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BACKGROUND: Inhaled corticosteroids (ICS) are the cornerstone of asthma treatment and significantly improve morbidity and mortality. Adverse effects of oral corticosteroids are well documented, but less is known about ICS. METHODS: We conducted observational studies in adults with asthma using two different UK nationwide datasets: Clinical Practice Research Datalink (CPRD) Aurum and CPRD GOLD. The exposure was incident ICS; the outcomes were major adverse cardiac events (MACE), arrhythmia, pulmonary embolism (PE) and pneumonia over 12-months. Our main analyses used a cohort method with stabilized inverse probability treatment weighting to balance confounding between exposed and unexposed patients. Secondary analyses included nested case-control studies, and self-controlled case series. ICS was treated both as a categorical and continuous variable. Absolute risk was estimated using weighted flexible parametric models. FINDINGS: From 162,202 patients in our main cohort, there was an association with all outcomes at medium daily ICS dose or higher (HR, 95%CI at 201-599mcg: MACE=2.63, 1.66-4.15, arrhythmia=2.21, 1.60-3.04, PE=2.10, 1.37-3.22, pneumonia=2.25, 1.77-2.85; at ≥600mcg: MACE=4.63, 2.62-8.17, arrhythmia=2.91, 1.72-4.91, PE=3.32, 1.69-6.50, pneumonia=4.09, 2.98-5.60). There were no associations with lower doses of ICS. Secondary analyses produced similar results. The number needed to harm (95%CI) using 12-months of ICS 201-599mcg: MACE=473 (344-754), arrhythmia=567 (395-1006), PE=1221 (744-3388) and pneumonia=230 (177-327) and using ICS ≥600mcg: MACE=224 (148-461), arrhythmia=396 (228-1523), PE=577 (309-4311), pneumonia=93 (69-141). INTERPRETATION: Short-term use of low dose ICS was not associated with adverse effects. Moderate-high daily ICS doses were associated with an increased risk, but low-frequency, of cardiovascular events, pulmonary embolism and pneumonia. It is important for clinicians to adhere to guideline recommendations to use the lowest effective ICS dose. This article is open access and distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/).
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OBJECTIVES: To determine demographic and clinical characteristics associated with uptake of COVID-19 vaccines among pregnant women, and quantify the relationship between vaccine uptake and admission to hospital for COVID-19. BACKGROUND: Pregnant women are at increased risk of severe adverse outcomes from COVID-19. Since April 2021, COVID-19 vaccines were recommended for pregnant women in the UK. Despite this, evidence shows vaccine uptake is low. However, this evidence has been based only on women admitted to hospital, or on qualitative or survey-based studies. METHODS: Retrospective cohort study including all pregnancies ending between 18 June 2021 and 22 August 2022, among adult women registered with a Northwest London general practice. Statistical analyses were mixed-effects multiple logistic regression models. We conducted a nested case-control analysis to quantify the relationship between vaccine uptake by end of pregnancy and hospitalisation for COVID-19 during pregnancy. RESULTS: Our study included 47,046 pregnancies among 39,213 women. In 26,724 (57%) pregnancies, women had at least one dose of vaccine by the end of pregnancy. Uptake was lowest in pregnant women aged 18-24 (33%; reference group), Black women compared with White (37%; OR 0.55, 95% CI: 0.51 to 0.60), and women in more deprived areas (50%; reference group). Women with chronic conditions were more likely to receive the vaccine than women without (Asthma OR 1.21, 95% CI: 1.13 to 1.29). Patterns were similar for the second dose. Women admitted to hospital were much less likely to be vaccinated (22%) than those not admitted (57%, OR 0.22, 95% CI: 0.15 to 0.31). CONCLUSIONS: Women who received the COVID-19 vaccine were less likely to be hospitalised for COVID-19 during pregnancy. COVID-19 vaccine uptake among pregnant women is suboptimal, particularly in younger women, Black women, and women in more deprived areas. Interventions should focus on increasing uptake in these groups to improve health outcomes and reduce health inequalities.
