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Nasir Hamid
Patient and public attitudes towards informed consent models and levels of awareness of Electronic Health Records in the UK
The development of Electronic Health Records (EHRs) forms an integral part of the information strategy for the National Health Service (NHS) in the UK, with the aim of facilitating health information exchange for patient care and secondary use, including research and healthcare planning. Implementing EHR systems requires an understanding of patient expectations for consent mechanisms and consideration of public awareness towards information sharing as might be made possible through integrated EHRs across primary and secondary health providers. Objectives: To explore levels of public awareness about EHRs and to examine attitudes towards different consent models with respect to sharing identifiable and de-identified records for healthcare provision, research and planning. Methods: A cross-sectional questionnaire survey was administered to adult patients and members of the public in primary and secondary care clinics in West London, UK in 2011. In total, 5331 individuals participated in the survey, and 3157 were included in the final analysis. Results: The majority (91%) of respondents expected to be explicitly asked for consent for their identifiable records to be accessed for health provision, research or planning. Half the respondents (49%) did not expect to be asked for consent before their de-identified records were accessed. Compared with White British respondents, those from all other ethnic groups were more likely to anticipate their permission would be obtained before their de-identified records were used. Of the study population, 59% reported already being aware of EHRs before the survey. Older respondents and individuals with complex patterns of interaction with healthcare services were more likely to report prior awareness of EHRs. Individuals self-identifying as belonging to ethnic groups other than White British, and those with lower educational qualifications were less likely to report being aware of EHRs than White British respondents and respondents with degree-level education, respectively. Those who reported being aware of EHRs were less likely to say they expected explicit consent to be sought before use of their de-identified record. Conclusions: A large number of patients remain unaware of EHRs, while preference for implicit consent is stronger among those who report previous awareness. Differences in awareness levels and consent expectations between groups with different socio-demographic characteristics suggest that public education and information campaigns should target specific groups to increase public awareness and ensure meaningful informed consent mechanisms.
Patient and public views on electronic health records and their uses in the United Kingdom: Cross-sectional survey
Background: The 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. Objective: To explore patient and public attitudes toward integrated EHRs used simultaneously for health care provision, planning and policy, and health research. Methods: Cross-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). Results: 5331 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. Conclusions: Despite 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.
Qualitative evaluation of the implementation and national roll-out of the NHS App in England
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.
Differences in Use of a Patient Portal Across Sociodemographic Groups: Observational Study of the NHS App in England
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
Adoption and Use of the NHS App in England: a mixed-methods evaluation
BACKGROUND: The NHS App was launched as a 'front door' to digitally enabled health services, offering a range of services including appointment booking and ordering prescriptions. The extent of App use and its impacts on digital inclusion is under-explored. AIM: To evaluate patterns of App uptake and adoption among different population groups. METHOD: Interrupted time series analyses explored aggregate monthly App usage from January 2019 - May 2021. Regression model assessed differences in App registration by markers of GP level socio-demographic variables. Qualitative interviews and focus groups involving 83 participants were conducted and analysed thematically. RESULTS: There were 8,524,882 App downloads and 4,449,869 registrations. Negative binomial models found 25% less registrations in the most deprived practices (P <0.001) and 44% more registrations in the largest practices (P<0.001). Registration was 36% more in practices with the highest percentage of White patients (P <0.001) and 23% more in practices with highest percentage of 15-34-year-olds (P <0.001). In contrast, App registration was 13% less in practices with highest percentage of males (P <0.001) and 2% less in those with highest percentage of people with long-term care needs (P <0.001). Qualitative evaluation found that the App was not perceived as relevant or accessible for all and there are important cultural considerations (for example, language barriers and some restrictions in symptom checking for non-White skin). However, it can enable patients to hold services accountable. CONCLUSION: There is high uptake of the NHS App but there are differences in adoption rates among different population groups and issues of relevance and accessibility, that warrant further work.
