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2.
Lancet Digit Health ; 4(9): e646-e656, 2022 09.
Article in English | MEDLINE | ID: covidwho-1967558

ABSTRACT

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 hypertension (yes or no); the area under the curve was 0·80 (95% CI 0·76-0·85) and on validation the negative predictive value of a low risk designation was 99% (95% CI 98·1-99·2; 1435 of 1453). RECAP-O2 included age (years), degree of breathlessness (two point scale), fatigue (two point scale), and SpO2 at rest (as a percentage); the area under the curve was 0·84 (0·78-0·90) and on validation the negative predictive value of low risk designation was 99% (95% CI 98·9-99·7; 1176 of 1183). INTERPRETATION: Both RECAP models are valid tools to assess COVID-19 patients in the community. RECAP-GP can be used initially, without need for observations, to identify patients who require monitoring. If the patient is monitored and SpO2 is available, RECAP-O2 is useful to assess the need for treatment escalation. FUNDING: Community Jameel and the Imperial College President's Excellence Fund, the Economic and Social Research Council, UK Research and Innovation, and Health Data Research UK.


Subject(s)
COVID-19 , Dyspnea , Female , Humans , Male , Primary Health Care , Prospective Studies , Risk Factors
3.
Emerg Med J ; 39(8): 575-582, 2022 Aug.
Article in English | MEDLINE | ID: covidwho-1788973

ABSTRACT

BACKGROUND: To 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. METHODS: We conducted a retrospective cohort study using a stepped wedge pre-implementation 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 PCR test result from 1 October 2020 to 3 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 with 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. RESULTS: 217 650 people were eligible and included in the analysis. Total enrolment onto the programme was low, with enrolment data received for only 5527 (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% to 18%) and emergency hospital admission (95% CI: 5% to 20%) and a 24% increase in the odds of critical care admission in those admitted (95% CI: 5% to 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. CONCLUSION: At 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 expected enrolment is likely to have diluted the effects of the programme at a population level.


Subject(s)
COVID-19 , COVID-19/epidemiology , Hospitalization , Humans , Oximetry , Patient Acceptance of Health Care , Retrospective Studies
4.
BMJ Qual Saf ; 2022 Mar 08.
Article in English | MEDLINE | ID: covidwho-1736078

ABSTRACT

BACKGROUND: The introduction of remote triage and assessment early in the pandemic raised questions about patient safety. We sought to capture patients and clinicians' experiences of the management of suspected acute COVID-19 and generate wider lessons to inform safer care. SETTING AND SAMPLE: UK primary healthcare. A subset of relevant data was drawn from five linked in-pandemic qualitative studies. The data set, on a total of 87 participants recruited via social media, patient groups and snowballing, comprised free text excerpts from narrative interviews (10 survivors of acute COVID-19), online focus groups (20 patients and 30 clinicians), contributions to a Delphi panel (12 clinicians) and fieldnotes from an online workshop (15 patients, clinicians and stakeholders). METHODS: Data were uploaded onto NVivo. Coding was initially deductive and informed by WHO and Institute of Medicine frameworks of quality and safety. Further inductive analysis refined our theorisation using a wider range of theories-including those of risk, resilience, crisis management and social justice. RESULTS: In the early weeks of the pandemic, patient safety was compromised by the driving logic of 'stay home' and 'protect the NHS', in which both patients and clinicians were encouraged to act in a way that helped reduce pressure on an overloaded system facing a novel pathogen with insufficient staff, tools, processes and systems. Furthermore, patients and clinicians observed a shift to a more transactional approach characterised by overuse of algorithms and decision support tools, limited empathy and lack of holistic assessment. CONCLUSION: Lessons from the pandemic suggest three key strategies are needed to prevent avoidable deaths and inequalities in the next crisis: (1) strengthen system resilience (including improved resourcing and staffing; support of new tools and processes; and recognising primary care's role as the 'risk sink' of the healthcare system); (2) develop evidence-based triage and scoring systems; and (3) address social vulnerability.

