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Li E, Neves AL, 2023, Virtual primary care use during the COVID-19 pandemic, WHO Health Services Learning Hub (HLH), Publisher: World Health Organization (WHO)
This learning brief draws on findings derived from several publicly available peer-reviewed articles. For further details, please refer to the end of the brief. Prior to the onset of COVID-19, virtual primary care – a broad term describing the use of phone or digital technologies to enable primary care activities – was largely a nascent technology. While slowly increasing in availability over the years, virtual primary care had remained a complementary or alternative means to face-to-face consultations.The COVID-19 pandemic changed all that as it presented health systemsworldwide with a set of unprecedented challenges. Virtual approaches rapidly became the mainstay modality for health care delivery during the early phases of the pandemic, supporting continuity of care, facilitating public health interventions and disease surveillance, and curbing disease transmission in the community. This abrupt and rapid adoption of virtual primary care has had significantimplications on the care received by patients, the health provider’s routineclinical practice, and has pushed health systems towards greater incorporation of virtual primary care as an important means of care delivery, moving on from the pandemic.This briefing aims to summarize the key findings from the experiences of primary care physicians using virtual care tools. Using an online survey, we explored the perspectives of general practitioners working during the COVID-19 pandemic (June-September 2020) across 20 countries, and invited them to share their views on the main barriers and challenges of using virtual care
Teixeira F, Li E, Laranjo L, et al., 2023, Digital maturity and its determinants in General Practice: a cross- sectional study in 20 countries, Frontiers in Public Health, Vol: 10, Pages: 1-10, ISSN: 2296-2565
Background: The extent to which digital technologies are employed to promote the delivery of high-quality healthcare is known as Digital Maturity. Individual and systemic digital maturity are both necessary to ensure a successful, scalable and sustainable digital transformation in healthcare. However, digital maturity in primary care has been scarcely evaluated.Objectives: This study assessed the digital maturity in General Practice (GP) globally and evaluated its association with participants' demographic characteristics, practice characteristics and features of Electronic Health Records (EHRs) use.Methods: GPs across 20 countries completed an online questionnaire between June and September 2020. Demographic data, practice characteristics, and features of EHRs use were collected. Digital maturity was evaluated through a framework based on usage, resources and abilities (divided in this study in its collective and individual components), interoperability, general evaluation methods and impact of digital technologies. Each dimension was rated as 1 or 0. The digital maturity score was calculated as the sum of the six dimensions and ranged between 0 to 6 (maximum digital maturity). Multivariable linear regression was used to model the total score, while multivariable logistic regression was used to model the probability of meeting each dimension of the score.Results: One thousand six hundred GPs (61% female, 68% Europeans) participated. GPs had a median digital maturity of 4 (P25–P75: 3–5). Positive associations with digital maturity were found with: male gender [B = 0.18 (95% CI 0.01; 0.36)], use of EHRs for longer periods [B = 0.45 (95% CI 0.35; 0.54)] and higher frequencies of access to EHRs [B = 0.33 (95% CI 0.17; 0.48)]. Practicing in a rural setting was negatively associated with digital maturity [B = −0.25 (95%CI −0.43; −0.08)]. Usage (90%) was the most acknowledged dimension while interoperability (47%) and use of best practice gen
Clarke J, Beaney T, Alboksmaty A, et al., 2022, Identifying factors associated with enrolment into a national COVID-19 pulse oximetry remote monitoring programme in England: a retrospective observational study, The Lancet Digital Health, ISSN: 2589-7500
Background:Hypoxaemia is an important predictor of severity in patients with COVID-19 and may present without symptoms. The COVID-19 Oximetry @home (CO@h) programme was implemented across England from November 2020 providing pulse oximeters to higher risk people with COVID-19 to enable early detection of deterioration and escalation of care. However, the equity of access to the programme was unknown.Methods:This was a retrospective observational study. The proportion of patients enrolled onto CO@h programmes in the seven days before and 28 days after a positive COVID-19 test was calculated for each Clinical Commissioning Group (CCG) in England. Two-level hierarchical multivariable logistic regression with random intercepts for each CCG was run to identify factors predictive of being enrolled onto the CO@h programme. Findings:A total of 1,215,405 residents in 72 CCGs had a positive COVID-19 test between the date of programme implementation and the 3rd May 2021, of whom 19,932 (1·6%) were enrolled onto a CO@h programme. Of those enrolled, 14,441 (72·5%) were aged 50 years or more or were identified as clinically extremely vulnerable (CEV). Of all those aged 50 years or more or identified as CEV, 2·9% were enrolled. Higher odds of enrolment onto the CO@h programme were found in older patients, of non-White ethnicity, from more socioeconomically deprived areas, who were overweight (adjusted odds ratio (aOR) 1·31 [95% CI 1·26-1·37], p<0·001) or obese (aOR 1·69 [95% CI 1·63-1·77], p<0·001) or those identified as having a high-risk medical condition (aOR 1·58 [95% CI 1·51-1·65], p<0·001). Interpretation:Nationally, uptake of the CO@h programme was low with use of clinical judgement in determining eligibility. Preferential enrolment to the pulse oximetry monitoring programme was observed in people known to be at the highest risk of developing severe COVID-19. Fu
Fadahunsi KP, Wark PA, Mastellos N, et al., 2022, Assessment of clinical information quality in digital health technologies: an international eDelphi study, Journal of Medical Internet Research, Vol: 24, Pages: 1-10, ISSN: 1438-8871