Uptake and adoption of the NHS App in England: an observational study
Background Technological advances have led to the use of patient portals that give people digital access to their personal health information. The NHS App was launched in January 2019 as a ‘front door’ to digitally enabled health services. Aim To evaluate patterns of uptake of the NHS App, subgroup differences in registration, and the impact of COVID-19. Design and setting An observational study using monthly NHS App user data at general-practice level in England was conducted. Method Descriptive statistics and time-series analysis explored monthly NHS App use from January 2019–May 2021. Interrupted time-series models were used to identify changes in the level and trend of use of different functionalities, before and after the first COVID-19 lockdown. Negative binomial regression assessed differences in app registration by markers of general-practice level sociodemographic variables. Result Between January 2019 and May 2021, there were 8 524 882 NHS App downloads and 4 449 869 registrations, with a 4-fold increase in App downloads when the COVID Pass feature was introduced. Analyses by sociodemographic data found 25% lower registrations in the most deprived practices (P<0.001), and 44% more registrations in the largest sized practices (P<0.001). Registration rates were 36% higher in practices with the highest proportion of registered White patients (P<0.001), 23% higher in practices with the largest proportion of 15–34-year-olds (P<0.001) and 2% lower in practices with highest proportion of people with long-term care needs (P<0.001). Conclusion The uptake of the NHS App substantially increased post-lockdown, most significantly after the NHS COVID Pass feature was introduced. An unequal pattern of app registration was identified, and the use of different functions varied. Further research is needed to understand these patterns of inequalities and their impact on patient experience.
Optimising the delivery and impacts of interventions to improve hospital doctors’ workplace wellbeing in the NHS: The Care Under Pressure 3 realist evaluation study
Background: The key role of medical workforce well-being in the delivery of excellent and equitable care is recognised internationally. However, doctors are known to experience significant mental ill health and erosion of their well-being due to challenging demands and pressurised work environments. Existing workplace support strategies often have limited effect and do not consider the multiple factors contributing to poor well-being in doctors (e.g. individual, organisational and social), nor whether interventions have been implemented effectively. Aim: To work with, and learn from, diverse hospital settings to understand how to optimise strategies to improve doctors’ workplace well-being and reduce negative impacts on the workforce and patient care. Design and method: Three inter-related sequential phases of research activity: • Phase 1: a typology of interventions and mapping tool to improve hospital doctors’ workplace well-being based on iterative cycles of analysis of published and in-practice interventions and informed by relevant theories and frameworks and engagement with stakeholders. • Phase 2: realist evaluation consistent with Realist And MEta-narrative Evidence Syntheses: Evolving Standards quality standards of existing strategies to improve hospital doctors’ workplace well-being in eight purposively selected acute National Health Service trusts in England based on 124 interviews with doctors, well-being intervention implementers/practitioners and leaders. • Phase 3: codeveloped implementation guidance for all National Health Service trusts to optimise their strategies to improve hospital doctors’ workplace well-being – drawing on phases 1 and 2, and engagement with stakeholders in three online national workshops. Results: • Phase 1: although many sources did not clarify their underlying assumptions about causal pathways or the theoretical basis of interventions, we were able to develop a typology and mapping tool which can be used to conceptualise interventions by type (e.g. whether they are designed to be largely preventative or ‘curative’). • Phase 2: key findings from our realist interviews were that: (1) solutions needed to align with problems to support doctor’s well-being and avoid harm to doctors; (2) involving doctors in creating solutions was important to address their well-being problems; (3) doctors often do not know what well-being support is available and (4) there were physical and psychological barriers to accessing well-being support. • Phase 3: our ‘Workplace well-being MythBuster’s guide’ provides constructive evidence-based implementation guidance, while authentically representing the predominantly negative experiences reported in phase 2. Limitations: Although we sampled for diversity, the eight trusts we worked with may not be representative of all trusts in England. Conclusions: Misaligned well-being solutions can cause harm. It is paramount to prioritise improvements in working environments, instead of well-being ‘add-on’s, and to involve doctors and other relevant staff in identifying problems and in planning how to address these. Future work: Further research is required to tailor the findings to primary care, mental health and social care settings. Health economic studies of well-being interventions (ideally, at systems level) are urgently required, since small investments could have far-reaching positive impacts.