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INTRODUCTION: Increasing demand for healthcare services worldwide has led to unprecedented challenges in managing patient flow and delivering timely care in emergency care settings. Overcrowding, prolonged waiting times, reduced patient satisfaction and increased mortality are some of the consequences of this increased demand. To address this issue, some healthcare providers have turned to digital systems, such as self-check-in kiosks, for efficient patient triage and prioritisation. While digital triage systems hold promise for efficient patient prioritisation, reduced data duplication, shorter waiting times, improved patient satisfaction, the impact on workflow, the accuracy of triage and staff workload require further exploration for successful implementation in emergency care settings. This systematic review aims to assess the efficacy and safety of digital check-in and triage kiosk implementation within emergency departments. METHODS AND ANALYSIS: A systematic review will be conducted in MEDLINE (Ovid), Web of Science, Scopus and Science Direct and will include quantitative and mixed method studies with a significant quantitative component, related to self-service kiosk implementation in emergency departments. The outcomes of interest will focus on the efficacy and safety of digital triage, including triage time, workflow, the diagnostic accuracy of triage and adverse events. Risk of bias will be assessed using the Cochrane Risk of Bias Tool. A narrative synthesis will be used to summarise the findings of the included studies. ETHICS AND DISSEMINATION: This review is exempt from ethical approval because it will be analysing published studies containing non-identifiable data. The findings will be disseminated through peer-reviewed publications. PROSPERO REGISTRATION NUMBER: CRD42024481506.
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Emergency Service, Hospital , Systematic Reviews as Topic , Triage , Triage/methods , Humans , Emergency Service, Hospital/organization & administration , Research Design , Workflow , Patient SatisfactionABSTRACT
BACKGROUND: Identifying clusters of diseases may aid understanding of shared aetiology, management of co-morbidities, and the discovery of new disease associations. Our study aims to identify disease clusters using a large set of long-term conditions and comparing methods that use the co-occurrence of diseases versus methods that use the sequence of disease development in a person over time. METHODS: We use electronic health records from over ten million people with multimorbidity registered to primary care in England. First, we extract data-driven representations of 212 diseases from patient records employing (i) co-occurrence-based methods and (ii) sequence-based natural language processing methods. Second, we apply the graph-based Markov Multiscale Community Detection (MMCD) to identify clusters based on disease similarity at multiple resolutions. We evaluate the representations and clusters using a clinically curated set of 253 known disease association pairs, and qualitatively assess the interpretability of the clusters. RESULTS: Both co-occurrence and sequence-based algorithms generate interpretable disease representations, with the best performance from the skip-gram algorithm. MMCD outperforms k-means and hierarchical clustering in explaining known disease associations. We find that diseases display an almost-hierarchical structure across resolutions from closely to more loosely similar co-occurrence patterns and identify interpretable clusters corresponding to both established and novel patterns. CONCLUSIONS: Our method provides a tool for clustering diseases at different levels of resolution from co-occurrence patterns in high-dimensional electronic health records, which could be used to facilitate discovery of associations between diseases in the future.
Having multiple long-term conditions is linked to worse health, poorer quality of life, and difficulties accessing healthcare. Identifying groups, or 'clusters' of diseases that are more likely to occur together in one person may help healthcare services to better meet the needs of those with multiple conditions. Our study aims to identify clusters of similar diseases, based not only on the diseases someone has now, but on the order in which they developed them. We compare a range of methods and find that our strategy performs best at explaining diseases that are already known to be linked, whilst also identifying new clusters of diseases. These methods could be used in future to better understand how diseases occur together, which could help the design of more efficient healthcare services.