5.
J Telemed Telecare ; : 1357633X211066235, 2021 Dec 22.
Article in English | MEDLINE | ID: covidwho-1582815

ABSTRACT

INTRODUCTION: With 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. METHODOLOGY: An 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. RESULTS: Respondents (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 = 1802), safety (45.5%, n = 1822), patient-centredness (45.2%, n = 45.2) and equity (42.9%, n = 1726). Interest in future use was highest for telephone consultations (55.9%), patient-initiated digital services (56.1%), secure messaging systems (43.4%), online triage (35.1%), video consultations (37.0%) and chat consultations (30.1%), although significant variation was observed between countries and patient characteristics. DISCUSSION: Future work must examine the drivers and determinants of positive experiences using remote care to co-create a supportive environment that ensures equitable adoption and use. Comparative analysis between countries and health systems offers the opportunity for policymakers to learn from best practices internationally.

6.
BMJ Open ; 11(12): e047623, 2021 12 06.
Article in English | MEDLINE | ID: covidwho-1555294

ABSTRACT

OBJECTIVES: High-quality data are crucial for guiding decision-making and practising evidence-based healthcare, especially if previous knowledge is lacking. Nevertheless, data quality frailties have been exposed worldwide during the current COVID-19 pandemic. Focusing on a major Portuguese epidemiological surveillance dataset, our study aims to assess COVID-19 data quality issues and suggest possible solutions. SETTINGS: On 27 April 2020, the Portuguese Directorate-General of Health (DGS) made available a dataset (DGSApril) for researchers, upon request. On 4 August, an updated dataset (DGSAugust) was also obtained. PARTICIPANTS: All COVID-19-confirmed cases notified through the medical component of National System for Epidemiological Surveillance until end of June. PRIMARY AND SECONDARY OUTCOME MEASURES: Data completeness and consistency. RESULTS: DGSAugust has not followed the data format and variables as DGSApril and a significant number of missing data and inconsistencies were found (eg, 4075 cases from the DGSApril were apparently not included in DGSAugust). Several variables also showed a low degree of completeness and/or changed their values from one dataset to another (eg, the variable 'underlying conditions' had more than half of cases showing different information between datasets). There were also significant inconsistencies between the number of cases and deaths due to COVID-19 shown in DGSAugust and by the DGS reports publicly provided daily. CONCLUSIONS: Important quality issues of the Portuguese COVID-19 surveillance datasets were described. These issues can limit surveillance data usability to inform good decisions and perform useful research. Major improvements in surveillance datasets are therefore urgently needed-for example, simplification of data entry processes, constant monitoring of data, and increased training and awareness of healthcare providers-as low data quality may lead to a deficient pandemic control.


Subject(s)
COVID-19 , Data Accuracy , Humans , Pandemics , Research , SARS-CoV-2
7.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-295604

ABSTRACT

Background With the onset of COVID-19, primary care has swiftly transitioned from face-to-face to virtual care, yet it remains largely unknown how this has impacted on the quality and safety of care. Aim To evaluate patient use of virtual primary care models during COVID-19 in terms of change in uptake, perceived impact on the quality and safety of care, and willingness of future use. Design and setting An online cross-sectional survey was administered to the public across the United Kingdom, Sweden, Italy and Germany. Methods 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. Results Respondents (N=6,326) 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 (2.39±0.96 vs 2.29±0.92, P<.001), those with higher literacy (2.75±1.02 vs 2.29±0.92, P<.001), and participants from Germany (2.54±0.91, P<.001). Healthcare timeliness and efficiency were the quality dimensions most often reported as being positively impacted by virtual technologies (60.2%, n=2,793 and 55.7%, n=2,401, respectively), followed by effectiveness (46.5%, n=1,802), safety (45.5%, n=1,822), patient-centredness (45.2%, n=45.2) and equity (42.9%, n=1,726). Interest in future use was highest for telephone consultations (55.9%), followed by patient-initiated digital services (56.1%), secure messaging systems (43.4%), online triage (35.1%), video consultations (37.0%), and chat consultations (30.1%), although significant variation was observed between countries and patient characteristics. Conclusion Future work must examine the drivers and determinants of positive experiences using remote care to co-create a supportive environment that ensures equitable adoption and use across different patient groups. Comparative analysis between countries and health systems offers the opportunity for policymakers to learn from best practices internationally.