Support for hospital doctors' workplace well-being in England: The Care under Pressure 3 realist evaluation
Introduction: The vital role of medical workforce well-being for improving patient experience and population health while assuring safety and reducing costs is recognised internationally. Yet the persistence of poor well-being outcomes suggests that current support initiatives are suboptimal. The aim of this research study was to work with, and learn from, diverse hospital settings to understand how to optimise strategies to improve doctors' well-being and reduce negative impacts on the workforce and patient care. Methods: Realist evaluation consistent with the Realist And Meta-narrative Evidence Synthesis: Evolving Standards (RAMESES) II quality standards. Realist interviews (n=124) with doctors, well-being intervention implementers/practitioners and leaders in eight hospital settings (England) were analysed using realist logic. Results: There were four key findings, underpinned by 21 context-mechanism-outcome configurations: (1) solutions needed to align with problems, to support doctor well-being and avoid harm to doctors; (2) doctors needed to be involved in creating solutions to their well-being problems; (3) doctors often did not know what support was available to help them with well-being problems and (4) there were physical and psychological barriers to accessing well-being support. Discussion and conclusion: Doctors are mandated to 'first, do no harm' to their patients, and the same consideration should be extended to doctors themselves. Since doctors can be harmed by poorly designed or implemented well-being interventions, new approaches need careful planning and evaluation. Our research identified many ineffective or harmful interventions that could be stopped. The findings are likely transferable to other settings and countries, given the realist approach leading to principles and causal explanations.
Developing a typology of interventions to support doctors’ mental health and wellbeing
Background: The problem of mental ill-health in doctors is complex, accentuated by the COVID-19 pandemic, and impacts on healthcare provision and broader organisational performance. There are many interventions to address the problem but currently no systematic way to categorise them, which makes it hard to describe and compare interventions. As a result, implementation tends to be unfocussed and fall short of the standards developed for implementing complex healthcare interventions. This study aims to develop: 1) a conceptual typology of workplace mental health and wellbeing interventions and 2) a mapping tool to apply the typology within research and practice. Methods: Typology development was based on iterative cycles of analysis of published and in-practice interventions, incorporation of relevant theories and frameworks, and team and stakeholder group discussions. Results: The newly developed typology and mapping tool enable interventions to be conceptualised and/or mapped into different categories, for example whether they are designed to be largely preventative (by either improving the workplace or increasing personal resources) or to resolve problems after they have arisen. Interventions may be mapped across more than one category to reflect the nuance and complexity in many mental health and wellbeing interventions. Mapping of interventions indicated that most publications have not clarified their underlying assumptions about what causes outcomes or the theoretical basis for the intervention. Conclusion: The conceptual typology and mapping tool aims to raise the quality of future research and promote clear thinking about the nature and purpose of interventions, In doing so it aims to support future research and practice in planning interventions to improve the mental health and wellbeing of doctors.
The usage of data in NHS primary care commissioning: a realist review
Background: Primary care has been described as the ‘bedrock’ of the National Health Service (NHS) accounting for approximately 90% of patient contacts but is facing significant challenges. Against a backdrop of a rapidly ageing population with increasingly complex health challenges, policy-makers have encouraged primary care commissioners to increase the usage of data when making commissioning decisions. Purported benefits include cost savings and improved population health. However, research on evidence-based commissioning has concluded that commissioners work in complex environments and that closer attention should be paid to the interplay of contextual factors and evidence use. The aim of this review was to understand how and why primary care commissioners use data to inform their decision making, what outcomes this leads to, and understand what factors or contexts promote and inhibit their usage of data. Methods: We developed initial programme theory by identifying barriers and facilitators to using data to inform primary care commissioning based on the findings of an exploratory literature search and discussions with programme implementers. We then located a range of diverse studies by searching seven databases as well as grey literature. Using a realist approach, which has an explanatory rather than a judgemental focus, we identified recurrent patterns of outcomes and their associated contexts and mechanisms related to data usage in primary care commissioning to form context-mechanism-outcome (CMO) configurations. We then developed a revised and refined programme theory. Results: Ninety-two studies met the inclusion criteria, informing the development of 30 CMOs. Primary care commissioners work in complex and demanding environments, and the usage of data are promoted and inhibited by a wide range of contexts including specific commissioning activities, commissioners’ perceptions and skillsets, their relationships with external providers of data (analysis), and the characteristics of data themselves. Data are used by commissioners not only as a source of evidence but also as a tool for stimulating commissioning improvements and as a warrant for convincing others about decisions commissioners wish to make. Despite being well-intentioned users of data, commissioners face considerable challenges when trying to use them, and have developed a range of strategies to deal with ‘imperfect’ data. Conclusions: There are still considerable barriers to using data in certain contexts. Understanding and addressing these will be key in light of the government’s ongoing commitments to using data to inform policy-making, as well as increasing integrated commissioning.