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OBJECTIVE: Natural language processing (NLP) algorithms are increasingly being applied to obtain unsupervised representations of electronic health record (EHR) data, but their comparative performance at predicting clinical endpoints remains unclear. Our objective was to compare the performance of unsupervised representations of sequences of disease codes generated by bag-of-words versus sequence-based NLP algorithms at predicting clinically relevant outcomes. MATERIALS AND METHODS: This cohort study used primary care EHRs from 6 286 233 people with Multiple Long-Term Conditions in England. For each patient, an unsupervised vector representation of their time-ordered sequences of diseases was generated using 2 input strategies (212 disease categories versus 9462 diagnostic codes) and different NLP algorithms (Latent Dirichlet Allocation, doc2vec, and 2 transformer models designed for EHRs). We also developed a transformer architecture, named EHR-BERT, incorporating sociodemographic information. We compared the performance of each of these representations (without fine-tuning) as inputs into a logistic classifier to predict 1-year mortality, healthcare use, and new disease diagnosis. RESULTS: Patient representations generated by sequence-based algorithms performed consistently better than bag-of-words methods in predicting clinical endpoints, with the highest performance for EHR-BERT across all tasks, although the absolute improvement was small. Representations generated using disease categories perform similarly to those using diagnostic codes as inputs, suggesting models can equally manage smaller or larger vocabularies for prediction of these outcomes. DISCUSSION AND CONCLUSION: Patient representations produced by sequence-based NLP algorithms from sequences of disease codes demonstrate improved predictive content for patient outcomes compared with representations generated by co-occurrence-based algorithms. This suggests transformer models may be useful for generating multi-purpose representations, even without fine-tuning.
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Algorithms , Electronic Health Records , Natural Language Processing , Humans , Cohort Studies , Female , Male , Disease/classification , EnglandABSTRACT
BACKGROUND: Migrants in the UK and Europe face vulnerability to vaccine-preventable diseases (VPDs) due to missed childhood vaccines and doses and marginalisation from health systems. Ensuring migrants receive catch-up vaccinations, including MMR, Td/IPV, MenACWY, and HPV, is essential to align them with UK and European vaccination schedules and ultimately reduce morbidity and mortality. However, recent evidence highlights poor awareness and implementation of catch-up vaccination guidelines by UK primary care staff, requiring novel approaches to strengthen the primary care pathway. METHODS: The 'Vacc on Track' study (May 2021-September 2022) aimed to measure under-vaccination rates among migrants in UK primary care and establish new referral pathways for catch-up vaccination. Participants included migrants aged 16 or older, born outside of Western Europe, North America, Australia, or New Zealand, in two London boroughs. Quantitative data on vaccination history, referral, uptake, and sociodemographic factors were collected, with practice nurses prompted to deliver catch-up vaccinations following UK guidelines. Focus group discussions and in-depth interviews with staff and migrants explored views on delivering catch-up vaccination, including barriers, facilitators, and opportunities. Data were analysed using STATA12 and NVivo 12. RESULTS: Results from 57 migrants presenting to study sites from 18 countries (mean age 41 [SD 7.2] years; 62% female; mean 11.3 [SD 9.1] years in UK) over a minimum of 6 months of follow-up revealed significant catch-up vaccination needs, particularly for MMR (49 [86%] required catch-up vaccination) and Td/IPV (50 [88%]). Fifty-three (93%) participants were referred for any catch-up vaccination, but completion of courses was low (6 [12%] for Td/IPV and 33 [64%] for MMR), suggesting individual and systemic barriers. Qualitative in-depth interviews (n = 39) with adult migrants highlighted the lack of systems currently in place in the UK to offer catch-up vaccination to migrants on arrival and the need for health-care provider skills and knowledge of catch-up vaccination to be improved. Focus group discussions and interviews with practice staff (n = 32) identified limited appointment/follow-up time, staff knowledge gaps, inadequate engagement routes, and low incentivisation as challenges that will need to be addressed. However, they underscored the potential of staff champions, trust-building mechanisms, and community-based approaches to strengthen catch-up vaccination uptake among migrants. CONCLUSIONS: Given the significant catch-up vaccination needs of migrants in our sample, and the current barriers to driving uptake identified, our findings suggest it will be important to explore this public health issue further, potentially through a larger study or trial. Strengthening existing pathways, staff capacity and knowledge in primary care, alongside implementing new strategies centred on cultural competence and building trust with migrant communities will be important focus areas.