Background:Digital health technologies (DHTs), such as electronic health records and prescribing systems, are transforming health care delivery around the world. The quality of information in DHTs is key to the quality and safety of care. We developed a novel clinical information quality (CLIQ) framework to assess the quality of clinical information in DHTs.Objective:This study explored clinicians’ perspectives on the relevance, definition, and assessment of information quality dimensions in the CLIQ framework.Methods:We used a systematic and iterative eDelphi approach to engage clinicians who had information governance roles or personal interest in information governance; the clinicians were recruited through purposive and snowball sampling techniques. Data were collected using semistructured online questionnaires until consensus was reached on the information quality dimensions in the CLIQ framework. Responses on the relevance of the dimensions were summarized to inform decisions on retention of the dimensions according to prespecified rules. Thematic analysis of the free-text responses was used to revise definitions and the assessment of dimensions.Results:Thirty-five clinicians from 10 countries participated in the study, which was concluded after the second round. Consensus was reached on all dimensions and categories in the CLIQ framework: informativeness (accuracy, completeness, interpretability, plausibility, provenance, and relevance), availability (accessibility, portability, security, and timeliness), and usability (conformance, consistency, and maintainability). A new dimension, searchability, was introduced in the availability category to account for the ease of finding needed information in the DHTs. Certain dimensions were renamed, and some definitions were rephrased to improve clarity.Conclusions:The CLIQ framework reached a high expert consensus and clarity of language relating to the information quality dimensions. The framework can be used b
Lear R, Freise L, Kybert M, et al., 2022, Perceptions of Quality of Care Among Users of a Web-Based Patient Portal: Cross-sectional Survey Analysis., J Med Internet Res, Vol: 24
BACKGROUND: Web-based patient portals enable patients access to, and interaction with, their personal electronic health records. However, little is known about the impact of patient portals on quality of care. Users of patient portals can contribute important insights toward addressing this knowledge gap. OBJECTIVE: We aimed to describe perceived changes in the quality of care among users of a web-based patient portal and to identify the characteristics of patients who perceive the greatest benefit of portal use. METHODS: A cross-sectional web-based survey study was conducted to understand patients' experiences with the Care Information Exchange (CIE) portal. Patient sociodemographic data were collected, including age, sex, ethnicity, educational level, health status, geographic location, motivation to self-manage, and digital health literacy (measured by the eHealth Literacy Scale). Patients with experience using CIE, who specified both age and sex, were included in these analyses. Relevant survey items (closed-ended questions) were mapped to the Institute of Medicine's 6 domains of quality of care. Users' responses were examined to understand their perceptions of how portal use has changed the overall quality of their care, different aspects of care related to the 6 domains of care quality, and patient's satisfaction with care. Multinomial logistic regression analyses were performed to identify patient characteristics associated with perceived improvements in overall care quality and greater satisfaction with care. RESULTS: Of 445 CIE users, 38.7% (n=172) reported that the overall quality of their care was better; 3.2% (n=14) said their care was worse. In the patient centeredness domain, 61.2% (273/445) of patients felt more in control of their health care, and 53.9% (240/445) felt able to play a greater role in decision-making. Regarding timeliness, 40.2% (179/445) of patients reported they could access appointments, diagnoses, and treatment more quickly. Approxi
Li E, Clarke J, Ashrafian H, et al., 2022, Impact of electronic health record interoperability on safety and quality of care in high-income countries: A systematic review, Journal of Medical Internet Research, Vol: 24, Pages: 1-15, ISSN: 1438-8871
Background: Electronic health records (EHR) and poor systems interoperability are well-known issues in the use of health information technologies worldwide in most high-income countries. Despite the abundance of literature exploring their relationship, its practical implications on patient safety and quality of care remain unclear.Objective: To examine how EHR interoperability affects patient safety, or other dimensions of care quality, in high-income healthcare settings. Methods: A systematic search was conducted using four online medical journal repositories and grey literature sources. Publications included were published in English between 2010-2022, pertaining to EHR use, interoperability, and patient safety or care quality in high-income settings. Screening was completed by three researchers in accordance with the Preferred Reporting Items for Systematic Reviews (PRISMA) guidelines. Risk of bias assessments was performed using the Risk Of Bias In Non-randomised Studies - of Interventions (ROBINS-I) and the Cochrane Risk of Bias 2 (RoB2) tools. Findings were presented as a narrative synthesis and mapped based on the Institute of Medicine’s framework for healthcare quality.Results: Twelve studies met the inclusion criteria to be included in our review. Findings were categorised into six common outcome measure categories: patient safety events, medication safety, data accuracy and errors, care effectiveness, productivity, and cost-savings. EHR interoperability was found to positively influence medication safety, reduce patient safety events, and lower costs. Improvements to time-savings and clinical workflow are mixed. However, true measures of effect are difficult to determine with certainty due to the heterogeneity in outcome measures used and notable variation in study quality.Conclusion: The benefits of EHR interoperability on the quality and safety of care remain unclear and reflect the extensive heterogeneity in the interventions, designs, and outcome
Espinosa-Gonzalez A, Prociuk D, Fiorentino F, et al., 2022, Remote COVID-19 assessment in primary care (RECAP) risk prediction tool: derivation and real-world validation studies, The Lancet Digital Health, Vol: 4, Pages: e646-e656, ISSN: 2589-7500
BACKGROUND: Accurate assessment of COVID-19 severity in the community is essential for patient care and requires COVID-19-specific risk prediction scores adequately validated in a community setting. Following a qualitative phase to identify signs, symptoms, and risk factors, we aimed to develop and validate two COVID-19-specific risk prediction scores. Remote COVID-19 Assessment in Primary Care-General Practice score (RECAP-GP; without peripheral oxygen saturation [SpO2]) and RECAP-oxygen saturation score (RECAP-O2; with SpO2). METHODS: RECAP was a prospective cohort study that used multivariable logistic regression. Data on signs and symptoms (predictors) of disease were collected from community-based patients with suspected COVID-19 via primary care electronic health records and linked with secondary data on hospital admission (outcome) within 28 days of symptom onset. Data sources for RECAP-GP were Oxford-Royal College of General Practitioners Research and Surveillance Centre (RCGP-RSC) primary care practices (development set), northwest London primary care practices (validation set), and the NHS COVID-19 Clinical Assessment Service (CCAS; validation set). The data source for RECAP-O2 was the Doctaly Assist platform (development set and validation set in subsequent sample). The two probabilistic risk prediction models were built by backwards elimination using the development sets and validated by application to the validation datasets. Estimated sample size per model, including the development and validation sets was 2880 people. FINDINGS: Data were available from 8311 individuals. Observations, such as SpO2, were mostly missing in the northwest London, RCGP-RSC, and CCAS data; however, SpO2 was available for 1364 (70·0%) of 1948 patients who used Doctaly. In the final predictive models, RECAP-GP (n=1863) included sex (male and female), age (years), degree of breathlessness (three point scale), temperature symptoms (two point scale), and presence of hypert