The usage of data in NHS primary care commissioning: a realist evaluation
Background: To improve health outcomes and address mounting costs pressures, policy-makers have encouraged primary care commissioners in the British National Health Service (NHS) to increase the usage of data in decision-making. However, there exists limited research on this topic. In this study, we aimed to understand how and why primary care commissioners use data (i.e. quantitative, statistical information) to inform commissioning, and what outcomes this leads to. Methods: A realist evaluation was completed to create context-mechanism-outcome configurations (CMOs) relating to the contexts influencing the usage of data in primary care commissioning. Using a realist logic of analysis and drawing on substantive theories, we analysed qualitative content from 30 interviews and 51 meetings (51 recordings and 19 accompanying meeting minutes) to develop CMOs. Purposive sampling was used to recruit interviewees from diverse backgrounds. Results: Thirty-five CMOs were formed, resulting in an overarching realist programme theory. Thirteen CMOs were identical and 3 were truncated versions of those formed in an existing realist synthesis on the same topic. Seven entirely new CMOs, and 12 refined and enhanced CMOs vis-à-vis the synthesis were created. The findings included CMOs containing contexts which facilitated the usage of data, including the presence of a data champion and commissioners’ perceptions that external providers offered new skillsets and types of data. Other CMOs included contexts presenting barriers to using data, such as data not being presented in an interoperable way with consistent definitions, or financial pressures inhibiting commissioners’ abilities to make evidence-based decisions. Conclusions: Commissioners are enthusiastic about using data as a source of information, a tool to stimulate improvements, and a warrant for decision-making. However, they also face considerable challenges when using them. There are replicable contexts available to facilitate commissioners’ usage of data, which we used to inform policy recommendations. The findings of this study and our recommendations are pertinent in light of governments’ increasing commitment to data-driven commissioning and health policy-making.
How can NHS trusts in England optimise strategies to improve the mental health and well-being of hospital doctors? The Care Under Pressure 3 (CUP3) realist evaluation study protocol
Introduction The growing incidence of mental ill health in doctors was a major issue in the UK and internationally, even prior to the COVID-19 pandemic. It has significant and far-reaching implications, including poor quality or inconsistent patient care, absenteeism, workforce attrition and retention issues, presenteeism, and increased risk of suicide. Existing approaches to workplace support do not take into account the individual, organisational and social factors contributing to mental ill health in doctors, nor how interventions/programmes might interact with each other within the workplace. The aim of this study is to work collaboratively with eight purposively selected National Health Service (NHS) trusts within England to develop an evidence-based implementation toolkit for all NHS trusts to reduce doctors' mental ill health and its impacts on the workforce. Methods and analysis The project will incorporate three phases. Phase 1 develops a typology of interventions to reduce doctors' mental ill health. Phase 2 is a realist evaluation of the existing combinations of strategies being used by acute English healthcare trusts to reduce doctors' mental ill health (including preventative promotion of well-being), based on 160 interviews with key stakeholders. Phase 3 synthesises the insights gained through phases 1 and 2, to create an implementation toolkit that all UK healthcare trusts can use to optimise their strategies to reduce doctors' mental ill health and its impact on the workforce and patient care. Ethics and dissemination Ethical approval has been granted for phase 2 of the project from the NHS Research Ethics Committee (REC reference number 22/WA/0352). As part of the conditions for our ethics approval, the sites included in our study will remain anonymous. To ensure the relevance of the study's outputs, we have planned a wide range of dissemination strategies: an implementation toolkit for healthcare leaders, service managers and doctors; conventional academic outputs such as journal manuscripts and conference presentations; plain English summaries; cartoons and animations; and a media engagement campaign.
