRs. Frequent health services users were more likely to report being supportive than undecided. ConclusionsDespite previous difficulties with National Health Service (NHS) technology projects, patients and the public generally support the development of integrated EHRs for health care provision, planning and policy, and health research. This support, however, varies between social groups and is not unqualified; relevant safeguards must be in place and patients should be guided in their decision-making process, including increased awareness about the benefits of EHRs for secondary uses.

Background: The NHS App launched in 2019 as the 'digital front door' to the National Health Service in England with core features including General Practitioner (GP) appointment booking, repeat prescriptions, patient access to records and, later on, COVID-19 vaccination certification. Similar patient portals have been adopted in different formats and with variable levels of success. In this longitudinal study (2021–2023) we examined how the NHS App became implemented in the pandemic context and beyond. Methods: We recruited 88 participants in 62 qualitative interviews and four focus groups. Participants included patients, carers, members of the public, clinical/non-clinical NHS staff from five GP practices (where we also conducted over 60 h of observations) across England, as well as other industry, policy and civil rights stakeholders. Document analysis also contributed to participant recruitment and data interpretation. Data collection and analysis was informed by the Non-Adoption, Abandonment, Scale-up, Spread and Sustainability (NASSS) framework. Results: Our study identified the various ways in which complexity manifested as part of the implementation, use and roll-out of the NHS App. Patients had diverse (positive and negative) user experiences as the app evolved, with some of its features described as more useful than others (e.g. prescription ordering, COVID Pass). As the app primarily provided a gateway to general practice systems and infrastructures, not all features were available by default or consistently to all users, with information often appearing fragmented or system-facing (e.g. coded). NHS staff viewed the app as constituting core NHS infrastructure in the long term which made it appealing, even though initially there was less recognition of its immediate value. There was variable organisational capacity to enable implementation and to put in place processes and staff roles required to support patient adoption. Shifting emphasis towards in-person care, challenges with digital inclusion and controversies related to features such as patient access to own records further complicated roll-out. Conclusions: As the NHS App remains a complex innovation in a shifting landscape, it is clear ongoing work is needed to ensure its potential can be sustained to meet patient, service and policy needs. Clinical study registration: ISRCTN72729780. [ABSTRACT FROM AUTHOR]

Background: The adoption of patient portals, such as the National Health Service (NHS) App in England, may improve patient engagement in health care. However, concerns remain regarding differences across sociodemographic groups in the uptake and use of various patient portal features, which have not been fully explored. Understanding the use of various functions across diverse populations is essential to ensure any benefits are equally distributed across the population. Objective: This study aims to explore differences in the use of NHS App features across age, sex, deprivation, ethnicity, long-term health care needs, and general practice (GP) size categories. Methods: We used weekly NHS App use data from the NHS App dashboard for 6386 GPs in England from March 2020 to June 2022. Negative binomial regression models explored variations in weekly rates of NHS App features used (registrations, log-ins, prescriptions ordered, medical record views, and appointments booked). Outcomes were measured as weekly rates per 1000 GP-registered patients, and we conducted separate models for each outcome. Regression models included all covariates mentioned above and produced incident rate ratios, which we present here as relative percentages for ease of interpretation. GP-level covariate data on sociodemographic variables were used as categorical variables in 5 groups for deprivation (Q1=least deprived practices and Q5=most deprived practices) and 4 groups for all other variables (Q1=least deprived practices and Q4=most deprived practices). Results: We found variations in the use of different features overall and across sociodemographic categories. Fully adjusted regression models found lower use of features overall in more deprived practices (eg, Q5 vs Q1: registrations=–34%, log-ins=–34.9%, appointments booked=–39.7%, medical record views=–32.3%, and prescriptions ordered=–9.9%; P <.001). Practices with greater proportions of male patients also had lower levels of NHS App use (eg, Q4 vs Q1: registration=–7.1%, log-in=–10.4%, and appointments booked=–36.4%; P <.001). Larger practices had an overall higher use of some NHS App features (eg, Q4 vs Q1: registration=3.2%, log-ins=11.7%, appointments booked=73.4%, medical record views=23.9%, and prescriptions ordered=20.7%; P <.001), as well as those with greater proportions of White patients (eg, Q4 vs Q1: registration=1.9%, log-ins=9.1%, appointments booked=14.1%, medical record views=28.7%, and prescriptions ordered=130.4%; P <.001). Use patterns varied for practices with greater proportions of patients with long-term health care needs (eg, Q4 vs Q1: registrations=–3.6%, appointments booked=–20%, and medical record views=6%; P ≤.001). Conclusions: This study highlights that the use of the NHS App features varied across sociodemographic groups. In particular, it is used less by people living in more deprived areas. Tailored interventions and patient support are required to ensure that any benefits from the NHS App are spread equally throughout the population. [ABSTRACT FROM AUTHOR]

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%5frecord.php?RecordID=256005 International Registered Report Identifier (IRRID): RR2-10.2196/33145 [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: The implementation of models of integrated care for chronic conditions is not well understood. We conducted a realist evaluation to determine how and why the implementation of the National Diabetes Programme in Ireland worked (or not). Methods: Documentary analysis and qualitative interviews with a purposive sample of national stakeholders (n = 19), were used to develop an initial theory on expected programme delivery. We refined this theory using semi-structured interviews (n = 38) with professionals from different clinical disciplines involved in programme implementation. Results: Locally important contexts facilitating implementation included staff experience of delivering diabetes care, capacity, and familiarity with the intended purpose of new clinical posts. The extent to which integrated care was adopted and implemented depended on judgements made by professionals working in these contexts; specifically, judging the relative advantage of the programme and whether to engage in negotiations to legitimize their new roles in diabetes care. Conclusions: Our results highlight the need for adequate preparatory work to raise awareness of and support new roles to implement integrated care, clarification on the core components of new care models, and the development of local service infrastructures to support integrated care. [ABSTRACT FROM AUTHOR]