Li E, Neves AL, 2022, Lessons from remote antenatal care during the COVID-19 pandemic: how can we ensure equitable, safe, and patient-centred care?, BMJ Quality & Safety, ISSN: 2044-5415
Lear R, Freise L, Kybert M, et al., 2022, Patients’ willingness and ability to identify and respond to errors in their personal health records: a mixed methods analysis of cross-sectional survey data, Journal of Medical Internet Research, Vol: 24, ISSN: 1438-8871
Background:Errors in electronic health records are known to contribute to patient safety incidents, yet systems for checking the accuracy of patient records are almost non-existent. Personal health records, enabling patient access to, and interaction, with the clinical record, offer a valuable opportunity for patients to actively participate in error surveillance.Objective:The aim of this study was to evaluate patients’ willingness and ability to identify and respond to errors in their personal health records.Methods:A cross-sectional survey study was conducted using an online questionnaire. Patient sociodemographic data were collected, including age, gender, ethnicity, educational level, health status, geographical location, motivation to self-manage, and digital health literacy (measured by the eHEALS tool). Patients with experience of using the Care Information Exchange (CIE) portal, who specified both age and gender, were included in these analyses. Patients’ responses to four relevant survey items (closed-ended questions, some with space for free-text comments) were examined to understand their willingness and ability to identify and respond to errors in their personal health records. Multinomial logistic regression was used to identify patient characteristics that predict i) ability to understand information in CIE, and ii) willingness to respond to errors in their records. The Framework Method was used to derive themes from patients’ free-text responses.Results:Of 445 patients, 40.7% (n=181) “definitely” understood CIE information and around half (49.4%, n=220) understood CIE information “to some extent”. Patients with high digital health literacy (eHEALS score ≥30) were more confident in their ability to understand their records compared to patients with low digital health literacy (odds ratio (OR) 7.85, 95% confidence interval (CI) 3.04-20.29, P<.001). Information-related barriers (medical terminology; lack of
Lounsbury O, Roberts L, Kurek N, et al., 2022, The role of digital innovation in improving healthcare quality in extreme adversity: an interpretative phenomenological analysis study, Journal of Global Health Reports, ISSN: 2399-1623
Background: High quality is a necessary feature of healthcare delivery. These healthcare quality challenges are particularly present in areas of extreme adversity, such as in conflict settings or sustained humanitarian crises. Digital health technologies have recently emerged as an innovation to deliver care around the world in a variety of settings. However, there is little insight into how digital health technologies can be used to improve the quality of care where extreme adversity introduces unique challenges. Objective: This study aimed to identify where digital health technologies may be most impactful in improving the quality of care and evaluate opportunities for accelerated and meaningful digital innovation in adverse settings. Methods: A phenomenological approach (Interpretative Phenomenological Approach [IPA]), using semi-structured interviews, was adopted. Six individuals were interviewed in-person based on their expertise in global health, international care delivery, and application of digital health technologies to improve the quality of care in extreme adversity settings. The interviews were informed by a semi-structured topic guide with open-ended questions. The transcripts were compiled verbatim and were systematically examined by 2 reviewers, using the framework analysis method to extract themes and subthemes. Results: The participants identified several areas in which digital health technologies could be most impactful, which include engagement in care, continuity of care, workforce operations, and data collection. Opportunities for accelerated digital innovation include improving terminology, identity, ownership, and interoperability, identifying priority areas for digital innovation, developing tailored solutions, co-ordination and standardisation, and sustainability and resilience.Conclusions: These results suggest that there are conditions that favour or challenge the application of digital health technologies, even in specific areas in which
Li E, Tsopra R, Jimenez G, et al., 2022, General practitioners’ perceptions of using virtual primary care during the COVID-19 pandemic: An international cross-sectional survey study, PLOS Digital Health, Vol: 1, Pages: 1-23, ISSN: 2767-3170
With the onset of COVID-19, general practitioners (GPs) and patients worldwide swiftly transitioned from face-to-face to digital remote consultations. There is a need to evaluate how this global shift has impacted patient care, healthcare providers, patient and carer experience, and health systems. We explored GPs’ perspectives on the main benefits and challenges of using digital virtual care. GPs across 20 countries completed an online questionnaire between June–September 2020. GPs’ perceptions of main barriers and challenges were explored using free-text questions. Thematic analysis was used to analyse the data. A total of 1,605 respondents participated in our survey. The benefits identified included reducing COVID-19 transmission risks, guaranteeing access and continuity of care, improved efficiency, faster access to care, improved convenience and communication with patients, greater work flexibility for providers, and hastening the digital transformation of primary care and accompanying legal frameworks. Main challenges included patients’ preference for face-to-face consultations, digital exclusion, lack of physical examinations, clinical uncertainty, delays in diagnosis and treatment, overuse and misuse of digital virtual care, and unsuitability for certain types of consultations. Other challenges include the lack of formal guidance, higher workloads, remuneration issues, organisational culture, technical difficulties, implementation and financial issues, and regulatory weaknesses. At the frontline of care delivery, GPs can provide important insights on what worked well, why, and how during the pandemic. Lessons learned can be used to inform the adoption of improved virtual care solutions and support the long-term development of platforms that are more technologically robust and secure.