Interventions to minimise doctors’ mental ill-health and its impacts on the workforce and patient care: the Care Under Pressure realist review
BackgroundThe growing incidence of mental ill-health in health professionals, including doctors, is a global concern. Although a large body of literature exists on interventions that offer support, advice and/or treatment to sick doctors, it has not yet been synthesised in a way that takes account of the complexity and heterogeneity of the interventions, and the many dimensions (e.g. individual, organisational, sociocultural) of the problem.ObjectivesOur aim was to improve understanding of how, why and in what contexts mental health services and support interventions can be designed to minimise the incidence of doctors’ mental ill-health. The objectives were to review interventions to tackle doctors’ mental ill-health and its impact on the clinical workforce and patient care, drawing on diverse literature sources and engaging iteratively with diverse stakeholder perspectives to produce actionable theory; and recommendations that support the tailoring, implementation, monitoring and evaluation of contextually sensitive strategies to tackle mental ill-health and its impacts.DesignRealist literature review consistent with the Realist And Meta-narrative Evidence Syntheses: Evolving Standards quality and reporting standards.Data sourcesBibliographic database searches were developed and conducted using MEDLINE (1946 to November week 4 2017), MEDLINE In-Process and Other Non-indexed Citations (1946 to 6 December 2017) and PsycINFO (1806 to November week 2 2017) (all via Ovid) and Applied Social Sciences Index and Abstracts (1987 to 6 December 2017) (via ProQuest) on 6 December 2017. Further UK-based studies were identified by forwards and author citation searches, manual backwards citation searching and hand-searching relevant journal websites.Review methodsWe included all studies that focused on mental ill-health; all study designs; all health-care settings; all studies that included medical doctors/medical students; descriptions of interventions or resources that focus on improving mental ill-health and minimising its impacts; all mental health outcome measures, including absenteeism (doctors taking short-/long-term sick leave); presenteeism (doctors working despite being unwell); and workforce retention (doctors leaving the profession temporarily/permanently). Data were extracted from included articles and the data set was subjected to realist analysis to identify context–mechanism–outcome configurations.ResultsA total of 179 out of 3069 records were included. Most were from the USA (45%) and had been published since 2009 (74%). More included articles focused on structural-level interventions (33%) than individual-level interventions (21%), but most articles (46%) considered both levels. Most interventions focused on prevention, rather than treatment/screening, and most studies referred to doctors/physicians in general, rather than to specific specialties or career stages. Nineteen per cent of the included sources provided cost information and none reported a health economic analysis. The 19 context–mechanism–outcome configurations demonstrated that doctors were more likely to experience mental ill-health when they felt isolated or unable to do their job, and when they feared repercussions of help-seeking. Healthy staff were necessary for excellent patient care. Interventions emphasising relationships and belonging were more likely to promote well-being. Interventions creating a people-focused working culture, balancing positive/negative performance and acknowledging positive/negative aspects of a medical career helped doctors to thrive. The way that interventions were implemented seemed critically important. Doctors needed to have confidence in an intervention for the intervention to be effective.LimitationsVariable quality of included literature; limited UK-based studies.Future workUse this evidence synthesis to refine, implement and evaluate interventions.Study registrationThis study is registered as PROSPERO CRD42017069870.FundingThis project was funded by the National Institute for Health Research (NIHR) Health Services and Delivery Research programme and will be published in full in Health Services and Delivery Research; Vol. 8, No. 19. See the NIHR Journals Library website for further project information.