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General Practice , Transients and Migrants , Vaccination , Humans , Pilot Projects , Male , Adolescent , Female , Adult , United Kingdom , Young Adult , Vaccination/statistics & numerical data , General Practice/statistics & numerical data , Middle AgedABSTRACT
INTRODUCTION: Polypharmacy is common among individuals with multimorbidity, often leading to inappropriate medication use and is associated with an increased risk of frailty, hospitalisation and mortality. Structured medication reviews (SMRs) have emerged as a promising method for optimising medication use. However, research examining their efficacy is limited. This review aims to evaluate the impact of SMRs on improving outcomes for adults with multimorbidity and polypharmacy in primary care settings. Additionally, this review seeks to identify prevailing patterns and trends in the mode of delivery of SMRs. METHODS AND ANALYSIS: A systematic review will be conducted using Ovid MEDLINE, Ovid EMBASE, Web of Science and CINAHL (1997-present). Primary outcomes will include medication-related measures such as dose, frequency and dosage form. Secondary outcomes under investigation will include physical, mental, functional and health service outcomes, as reported. Two independent reviewers will conduct the screening and data extraction, resolving disagreements through discussion. Once eligible studies are identified, the extracted data will be summarised in tabular format. The risk of bias in the articles will be assessed using either the Cochrane Risk of Bias 2 tool or the Newcastle-Ottawa scale, depending on the design of the studies retrieved. Subgroup analysis will be performed using demographic variables and modes of delivery where the data supports. If appropriate, a meta-analysis of the data extracted will be conducted to determine the impact of the SMRs on reported outcomes. If a meta-analysis is not possible due to heterogeneity, a narrative synthesis approach will be adopted. ETHICS AND DISSEMINATION: This proposed review is exempt from ethical approval as it aims to collate and summarise peer-reviewed, published evidence. This protocol and the subsequent review will be disseminated in peer-reviewed journals, conferences and patient-led lay summaries. PROSPERO REGISTRATION NUMBER: CRD42023454965.
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Multimorbidity , Polypharmacy , Primary Health Care , Systematic Reviews as Topic , Humans , Research Design , Inappropriate Prescribing/prevention & control , Inappropriate Prescribing/statistics & numerical data , AdultABSTRACT
INTRODUCTION: Effective treatment of severe asthma requires patient adherence to inhaled and biological medications. Previous work has shown that patient support programmes (PSP) can improve adherence in patients with chronic diseases, but the impact of PSPs in patients with severe asthma treated with biologics has not been thoroughly investigated. METHODS: We conducted a systematic literature review to understand the impact of PSPs on treatment adherence, asthma control and health-related quality of life (HRQoL) in patients with severe asthma. Embase, MEDLINE and EconLit databases were searched for studies published from 2003 (the year of the first biological approval for severe asthma) to June 2023 that described PSP participation among patients with severe asthma on biological treatment. Direct pooling of outcomes was not possible due to the heterogeneity across studies, so an indirect treatment comparison (ITC) was performed to determine the effect of PSP participation on treatment discontinuation. The ITC used patient-level data from patients treated with benralizumab either enrolled in a PSP (VOICE study, Connect 360 PSP) or not enrolled in a PSP (Benralizumab Patient Access Programme study) in the UK. FINDINGS: 25 records of 21 studies were selected. Six studies investigated the impact of PSPs on treatment adherence, asthma control or HRQoL. All six studies reported positive outcomes for patients enrolled in PSPs; the benefits of each PSP were closely linked to the services provided. The ITC showed that patients in the Connect 360 PSP group were less likely to discontinue treatment compared with the non-PSP group (OR 0.26, 95% CI 0.11 to 0.57, p<0.001). CONCLUSIONS: PSPs contribute to positive clinical outcomes in patients with severe asthma on biological treatment. Future analyses will benefit from thorough descriptions of PSP services, and study designs that allow direct comparisons of patient outcomes with and without a PSP.