Beaney T, Neves AL, Alboksmaty A, et al., 2022, Trends and associated factors for Covid-19 hospitalisation and fatality risk in 2.3 million adults in England, Nature Communications, Vol: 13, Pages: 1-9, ISSN: 2041-1723
The Covid-19 mortality rate varies between countries and over time but the extent to which this is explained by the underlying risk in those infected is unclear. Using data on all adults in England with a positive Covid-19 test between 1st October 2020 and 30th April 2021 linked to clinical records, we examined trends and risk factors for hospital admission and mortality. Of 2,311,282 people included in the study, 164,046 (7.1%) were admitted and 53,156 (2.3%) died within 28 days of a positive Covid-19 test. We found significant variation in the case hospitalisation and mortality risk over time, which remained after accounting for the underlying risk of those infected. Older age groups, males, those resident in areas of greater socioeconomic deprivation, and those with obesity had higher odds of admission and death. People with severe mental illness and learning disability had the highest odds of admission and death. Our findings highlight both the role of external factors in Covid-19 admission and mortality risk and the need for more proactive care in the most vulnerable groups.
Beaney T, Clarke J, Alboksmaty A, et al., 2022, Population level impact of a pulse oximetry remote monitoring programme on mortality and healthcare utilisation in the people with COVID-19 in England: a national analysis using a stepped wedge design, Emergency Medicine Journal, Vol: 39, ISSN: 1472-0205
BackgroundTo identify the population level impact of a national pulse oximetry remote monitoring programme for COVID-19 (COVID Oximetry @home; CO@h) in England on mortality and health service use.MethodsWe conducted a retrospective cohort study using a stepped wedge pre- and post- implementation design, including all 106 Clinical Commissioning Groups (CCGs) in England implementing a local CO@h programme. All symptomatic people with a positive COVID-19 polymerase chain reaction test result from 1st October 2020 to 3rd May 2021, and who were aged ≥65 years or identified as clinically extremely vulnerable were included. Care home residents were excluded. A pre-intervention period before implementation of the CO@h programme in each CCG was compared to a post-intervention period after implementation. Five outcome measures within 28 days of a positive COVID-19 test: i) death from any cause; ii) any ED attendance; iii) any emergency hospital admission; iv) critical care admission; and v) total length of hospital stay.Results217,650 people were eligible and included in the analysis. Total enrolment onto the programme was low, with enrolment data received for only 5,527 (2.5%) of the eligible population. The period of implementation of the programme was not associated with mortality or length of hospital stay. The period of implementation was associated with increased health service utilisation with a 12% increase in the odds of ED attendance (95% CI: 6%-18%) and emergency hospital admission (95% CI: 5%-20%) and a 24% increase in the odds of critical care admission in those admitted (95% CI: 5%-47%). In a secondary analysis of CO@h sites with at least 10% or 20% of eligible people enrolled, there was no significant association with any outcome measure. ConclusionAt a population level, there was no association with mortality before and after the implementation period of the CO@h programme, and small increases in health service utilisation were observed. However, lower than
Alboksmaty A, Beaney T, Elkin S, et al., 2022, Effectiveness and safety of pulse oximetry in remote patient monitoring of patients with COVID-19: a systematic review, The Lancet Digital Health, Vol: 4, Pages: e279-e289, ISSN: 2589-7500
The COVID-19 pandemic has led health systems to increase the use of tools for monitoring and triaging patients remotely. This study aims to assess the effectiveness and safety of pulse oximetry in Remote Patient Monitoring (RPM) of COVID-19 patients at home. We conducted a systematic review, searching five databases, Medline, Embase, Global Health, medRxiv, and bioRxiv, from inception to April 15, 2021. We included feasibility studies, clinical trials, observational studies, including preprints. We found 561 studies, of which 13 were included in our synthesis. The final studies were all observational cohorts and involved a total of 2,908 participants. A meta-analysis was not feasible due to the heterogeneity of the outcomes reported in the included studies. Our review confirmed the safety and potential of using pulse oximetry in monitoring COVID-19 patients at home. It can potentially save hospital resources for those who may benefit most from care escalation. However, we could not identify explicit evidence on the impact on health outcomes compared with other monitoring models that have not used pulse oximetry. Based on our findings, we make 11 recommendations and three measures for setting up an RPM system using pulse oximetry.