9.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-293222

ABSTRACT

Background: The Covid-19 case fatality ratio varies between countries and over time but it is unclear whether variation is explained by the underlying risk in those infected. This study aims to describe the trends and risk factors for admission and mortality rates over time in England. Methods In this retrospective cohort study, we included all adults (≥18 years) in England with a positive Covid-19 test result between 1st October 2020 and 30th April 2021. Data were linked to primary and secondary care electronic health records and death registrations. Our outcomes were i) one or more emergency hospital admissions and ii) death from any cause, within 28 days of a positive test. Multivariable multilevel logistic regression was used to model each outcome with patient risk factors and time. Results 2,311,282 people were included in the study, of whom 164,046 (7.1%) were admitted and 53,156 (2.3%) died within 28 days. There was significant variation in the case hospitalisation and mortality risk over time, peaking in December 2020-February 2021, which remained after adjustment for individual risk factors. Older age groups, males, those resident in more deprived areas, and those with obesity had higher odds of admission and mortality. Of risk factors examined, severe mental illness and learning disability had the highest odds of admission and mortality. Conclusions In one of the largest studies of nationally representative Covid-19 risk factors, case hospitalisation and mortality risk varied significantly over time in England during the second pandemic wave, independent of the underlying risk in those infected.

10.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-293221

ABSTRACT

Objectives: To 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. Design Retrospective cohort study using a stepped wedge pre- and post- implementation design. Setting All Clinical Commissioning Groups (CCGs) in England implementing a local CO@h programme. Participants 217,650 people with a positive covid-19 polymerase chain reaction test result and symptomatic, from 1st October 2020 to 3rd May 2021, aged ≥65 years or identified as clinically extremely vulnerable. Care home residents were excluded. Interventions A pre-intervention period before implementation of the CO@h programme in each CCG was compared to a post-intervention period after implementation. Main outcome measures Five outcome measures within 28 days of a positive covid-19 test: i) death from any cause;ii) any A&E attendance;iii) any emergency hospital admission;iv) critical care admission;and v) total length of hospital stay. Results Implementation of the programme was not associated with mortality or length of hospital stay. Implementation was associated with increased health service utilisation with a 12% increase in the odds of A&E 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. However, uptake of the programme was low, with enrolment data received for only 5,527 (2.5%) of the eligible population. Conclusions At a population level, there was no association with mortality following implementation of the CO@h programme, and small increases in health service utilisation were observed. Low enrolment of eligible people may have diluted the effects of the programme at a population level.

11.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-293220

ABSTRACT

Objectives: To identify the impact of a national pulse oximetry remote monitoring programme for covid-19 (COVID Oximetry @home;CO@h) on health service use and mortality in patients attending Accident and Emergency (A&E) departments. Design Retrospective matched cohort study of patients enrolled onto the CO@h pathway from A&E. Setting National Health Service (NHS) A&E departments in England. Participants All patients with a positive covid-19 test from 1st October 2020 to 3rd May 2021 who attended A&E from three days before to ten days after the date of the test. All patients who were admitted or died on the same or following day to the first A&E attendance within the time window were excluded. Interventions Participants enrolled onto CO@h were matched using demographic and clinical criteria to participants who were not enrolled. Main outcome measures Five outcome measures were examined within 28 days of first A&E attendance: i) death from any cause;ii) any subsequent A&E attendance;iii) any emergency hospital admission;iv) critical care admission;and v) length of stay. Results 15,621 participants were included in the primary analysis, of whom 639 were enrolled onto CO@h and 14,982 were controls. Odds of death were 52% lower in those enrolled (95% CI: 7%-75% lower) compared to those not enrolled on CO@h. Odds of any A&E attendance or admission were 37% (95% CI: 16-63%) and 59% (95% CI: 16-63%) higher, respectively, in those enrolled. Of those admitted, those enrolled had 53% (95% CI: 7%-76%) lower odds of critical care admission. There was no significant impact on length of stay. Conclusions These findings indicate that for patients assessed in A&E, pulse oximetry remote monitoring may be a clinically effective and safe model for early detection of hypoxia and escalation, leading to increased subsequent A&E attendance and admissions, and reduced critical care requirement and mortality.