Postdischarge health information tools and information needs for mothers of vulnerable newborns in low- and middle-income countries: a scoping review
OBJECTIVES: The postdischarge period is crucial for vulnerable newborns at risk of morbidity, readmission and mortality in low- and middle-income countries (LMICs). Addressing gaps in care during this period could improve outcomes. This review consolidates evidence on caregiver information needs and relevant information tools used in postdischarge care for vulnerable newborns in LMICs. DESIGN: Scoping review using the methodological framework developed by Arksey and O'Malley. DATA SOURCES: We searched six databases for relevant articles published in English between 2001 and 2021. Additional articles were identified through citation and reference checking. ELIGIBILITY CRITERIA: Articles on postdischarge care for newborns in LMICs, excluding economic and technical development studies, discharge to other healthcare facilities (rather than to home) and maternal-focused studies. DATA EXTRACTION AND SYNTHESIS: Data extraction followed Arksey and O'Malley's data charting method. Using a descriptive synthesis approach, heterogeneous data were collated in narrative format. RESULTS: From 5190 articles, 22 were included. Only a small number of articles discussed caregiver challenges, like receiving insufficient information at discharge which led to uncertainty in caring for vulnerable newborns. Caregivers had a number of needs in relation to maternal and newborn care, including in terms of coordination of follow-up care. Although a number of tools have been used to support relevant needs (for postnatal care in general rather than specifically for postdischarge care of vulnerable newborns), these have shown mixed effectiveness due to challenges with completeness, lack of training and support, supply chain issues and cultural barriers to adoption, such as preference for alternative providers. CONCLUSION: Our understanding of postdischarge information needs for those looking after vulnerable newborns in LMICs remains limited. More effective use of information tools could help address some of these needs and contribute towards reducing neonatal mortality rates.
‘Online boundary-work’: How people with diabetes negotiate what counts as legitimate knowledge in Facebook peer support groups
People with chronic conditions such as diabetes use social media to interact with peers. While these online interactions allow them to exchange advice and gain insight into how others cope with their condition, concerns about ‘misinformation’ being shared are persistently raised, especially among medical professionals. Rather than assessing whether information shared on social media is ‘correct’ from a clinical perspective, we explore how people with diabetes negotiate what counts as legitimate knowledge as they interact in Facebook groups. Empirically, we draw on a six-month observation of interactions in two Danish Facebook groups for people with type 1 and 2 diabetes, including a data sample of 300 posts and 7797 comments. Observations were carried out in 2021. Guided by the concept of boundary-work (Gieryn, 1983), we analyse how members of the Facebook groups demarcate legitimate knowledge from what they deem illegitimate, enacted as they scrutinise peer advice and knowledge claims. We refer to this ongoing process as ‘online boundary-work’ and draw out three distinct negotiations, specifying how group members (a) recognise sharing of personal experiences as useful but do not necessarily accept them as valid forms of self-management advice, (b) support each other in evaluating medical issues but delegate certain treatment decisions and responsibility to professionals and (c) do not necessarily agree on the most accurate answer but mobilise scientific or professionally managed sources to legitimise or question claims. Our work contributes to the science and technology studies (STS) literature on how social media facilitates a collective space for people with chronic conditions to ‘diagnose’ issues in daily self-management and reflect on solutions, especially through sharing personal experiences. By demonstrating how these activities involve an ongoing, collective task of negotiating what counts as legitimate knowledge, we elucidate the effort people with diabetes put into upholding peer support groups as digital spaces for solidarity and knowledge useful to daily self-management. However, as we highlight, online boundary-work does not necessarily result in consensus, prevent certain types of advice from being shared or guarantee that answers are considered useful to members or ‘correct’ from a clinical perspective.