van Dael J, Gillespie A, Neves AL, et al., 2022, Patient–clinician communication research for 21st century health care, British Journal of General Practice, Vol: 72, Pages: 52-53, ISSN: 0960-1643
Neves AL, van Dael J, O'Brien N, et al., 2021, Use and impact of virtual primary care on quality and safety: The public's perspectives during the COVID-19 pandemic, Journal of Telemedicine and Telecare, ISSN: 1357-633X
IntroductionWith the onset of Coronavirus disease (COVID-19), primary care has swiftly transitioned from face-to-face to virtual care, yet it remains largely unknown how this has impacted the quality and safety of care. We aim to evaluate patient use of virtual primary care models during COVID-19, including change in uptake, perceived impact on the quality and safety of care and willingness of future use.MethodologyAn online cross-sectional survey was administered to the public across the United Kingdom, Sweden, Italy and Germany. McNemar tests were conducted to test pre- and post-pandemic differences in uptake for each technology. One-way analysis of variance was conducted to examine patient experience ratings and perceived impacts on healthcare quality and safety across demographic characteristics.ResultsRespondents (n = 6326) reported an increased use of telephone consultations ( + 6.3%, p < .001), patient-initiated services ( + 1.5%, n = 98, p < 0.001), video consultations ( + 1.4%, p < .001), remote triage ( + 1.3, p < 0.001) and secure messaging systems ( + 0.9%, p = .019). Experience rates using virtual care technologies were higher for men (2.4 ± 1.0 vs. 2.3 ± 0.9, p < .001), those with higher literacy (2.8 ± 1.0 vs. 2.3 ± 0.9, p < .001), and participants from Germany (2.5 ± 0.9, p < .001). Healthcare timeliness and efficiency were the dimensions most often reported as being positively impacted by virtual technologies (60.2%, n = 2793 and 55.7%, n = 2,401, respectively), followed by effectiveness (46.5%, n =
Costa-Santos C, Neves AL, Correia R, et al., 2021, COVID-19 surveillance data quality issues: a national consecutive case series, BMJ OPEN, Vol: 11, ISSN: 2044-6055
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Neves AL, Smalley K, Freise L, et al., 2021, Sharing electronic health records with patients: Who is using the Care Information Exchange portal? A cross-sectional study, Jornal of Medical Internet Research, Vol: 13, Pages: 1-12, ISSN: 1438-8871
Background: Sharing electronic health records with patients has been shown to improve patient safety and quality of care, and patient portals represent a powerful and convenient tool to enhance patient access to their own healthcare data. However, the success of patient portals will only be possible through sustained adoption by its end-users: the patients. A better understanding of the characteristics of users and non-users is critical to understand which groups remain underserved or excluded from using such tools.Objective: To identify the determinants of usage of the Care Information Exchange (CIE), a shared patient portal program in the United Kingdom.Methods: A cross-sectional study was conducted, using an online questionnaire. Information collected included age, gender, ethnicity, educational level, health status, postcode and digital literacy. Registered individuals were defined as having had an account created in the portal, independent of their actual use of the platform; users were defined as having ever used the portal. Multivariate logistic regression was used to model the probability of being a user. Statistical analysis was performed in R, and Tableau ® was used to create maps of the proportion of CIE users by postcode area.Results: A total of 1,083 subjects replied to the survey (+186% of the estimated minimum target sample). The proportion of users was 61.6% (n=667), and within these, the majority (57.7%, n=385) used the portal at least once a month. To characterise the users and non-users of the system, we performed a sub-analysis of the sample, including only participants that had provided at least information regarding gender and age category. The sub-analysis included 650 individuals (59.8% women, 84.8% over 40 years). The majority of the subjects were white (76.6%, n=498), resident in London (64.7%, n=651), and lived in North West London (55.9%, n=363). Individuals with a higher educational degree (undergraduate/professional or postgraduat
Shaw A, O'Brien N, Flott K, et al., 2021, How to improve patient safety in fragile, conflict-affected, and vulnerable settings: a Delphi study protocol, BMJ Open, Vol: 11, Pages: 1-5, ISSN: 2044-6055
Introduction There is a high burden of adverse events and poor outcomes in fragile, conflict-affected and vulnerable (FCV) settings. To improve outcomes, there is a need to better identify which interventions can improve patient safety in these settings, as well as to develop strategies to optimise their implementation.Objective This study intends to generate a consensus on the most relevant patient safety interventions from experts with experience on FCV settings, including frontline clinicians and managers/administrators, non-governmental organisations, policymakers and researchers.Methods and analysis The study uses an online Delphi research approach (eDelphi). Participants will include experts from a range of backgrounds, including those working in a variety of FCV settings. Participants will be established contacts known to the research team or recruited via snowball sampling, and will be asked to identify and rank the importance of a variety of patient safety interventions. Consensus will be defined as >70% of participants agreeing/strongly agreeing or disagreeing/strongly disagreeing with a statement. Data analysis will be completed in Microsoft Excel and NVivo. The primary outcome of the study will be a list of the most relevant and applicable patient safety interventions for FCV settings.Ethics and dissemination The study has received approval from Imperial College London Ethics Committee (reference number 20IC665). Anonymous results will be made available to the public, academic organisations and policymakers.