12.
JMIR Res Protoc ; 10(10): e30083, 2021 Oct 05.
Article in English | MEDLINE | ID: covidwho-1450770

ABSTRACT

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 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. OBJECTIVE: 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. METHODS: After the data have 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 regression analyses to construct the model. We aim to recruit a minimum of 1317 patients for model development and validation. We will then externally validate the model on an independent dataset of 1400 patients. The model will also be applied for multiple different datasets to assess both its performance in different patient groups and its applicability for different methods of data collection. RESULTS: As of May 10, 2021, we have recruited 3732 patients. A further 2088 patients have been recruited through the National Health Service Clinical Assessment Service, and approximately 5000 patients have been recruited through the DoctalyHealth platform. CONCLUSIONS: The methodology for the development of the RECAP-V1 prediction model as well as the risk score will provide clinicians with a statistically robust tool to help prioritize COVID-19 patients. TRIAL REGISTRATION: ClinicalTrials.gov NCT04435041; https://clinicaltrials.gov/ct2/show/NCT04435041. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/30083.

13.
Br J Gen Pract ; 71(710): 425-426, 2021 09.
Article in English | MEDLINE | ID: covidwho-1448957
14.
Eur J Gen Pract ; 27(1): 241-247, 2021 Dec.
Article in English | MEDLINE | ID: covidwho-1371665

ABSTRACT

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. OBJECTIVES: 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 focussed 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 to better incorporate novel technologies into the modern primary care clinical environment.


Subject(s)
COVID-19 , Primary Health Care/methods , Telemedicine/methods , Developed Countries , Digital Technology/methods , Health Policy , Humans , Primary Health Care/trends , Telemedicine/trends
15.
JMIR Res Protoc ; 10(8): e30099, 2021 Aug 26.
Article in English | MEDLINE | ID: covidwho-1320564

ABSTRACT

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. OBJECTIVE: This study aims to explore the perspectives of general practitioners (GPs) and family doctors on the (1) use of virtual care during the COVID-19 pandemic, (2) perceived impact on quality and safety of care, and (3) essential factors for high-quality and sustainable use of virtual care in the future. METHODS: This study used an online cross-sectional questionnaire completed by GPs distributed across 20 countries. The survey was hosted in Qualtrics and distributed using email, social media, and the researchers' personal contact networks. GPs 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 analyzed using framework analysis. RESULTS: Data collection took place from June 2020 to September 2020. As of this manuscript's submission, a total of 1605 GP respondents participated in the questionnaire. Further data analysis is currently ongoing. CONCLUSIONS: 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 underlying factors that influence this adoption and perceptions, in both individual GP and family doctor characteristics and the context in which they work, will be provided. While the COVID-19 pandemic may prove the first great stress test of the capabilities, capacity, and robustness of digital systems currently in use, remote care will likely remain an increasingly common approach in the future. There is an imperative to identify the main lessons from this unexpected transformation and use them to inform policy decisions and health service design. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/30099.

16.
BMC Fam Pract ; 22(1): 96, 2021 05 17.
Article in English | MEDLINE | ID: covidwho-1232422

ABSTRACT

BACKGROUND: General 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. METHODS: A 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. RESULTS: Recommendations 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). CONCLUSIONS: We 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.


Subject(s)
COVID-19 , General Practice/organization & administration , Guidelines as Topic , Primary Health Care/organization & administration , Humans , Internationality
17.
JMIR Res Protoc ; 10(5): e29072, 2021 May 25.
Article in English | MEDLINE | ID: covidwho-1211771