Scoping review of interventions to improve continuity of postdischarge care for newborns in LMICs
Introduction Neonatal mortality remains significant in low-income and middle-income countries (LMICs) with in-hospital mortality rates similar to those following discharge from healthcare facilities. Care continuity interventions have been suggested as a way of reducing postdischarge mortality by better linking care between facilities and communities. This scoping review aims to map and describe interventions used in LMICs to improve care continuity for newborns after discharge and examine assumptions underpinning the design and delivery of continuity. Methods We searched seven databases (MEDLINE, CINAHL, Scopus, Web of Science, EMBASE, Cochrane library and (Ovid) Global health). Publications with primary data on interventions focused on continuity of care for newborns in LMICs were included. Extracted data included year of publication, study location, study design and type of intervention. Drawing on relevant theoretical frameworks and classifications, we assessed the extent to which interventions adopted participatory methods and how they attempted to establish continuity. Results A total of 65 papers were included in this review; 28 core articles with rich descriptions were prioritised for more in-depth analysis. Most articles adopted quantitative designs. Interventions focused on improving continuity and flow of information via education sessions led by community health workers during home visits. Extending previous frameworks, our findings highlight the importance of interpersonal continuity in LMICs where communication and relationships between family members, healthcare workers and members of the wider community play a vital role in creating support systems for postdischarge care. Only a small proportion of studies focused on high-risk babies. Some studies used participatory methods, although often without meaningful engagement in problem definition and intervention implementation. Conclusion Efforts to reduce neonatal mortality and morbidity should draw across multiple continuity logics (informational, relational, interpersonal and managerial) to strengthen care after hospital discharge in LMIC settings and further focus on high-risk neonates, as they often have the worst outcomes.
Stakeholder Perspectives of Clinical Artificial Intelligence Implementation: Systematic Review of Qualitative Evidence
Background: The rhetoric surrounding clinical artificial intelligence (AI) often exaggerates its effect on real-world care. Limited understanding of the factors that influence its implementation can perpetuate this. Objective: In this qualitative systematic review, we aimed to identify key stakeholders, consolidate their perspectives on clinical AI implementation, and characterize the evidence gaps that future qualitative research should target. Methods: Ovid-MEDLINE, EBSCO-CINAHL, ACM Digital Library, Science Citation Index-Web of Science, and Scopus were searched for primary qualitative studies on individuals’ perspectives on any application of clinical AI worldwide (January 2014-April 2021). The definition of clinical AI includes both rule-based and machine learning–enabled or non–rule-based decision support tools. The language of the reports was not an exclusion criterion. Two independent reviewers performed title, abstract, and full-text screening with a third arbiter of disagreement. Two reviewers assigned the Joanna Briggs Institute 10-point checklist for qualitative research scores for each study. A single reviewer extracted free-text data relevant to clinical AI implementation, noting the stakeholders contributing to each excerpt. The best-fit framework synthesis used the Nonadoption, Abandonment, Scale-up, Spread, and Sustainability (NASSS) framework. To validate the data and improve accessibility, coauthors representing each emergent stakeholder group codeveloped summaries of the factors most relevant to their respective groups. Results: The initial search yielded 4437 deduplicated articles, with 111 (2.5%) eligible for inclusion (median Joanna Briggs Institute 10-point checklist for qualitative research score, 8/10). Five distinct stakeholder groups emerged from the data: health care professionals (HCPs), patients, carers and other members of the public, developers, health care managers and leaders, and regulators or policy makers, contributing 1204 (70%), 196 (11.4%), 133 (7.7%), 129 (7.5%), and 59 (3.4%) of 1721 eligible excerpts, respectively. All stakeholder groups independently identified a breadth of implementation factors, with each producing data that were mapped between 17 and 24 of the 27 adapted Nonadoption, Abandonment, Scale-up, Spread, and Sustainability subdomains. Most of the factors that stakeholders found influential in the implementation of rule-based clinical AI also applied to non–rule-based clinical AI, with the exception of intellectual property, regulation, and sociocultural attitudes. Conclusions: Clinical AI implementation is influenced by many interdependent factors, which are in turn influenced by at least 5 distinct stakeholder groups. This implies that effective research and practice of clinical AI implementation should consider multiple stakeholder perspectives. The current underrepresentation of perspectives from stakeholders other than HCPs in the literature may limit the anticipation and management of the factors that influence successful clinical AI implementation. Future research should not only widen the representation of tools and contexts in qualitative research but also specifically investigate the perspectives of all stakeholder HCPs and emerging aspects of non–rule-based clinical AI implementation.