Fiorentino F, Prociuk D, Espinosa Gonzalez AB, et al., 2021, An early warning risk prediction tool (RECAP-V1) for patients diagnosed with COVID-19: the protocol for a statistical analysis plan, JMIR Research Protocols, Vol: 10, ISSN: 1929-0748
Background:Since the start of the Covid-19 pandemic efforts have been made to develop early warning risk scores to help clinicians decide which patient is likely to deteriorate and require hospitalisation. The RECAP (Remote COVID Assessment in Primary Care) study investigates the predictive risk of hospitalisation, deterioration, and death of patients with confirmed COVID-19, based on a set of parameters chosen through a Delphi process done by clinicians. The study aims to use rich data collected remotely through the use of electronic data templates integrated in the electronic health systems of a number of general practices across the UK to construct accurate predictive models that will use pre-existing conditions and monitoring data of a patient’s clinical parameters such as blood oxygen saturation to make reliable predictions as to the patient’s risk of hospital admission, deterioration, and death.Objective:We outline the statistical methods to build the prediction model to be used in the prioritisation of patients in the primary care setting. The statistical analysis plan for the RECAP study includes as primary outcome the development and validation of the RECAP-V1 prediction model. Such prediction model will be adapted as a three-category risk score split into red (high risk), amber (medium risk), and green (low risk) for any patient with suspected covid-19. The model will predict risk of deterioration, hospitalisation, and death.Methods:After the data has been collected, we will assess the degree of missingness and use a combination of traditional data imputation using multiple imputation by chained equations, as well as more novel machine learning approaches to impute the missing data for the final analysis. For predictive model development we will use multiple logistic regressions to construct the model on a training dataset, as well as validating the model on an independent dataset. The model will also be applied for multiple different datasets
Fiorentino F, Prociuk D, Espinosa Gonzalez AB, et al., 2021, An Early Warning Risk Prediction Tool (RECAP-V1) for Patients Diagnosed With COVID-19: Protocol for a Statistical Analysis Plan, JMIR Research Protocols, Vol: 10, Pages: e30083-e30083
<jats:sec> <jats:title>Background</jats:title> <jats:p>Since the start of the COVID-19 pandemic, efforts have been made to develop early warning risk scores to help clinicians decide which patient is likely to deteriorate and require hospitalization. The RECAP (Remote COVID-19 Assessment in Primary Care) study investigates the predictive risk of hospitalization, deterioration, and death of patients with confirmed COVID-19, based on a set of parameters chosen through a Delphi process performed by clinicians. We aim to use rich data collected remotely through the use of electronic data templates integrated in the electronic health systems of several general practices across the United Kingdom to construct accurate predictive models. The models will be based on preexisting conditions and monitoring data of a patient’s clinical parameters (eg, blood oxygen saturation) to make reliable predictions as to the patient’s risk of hospital admission, deterioration, and death.</jats:p> </jats:sec> <jats:sec> <jats:title>Objective</jats:title> <jats:p>This statistical analysis plan outlines the statistical methods to build the prediction model to be used in the prioritization of patients in the primary care setting. The statistical analysis plan for the RECAP study includes the development and validation of the RECAP-V1 prediction model as a primary outcome. This prediction model will be adapted as a three-category risk score split into red (high risk), amber (medium risk), and green (low risk) for any patient with suspected COVID-19. The model will predict the risk of deterioration and hospitalization.</jats:p> </jats:sec> <jats:sec> <jats:title>Methods</jats:title> <jats:p>After the data have been collected, we will assess the degree of missingness and use a combination
Neves AL, Jacome C, Taveira-Gomes T, et al., 2021, Determinants of the use of health and fitness mobile apps by patients with asthma: secondary analysis of observational studies, Journal of Medical Internet Research, Vol: 23, Pages: 1-14, ISSN: 1438-8871
Background:Health and fitness apps have potential benefits to improve self-management and disease control among patients with asthma. However, inconsistent use rates have been reported across studies, regions, and health systems. A better understanding of the characteristics of users and nonusers is critical to design solutions that are effectively integrated in patients’ daily lives, and to ensure that these equitably reach out to different groups of patients, thus improving rather than entrenching health inequities.Objective:This study aimed to evaluate the use of general health and fitness apps by patients with asthma and to identify determinants of usage.Methods:A secondary analysis of the INSPIRERS observational studies was conducted using data from face-to-face visits. Patients with a diagnosis of asthma were included between November 2017 and August 2020. Individual-level data were collected, including age, gender, marital status, educational level, health status, presence of anxiety and depression, postcode, socioeconomic level, digital literacy, use of health services, and use of health and fitness apps. Multivariate logistic regression was used to model the probability of being a health and fitness app user. Statistical analysis was performed in R.Results:A total of 526 patients attended a face-to-face visit in the 49 recruiting centers and 514 had complete data. Most participants were ≤40 years old (66.4%), had at least 10 years of education (57.4%), and were in the 3 higher quintiles of the socioeconomic deprivation index (70.1%). The majority reported an overall good health status (visual analogue scale [VAS] score>70 in 93.1%) and the prevalence of anxiety and depression was 34.3% and 11.9%, respectively. The proportion of participants who reported using health and fitness mobile apps was 41.1% (n=211). Multivariate models revealed that single individuals and those with more than 10 years of education are more likely to use health and fitne
Neves AL, Li E, Serafini A, et al., 2021, Evaluating the impact of COVID-19 on the adoption of virtual care in general practice in 20 countries (inSIGHT): rationale and study protocol, Journal of Medical Internet Research, Vol: 10, Pages: 1-9, ISSN: 1438-8871