ABSTRACT

BACKGROUND: During the pandemic, remote consultations have become the norm for assessing patients with signs and symptoms of COVID-19 to decrease the risk of transmission. This has intensified the clinical uncertainty already experienced by primary care clinicians when assessing patients with suspected COVID-19 and has prompted the use of risk prediction scores, such as the National Early Warning Score (NEWS2), to assess severity and guide treatment. However, the risk prediction tools available have not been validated in a community setting and are not designed to capture the idiosyncrasies of COVID-19 infection. OBJECTIVE: The objective of this study is to produce a multivariate risk prediction tool, RECAP-V1 (Remote COVID-19 Assessment in Primary Care), to support primary care clinicians in the identification of those patients with COVID-19 that are at higher risk of deterioration and facilitate the early escalation of their treatment with the aim of improving patient outcomes. METHODS: The study follows a prospective cohort observational design, whereby patients presenting in primary care with signs and symptoms suggestive of COVID-19 will be followed and their data linked to hospital outcomes (hospital admission and death). Data collection will be carried out by primary care clinicians in four arms: North West London Clinical Commissioning Groups (NWL CCGs), Oxford-Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC), Covid Clinical Assessment Service (CCAS), and South East London CCGs (Doctaly platform). The study involves the use of an electronic template that incorporates a list of items (known as RECAP-V0) thought to be associated with disease outcome according to previous qualitative work. Data collected will be linked to patient outcomes in highly secure environments. We will then use multivariate logistic regression analyses for model development and validation. RESULTS: Recruitment of participants started in October 2020. Initially, only the NWL CCGs and RCGP RSC arms were active. As of March 24, 2021, we have recruited a combined sample of 3827 participants in these two arms. CCAS and Doctaly joined the study in February 2021, with CCAS starting the recruitment process on March 15, 2021. The first part of the analysis (RECAP-V1 model development) is planned to start in April 2021 using the first half of the NWL CCGs and RCGP RSC combined data set. Posteriorly, the model will be validated with the rest of the NWL CCGs and RCGP RSC data as well as the CCAS and Doctaly data sets. The study was approved by the Research Ethics Committee on May 27, 2020 (Integrated Research Application System number: 283024, Research Ethics Committee reference number: 20/NW/0266) and badged as National Institute of Health Research Urgent Public Health Study on October 14, 2020. CONCLUSIONS: We believe the validated RECAP-V1 early warning score will be a valuable tool for the assessment of severity in patients with suspected COVID-19 in the community, either in face-to-face or remote consultations, and will facilitate the timely escalation of treatment with the potential to improve patient outcomes. TRIAL REGISTRATION: ISRCTN registry ISRCTN13953727; https://www.isrctn.com/ISRCTN13953727. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/29072.

19.
BMJ Open ; 10(11): e042626, 2020 11 12.
Article in English | MEDLINE | ID: covidwho-922577

ABSTRACT

BACKGROUND: To develop items for an early warning score (RECAP: REmote COVID-19 Assessment in Primary Care) for patients with suspected COVID-19 who need escalation to next level of care. METHODS: The study was based in UK primary healthcare. The mixed-methods design included rapid review, Delphi panel, interviews, focus groups and software development. Participants were 112 primary care clinicians and 50 patients recovered from COVID-19, recruited through social media, patient groups and snowballing. Using rapid literature review, we identified signs and symptoms which are commoner in severe COVID-19. Building a preliminary set of items from these, we ran four rounds of an online Delphi panel with 72 clinicians, the last incorporating fictional vignettes, collating data on R software. We refined the items iteratively in response to quantitative and qualitative feedback. Items in the penultimate round were checked against narrative interviews with 50 COVID-19 patients. We required, for each item, at least 80% clinician agreement on relevance, wording and cut-off values, and that the item addressed issues and concerns raised by patients. In focus groups, 40 clinicians suggested further refinements and discussed workability of the instrument in relation to local resources and care pathways. This informed design of an electronic template for primary care systems. RESULTS: The prevalidation RECAP-V0 comprises a red flag alert box and 10 assessment items: pulse, shortness of breath or respiratory rate, trajectory of breathlessness, pulse oximeter reading (with brief exercise test if appropriate) or symptoms suggestive of hypoxia, temperature or fever symptoms, duration of symptoms, muscle aches, new confusion, shielded list and known risk factors for poor outcome. It is not yet known how sensitive or specific it is. CONCLUSIONS: Items on RECAP-V0 align strongly with published evidence, clinical judgement and patient experience. The validation phase of this study is ongoing. TRIAL REGISTRATION NUMBER: NCT04435041.


Subject(s)
Checklist , Coronavirus Infections/diagnosis , Early Warning Score , Pneumonia, Viral/diagnosis , Telemedicine , Betacoronavirus , COVID-19 , Confusion , Coronavirus Infections/physiopathology , Delphi Technique , Disease Progression , Dyspnea , Fever , Heart Rate , Humans , Hypoxia , Myalgia , Pandemics , Pneumonia, Viral/physiopathology , Qualitative Research , Risk Assessment , Risk Factors , SARS-CoV-2 , Time Factors , United Kingdom
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