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Anti-Asthmatic Agents , Asthma , Quality of Life , Asthma/drug therapy , Asthma/therapy , Humans , Anti-Asthmatic Agents/therapeutic use , Medication Adherence , Severity of Illness Index , Antibodies, Monoclonal, Humanized/therapeutic use , Biological Therapy/methodsSubject(s)
Primary Health Care , State Medicine , Primary Health Care/organization & administration , Primary Health Care/trends , State Medicine/organization & administration , Humans , United Kingdom , Delivery of Health Care, Integrated/organization & administration , Delivery of Health Care, Integrated/trends , ForecastingABSTRACT
INTRODUCTION: Vaccination during pregnancy protects both the mother and the foetus from vaccine-preventable diseases. However, uptake of the recommended vaccines (influenza, pertussis, COVID-19) by pregnant women remains low in Europe and the USA. Understanding the reasons for this is crucial to inform strategies to increase vaccination rates in pregnant women. This qualitative systematic review aimed to identify the barriers and facilitators to vaccination against influenza, pertussis/whooping cough and COVID-19 during pregnancy and identify possible strategies to increase vaccination rates. METHODS: We conducted a comprehensive search of electronic databases, including Medline, PsycINFO, CINAHL, Web of Science, WHO database, Embase and grey literature to identify qualitative studies that explored barriers and facilitators to vaccine uptake among pregnant women (PROSPERO CRD42023399488). The search was limited to studies published between 2012 and 2022 conducted in high-income countries with established vaccination programmes during pregnancy. Studies were thematically analysed and underwent quality assessment using the Joanna Briggs Institute validated critical appraisal tool for qualitative research. RESULTS: Out of 2681 articles screened, 28 studies (n = 1573 participants) were eligible for inclusion. Five overarching themes emerged relating to personal, provider and systemic factors. Barriers to vaccine uptake included concerns about vaccine safety and efficacy, lack of knowledge about vaccines' benefits and necessity, fear of adverse effects on the foetus or mother and low perception of disease severity. Facilitators included recommendations from trusted healthcare providers, easy access to vaccination, clear communication on the benefits and safety of vaccination, and positive social influences from family and friends. Strategies for increasing vaccination uptake included strong and proactive vaccine recommendations by trusted healthcare professionals, provision of vaccines during routine antenatal care, and clear and consistent communication about vaccines addressing pregnant women's concerns. CONCLUSION: This review highlights the need for interventions that address the identified barriers to vaccine uptake among pregnant women. Recommendation from a healthcare provider can play a significant role in promoting vaccine uptake, as can clear risk/benefit communication and convenient access to vaccination. Addressing concerns about vaccine safety and providing accurate information about vaccines is also important.
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COVID-19 , Vaccination , Humans , Pregnancy , Female , Vaccination/psychology , COVID-19/prevention & control , Pregnant Women/psychology , COVID-19 Vaccines/administration & dosage , Influenza, Human/prevention & control , SARS-CoV-2 , Patient Acceptance of Health Care/psychology , Health Knowledge, Attitudes, Practice , Whooping Cough/prevention & control , Influenza Vaccines/administration & dosageABSTRACT
Background: Identifying clusters of co-occurring diseases may help characterise distinct phenotypes of Multiple Long-Term Conditions (MLTC). Understanding the associations of disease clusters with health-related outcomes requires a strategy to assign clusters to people, but it is unclear how the performance of strategies compare. Aims: First, to compare the performance of methods of assigning disease clusters to people at explaining mortality, emergency department attendances and hospital admissions over one year. Second, to identify the extent of variation in the associations with each outcome between and within clusters. Methods: We conducted a cohort study of primary care electronic health records in England, including adults with MLTC. Seven strategies were tested to assign patients to fifteen disease clusters representing 212 LTCs, identified from our previous work. We tested the performance of each strategy at explaining associations with the three outcomes over 1 year using logistic regression and compared to a strategy using the individual LTCs. Results: 6,286,233 patients with MLTC were included. Of the seven strategies tested, a strategy assigning the count of conditions within each cluster performed best at explaining all three outcomes but was inferior to using information on the individual LTCs. There was a larger range of effect sizes for the individual LTCs within the same cluster than there was between the clusters. Conclusion: Strategies of assigning clusters of co-occurring diseases to people were less effective at explaining health-related outcomes than a person's individual diseases. Furthermore, clusters did not represent consistent relationships of the LTCs within them, which might limit their application in clinical research.