Background: In recent decades, virtual care has emerged as a promising option to support primary care delivery. However, despite the potential, adoption rates remained low. With the outbreak of COVID-19, it has suddenly been pushed to the forefront of care delivery. As we progress into the second year of the COVID-19 pandemic, there is a need and opportunity to review the impact remote care had in primary care settings and reassess its potential future role. This study aims to explore the perspectives of General Practitioners (GPs) / Family Doctors on a.) use of virtual care during the COVID-19 pandemic; b.) perceived impact on quality and safety of care; c.) essential factors for high-quality and sustainable use of virtual care in the future. Methods: Online cross-sectional questionnaire of GPs, distributed across 20 countries. The survey was hosted in Qualtrics and distributed using email, social media, and the researchers’ personal contact networks. General Practitioners were eligible for the survey if they were working mainly in primary care during the period of the COVID-19 pandemic. Descriptive statistical analysis will be performed for quantitative variables, and relationships between the use of virtual care and perceptions on impact on quality and safety of care, and participants’ characteristics, may be explored. Qualitative data (free-text responses) will be analysed using framework analysis. Results: Data collection took place from June to September 2020. As of this manuscript’s submission, a total of 1,605 GP respondents participated in the questionnaire. Further data analysis is currently ongoing. Discussion: The study will provide a comprehensive overview of the availability of virtual care technologies, perceived impact on quality and safety of care and essential factors for high-quality future use. In addition, a description of the under
Neves AL, Li E, Gupta PP, et al., 2021, Virtual primary care in high-income countries during the COVID-19 pandemic: policy responses and lessons for the future, European Journal of General Practice, Vol: 27, Pages: 241-247, ISSN: 1381-4788
Background: Telemedicine, once defined merely as the treatment of certain conditions remotely, has now often been supplanted in use by broader terms such as ‘virtual care’, in recognition of its increasing capability to deliver a diverse range of healthcare services from afar. With the unexpected onset of COVID-19, virtual care (e.g., telephone, video, online) has become essential to facilitating the continuation of primary care globally. Over several short weeks, existing healthcare policies have adapted quickly and empowered clinicians to use digital means to fulfil a wide range of clinical responsibilities which until then, have required face-to-face consultations. Objective: This paper aims to explore the virtual care policies and guidance material published during the initial months of the pandemic and examine their potential limitations and impact on transforming the delivery of primary care in high-income countries. Methods: A rapid review of publicly available national policies guiding the use of virtual care in General Practice was conducted. Documents were included if issued in the first six months of the pandemic (March to August of 2020) and focused primarily on high-income countries. Documents must have been issued by a national health authority, accreditation body, or professional organisation, and directly refer to the delivery of primary care. Results: We extracted six areas of relevance: primary care transformation during COVID-19, the continued delivery of preventative care, the delivery of acute care, remote triaging, funding & reimbursement, and security standards.Conclusion: Virtual care use in primary care saw a transformative change during the pandemic. However, despite the advances in the various governmental guidance offered, much work remains in addressing the shortcomings exposed during COVID-19 and strengthening viable policies so as to better incorporate novel technologies into the modern primary care clinical
Neves AL, Pereira Rodrigues P, Mulla A, et al., 2021, Using electronic health records to develop and validate a machine learning tool to predict type 2 diabetes outcomes: a study protocol, BMJ Open, Vol: 11, Pages: 1-5, ISSN: 2044-6055
Introduction: Type 2 diabetes (T2DM) is a major cause of blindness, kidney failure, myocardial infarction, stroke and lower limb amputation. We are still unable, however, to accurately predict or identify which patients are at a higher risk of deterioration. Most risk stratification tools do not account for novel factors such as socio-demographic determinants, self-management ability, or access to healthcare. Additionally, most tools are based in clinical trials, with limited external generalisability.Objective: The aim of this work is to design and validate a machine learning-based tool to identify patients with T2DM at high risk of clinical deterioration, based on a comprehensive set of patient level characteristics retrieved from a population health linked dataset.Sample and design: Retrospective cohort study of patients with diagnosis of T2DM on Jan 1st, 2015, with a 5-year follow-up. Anonymised electronic health care records from the Whole System Integrated Care (WSIC) database will be used. Preliminary outcomes: Outcome variables of clinical deterioration will include retinopathy, chronic renal disease, myocardial infarction, stroke, peripheral arterial disease, or death. Predictor variables will include sociodemographic and geographic data, patients’ ability to self-manage disease, clinical and metabolic parameters and healthcare service usage. Prognostic models will be defined using multi-dependence Bayesian networks (BN). The derivation cohort, comprising 80% of the patients, will be used to define the prognostic models. Model parameters will be internally validated by comparing the area under the receiver operating characteristic (ROC) curve (AUC) in the derivation cohort with those calculated from a leave-one-out and a 10 times 2-fold cross-validation. Ethics and dissemination: The study has received approvals from the Information Governance Committee at the Whole Systems Integrated Care. Results will be made available to people with type 2 diabetes
Shaw A, O'Brien N, Flott K, et al., 2021, The urgent need to identify and evaluate patient safety interventions in fragile, conflict-affected and vulnerable settings, Journal of Global Health, Vol: 11, ISSN: 2047-2978
Li E, Clarke J, Neves AL, et al., 2021, Electronic health records, interoperability, and patient safety in health systems of high-income countries: a systematic review protocol, BMJ Open, Vol: 11, ISSN: 2044-6055
Introduction The availability and routine use of electronic health records (EHRs) have become commonplace in healthcare systems of many high-income countries. While there is an ever-growing body ofliterature pertaining to EHR use, evidence surrounding the importance of EHR interoperability and its impact on patient safety remains less clear. There is therefore a need and opportunity to evaluate the evidence available regarding this relationship so as to better inform health informatics development and policies in the years to come. This systematic review aims to evaluate the impact of EHR interoperability on patient safety in health systems of high-income countries. Methods and analysis A systematic literature review will be conducted via a computerised search through four databases: PubMed, Embase, HMIC, and PsycInfo for relevant articles published between 2010 and 2020. Outcomes of interest will include: impact on patient safety, and the broader effects on health systems. Quality of the randomised quantitative studies will be assessed using Cochrane Risk of Bias Tool. Non-randomised papers will be evaluated with the Risk of Bias In Non Randomised Studies - of Interventions (ROBINS-I) tool. Drummond’s Checklist will be utilised for publications pertaining to economic evaluation. The National Institute for Health and Care Excellence (NICE) quality appraisal checklist will be used to assess qualitative studies. A narrative synthesis will be conducted for included studies, and the body of evidence will be summarised in a summary of findings table. Ethics and dissemination This review will summarise published studies with non-identifiable data and thus does not require ethical approval. Findings will be disseminated through preprints, open access peer reviewed publication, and conference presentations
Tsopra R, Frappe P, Streit S, et al., 2021, Reorganisation of GP surgeries during the COVID-19 outbreak: analysis of guidelines from 15 countries, BMC Family Practice, Vol: 22, Pages: 1-16, ISSN: 1471-2296
BackgroundGeneral practitioners (GPs) play a key role in managing the COVID-19 outbreak. However, they may encounter difficulties adapting their practices to the pandemic. We provide here an analysis of guidelines for the reorganisation of GP surgeries during the beginning of the pandemic from 15 countries.MethodsA network of GPs collaborated together in a three-step process: (i) identification of key recommendations of GP surgery reorganisation, according to WHO, CDC and health professional resources from health care facilities; (ii) collection of key recommendations included in the guidelines published in 15 countries; (iii) analysis, comparison and synthesis of the results.ResultsRecommendations for the reorganisation of GP surgeries of four types were identified: (i) reorganisation of GP consultations (cancelation of non-urgent consultations, follow-up via e-consultations), (ii) reorganisation of GP surgeries (area partitioning, visual alerts and signs, strict hygiene measures), (iii) reorganisation of medical examinations by GPs (equipment, hygiene, partial clinical examinations, patient education), (iv) reorganisation of GP staff (equipment, management, meetings, collaboration with the local community).ConclusionsWe provide here an analysis of guidelines for the reorganisation of GP surgeries during the beginning of the COVID-19 outbreak from 15 countries. These guidelines focus principally on clinical care, with less attention paid to staff management, and the area of epidemiological surveillance and research is largely neglected. The differences of guidelines between countries and the difficulty to apply them in routine care, highlight the need of advanced research in primary care. Thereby, primary care would be able to provide recommendations adapted to the real-world settings and with stronger evidence, which is especially necessary during pandemics.
Espinosa-Gonzalez AB, Neves AL, Fiorentino F, et al., 2021, Predicting Risk of Hospital Admission in Patients With Suspected COVID-19 in a Community Setting: Protocol for Development and Validation of a Multivariate Risk Prediction Tool, JMIR RESEARCH PROTOCOLS, Vol: 10, ISSN: 1929-0748
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van Dael J, Neves AL, Painter A, et al., 2021, Patient perspectives on the use of digital health services at a multi-site hospital in North-West London: a quantitative content analysis (Preprint), Journal of Medical Internet Research, ISSN: 1438-8871
Background:Following a large increase in the adoption of digital health amidst the COVID-19 crisis, there is increasing policy interest in the longer-term implementation of digital health services. Yet, there is still much unknown about the inherent quality of remote digital care, and research on patient perspectives remains comparatively small. Widespread usage amidst COVID-19 presents an important opportunity to better understand patients’ first-hand experiences with using these technologies.Objective:This study examined patients’ perspectives on main benefits and concerns with using digital health services in a large multi-site teaching hospital in North-West London during the COVID-19 crisis.Methods:Qualitative data was obtained from a larger questionnaire conducted during the COVID-19 pandemic on Care Information Exchange, which represents the largest patient-facing electronic health records in the English National Health Service. All responses were analysed using the framework analysis method. Quantitative content analysis was performed by mapping frequencies of reported themes across the respondent population.Results:Of all 6,766 respondents, 25.1% reported to have no concerns with digital health services, compared to 3.0% reporting no benefits. Reported benefits included: ease of access (37.1%), feeling empowered and informed (23.2%), improved timeliness of access and treatment (18.6%), healthcare capacity (11.5%), and care continuity amidst COVID-19 (7.4%). In contrast, reported concerns included issues around data security and privacy (17.5%), clinical uncertainty (17.0%), impact on patient-doctor relationship (11.9%), inequity in access and use (11.8%), misunderstanding health information (6.3%), and digital maturity (3.8%).Conclusions:Patients report many benefits with digital health services beyond immediate COVID-19 support, including improved access, timeliness, and enhanced healthcare capacity. Yet, some concerns remain, including some le
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