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BACKGROUND: The World Health Organization's (WHO) Immunization Agenda 2030 emphasises ensuring equitable access to vaccination across the life course. This includes placing an emphasis on migrant populations who may have missed key childhood vaccines, doses, and boosters due to disrupted healthcare systems and the migration process, or differing vaccination schedules in home countries. Guidelines exist in the UK for offering catch-up vaccinations to adolscent and adult migrants with incomplete or uncertain vaccination status (including MMR, Td-IPV, MenACWY, HPV), but emerging evidence suggests awareness and implementation in primary care is poor. It is unclear whether patient-level barriers to uptake of catch-up vaccinations also exist. We explored experiences and views around catch-up vaccination among adult migrants from a range of backgrounds, to define strategies for improving catch-up vaccination policy and practice. METHODS: In-depth semi-structured interviews were carried out in two phases with adult migrant populations (refugees, asylum seekers, undocumented migrants, those with no recourse to public funds) on views and experiences around vaccination, involving a team of peer researchers from specific migrant communities trained through the study. In Phase 1, we conducted remote interviews with migrants resident in the UK for < 10 years, from diverse backgrounds. In Phase 2, we engaged specifically Congolese and Angolan migrants as part of a community-based participatory study. Topic guides were developed iteratively and piloted. Participants were recruited using purposive, opportunistic and snowball sampling methods. Interviews were conducted in English (interpreters offered), Lingala or French and were audio-recorded, transcribed and analysed using a thematic framework approach in NVivo 12. RESULTS: 71 participants (39 in Phase 1, 32 in Phase 2) were interviewed (Mean age 43.6 [SD:12.4] years, 69% female, mean 9.5 [SD:7] years in the UK). Aside from COVID-19 vaccines, most participants reported never having been offered vaccinations or asked about their vaccination history since arriving in the UK as adults. Few participants mentioned being offered specific catch-up vaccines (e.g. MMR/Td-IPV) when attending a healthcare facility on arrival in the UK. Vaccines such as flu vaccines, pregnancy-related or pre-travel vaccination were more commonly mentioned. In general, participants were not aware of adult catch-up vaccination but regarded it positively when it was explained. A few participants expressed concerns about side-effects, risks/inconveniences associated with access (e.g. links to immigration authorities, travel costs), preference for natural remedies, and hesitancy to engage in further vaccination campaigns due to the intensity of COVID-19 vaccination campaigns. Trust was a major factor in vaccination decisions, with distinctions noted within and between groups; some held a healthcare professional's recommendation in high regard, while others were less trusting towards the healthcare system because of negative experiences of the NHS and past experiences of discrimination, injustice and marginalisation by wider authorities. CONCLUSIONS: The major barrier to adult catch-up vaccination for missed routine immunisations and doses in migrant communities in the UK is the limited opportunities, recommendations or tailored vaccination information presented to migrants by health services. This could be improved with financial incentives for provision of catch-up vaccination in UK primary care, alongside training of healthcare professionals to support catch-up immunisation and raise awareness of existing guidelines. It will also be essential to address root causes of mistrust around vaccination, where it exists among migrants, by working closely with communities to understand their needs and meaningfully involving migrant populations in co-producing tailored information campaigns and culturally relevant interventions to improve coverage.
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Transients and Migrants , Vaccination Coverage , Vaccination , Humans , United Kingdom , Adult , Female , Male , Vaccination/psychology , Vaccination Coverage/statistics & numerical data , Middle Aged , Interviews as Topic , Young Adult , Refugees , COVID-19/prevention & controlABSTRACT
BACKGROUND: Health apps are increasingly recognized as crucial tools for enhancing health care delivery. Many countries, particularly those in sub-Saharan Africa, can substantially benefit from using health apps to support self-management and thus help to achieve universal health coverage and the third sustainable development goal. However, most health apps published in app stores are of unknown or poor quality, which poses a risk to patient safety. Regulatory standards and guidance can help address this risk and promote patient safety. OBJECTIVE: This review aims to assess the regulatory standards and guidance for health apps supporting evidence-based best practices in sub-Saharan Africa with a focus on self-management. METHODS: A methodological framework for scoping reviews was applied. A search strategy was built and applied across the following databases, gray literature sources, and institutional websites: PubMed, Scopus, World Health Organization (WHO) African Index Medicus, OpenGrey, WHO Regional Office for Africa Library, ICTworks, WHO Directory of eHealth policies, HIS Strengthening Resource Center, International Telecommunication Union, Ministry of Health websites, and Google. The search covered the period between January 2005 and January 2024. The findings were analyzed using a deductive descriptive content analysis. The policy analysis framework was adapted and used to organize the findings. The Reporting Items for Stakeholder Analysis tool guided the identification and mapping of key stakeholders based on their roles in regulating health apps for self-management. RESULTS: The study included 49 documents from 31 sub-Saharan African countries. While all the documents were relevant for stakeholder identification and mapping, only 3 regulatory standards and guidance contained relevant information on regulation of health apps. These standards and guidance primarily aimed to build mutual trust; promote integration, inclusion, and equitable access to services; and address implementation issues and poor coordination. They provided guidance on systems quality, software acquisition and maintenance, security measures, data exchange, interoperability and integration, involvement of relevant stakeholders, and equitable access to services. To enhance implementation, the standards highlight that legal authority, coordination of activities, building capacity, and monitoring and evaluation are required. A number of stakeholders, including governments, regulatory bodies, funders, intergovernmental and nongovernmental organizations, academia, and the health care community, were identified to play key roles in regulating health apps. CONCLUSIONS: Health apps have huge potential to support self-management in sub-Saharan Africa, but the lack of regulatory standards and guidance constitutes a major barrier. Hence, for these apps to be safely and effectively integrated into health care, more attention should be given to regulation. Learning from countries with effective regulations can help sub-Saharan Africa build a more robust and responsive regulatory system, ensuring the safe and beneficial use of health apps across the region. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1136/bmjopen-2018-025714.
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Self-Management , Humans , Databases, Factual , Government , Gray Literature , Africa South of the SaharaABSTRACT
BACKGROUND: Medication non-adherence is a notable contributor to healthcare inefficiency, resulting in poor medication management, impaired patient outcomes, and ineffective symptom control. AIM: To summarise interventions targeting medication adherence for adults with mental-physical multimorbidity in primary healthcare settings. DESIGN AND SETTING: A systematic review of the literature - published in any language and with any country of origin - was conducted. METHOD: MEDLINE, EMBASE, PsycInfo, Web of Science, Cochrane Library, and the Cumulated Index to Nursing and Allied Health Literature - more commonly known as CINAHL - were searched for relevant studies. Data were extracted and synthesised using narrative synthesis. The Effective Practice and Organisation of Care (EPOC) taxonomy was used to classify intervention types. Risk of bias was assessed using the National Heart, Lung, and Blood Institute's quality assessment tool for controlled intervention studies. RESULTS: Eleven studies, representing 2279 patients, were included. All interventions examined were classified into one EPOC domain, namely 'delivery arrangements'. All included studies examined patients who had a physical condition and depression. Seven studies examining interventions focused on coordination of care and management of care processes reported statistically significant improvements in medication adherence that were attributed to the intervention. Four studies considering the use of information and communication technology observed no changes in medication adherence. CONCLUSION: Interventions that coordinate and manage healthcare processes may help improve patients' adherence to medication regimes in those with mental-physical multimorbidity. However, it is still necessary to better understand how digital health technology can support patients in following their medication regimes. As the growing challenges of treating multimorbidity are faced, everyone involved in health services - from providers to policymakers - must be receptive to a more integrated approach to healthcare delivery.