key: cord-342974-g6ltr6am authors: Hull, S. A.; Williams, C.; Ashworth, M.; Carvalho, C.; Boomla, K. title: Suspected COVID-19 in primary care: how GP records contribute to understanding differences in prevalence by ethnicity. date: 2020-05-26 journal: nan DOI: 10.1101/2020.05.23.20101741 sha: doc_id: 342974 cord_uid: g6ltr6am Abstract Background The first wave of the London COVID-19 epidemic peaked in April 2020. Attention initially focussed on severe presentations, intensive care capacity, and the timely supply of equipment. General practice has seen a rapid take up of technology to allow virtual consultations, enabling the management of mild and moderate community cases. Aim To quantify the prevalence and time-course of suspected COVID-19 presenting to general practices during the London epidemic. To report disease prevalence by ethnic group, and explore how far differences by ethnicity can be explained by data in the electronic health record (EHR). Design and Setting Cross-sectional study using anonymised data from the primary care records of 1.3 million people registered with 157 practices in four adjacent east London clinical commissioning groups (CCGs). The study area includes 48% of people from ethnic minorities and is in the top decile of social deprivation in England. Method Suspected COVID-19 cases were identified using SNOMED codes. Explanatory variables included age, gender, self-reported ethnicity and measures of social deprivation. Clinical factors included 16 long-term conditions, latest body mass index and smoking status. Results There were 8,985 suspected COVID-19 cases. Ethnicity recording was 78% complete. Univariate analysis showed a two-fold increase in odds of infection for South Asian and Black adults compared to White. In a fully adjusted analysis, including clinical factors, the odds were: South Asian OR 1.93 (95% CI = 1.83 to 2.04) Black OR 1.47 (95% CI 1.38 to 1.57) Conclusions Using data in GP records Black and south Asian ethnicity remain as predictors of community cases of COVID-19, with levels of risk similar to hospital admission cases. Further understanding of these differences requires social and occupational data. The rapid worldwide spread of COVID-19 in early 2020, from its origin in Wuhan China, (1) led the World Health Organisation to declare a pandemic on 11 March 2020. (2) In the UK early attention focussed on hospital presentations and intensive care capacity, the timely supply of equipment, and latterly the increasing death rate in care home settings. (3) (4) (5) Community testing -which forms part of standard public health test and quarantine policy -ceased in England on 12 March, (6) hence the extent of asymptomatic and milder symptomatic cases within community settings remains unknown. Early evidence from testing among passengers on cruise ships, (7) suggests that 18% of infected people have no symptoms. The figures are likely to be higher in populations with a younger demographic profile. Up to mid-April 2020 London has had the highest age standardised mortality rate for deaths in the the OpenSAFELY study indicate that mortality rates in the most deprived areas of England were almost twice as high as those in the least deprived areas, and that males had higher death rates than females. (8, 9) From an early stage in the UK epidemic people with COVID-19 like symptoms were advised not to attend their general practice in person, and to use online or phone contact with NHS 111. (10) Throughout general practice there was rapid take up of technological solutions to facilitate a shift to telephone and video consultations, which enabled GPs to manage community cases -despite the national failure to share COVID-19 test results offered by drive-through or home-based tests. (11, 12) Practices worked collectively to provide separate locations for the necessary physical examinations of people with suspected COVID-19 cases and for those with other medical problems. (13) Concern has been raised about the higher case fatality rate of Black, Asian, and minority ethnic (BAME) patients in intensive care units (14) and the disproportionate numbers of deaths of health and social care workers from these groups. The population of east London includes 48% of people from minority ethnic backgrounds. Hence this geographical area is well placed to examine whether Black and south Asian populations are . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted May 26, 2020. . https://doi.org/10.1101/2020.05.23.20101741 doi: medRxiv preprint over-represented in the population consulting their GP practice with suspected COVID-19 symptoms, and to explore health related causes of these differences. a) To identify the numbers of clinically suspected COVID-19 cases recorded by practices through the peak of the London epidemic in February to end of April 2020. b) To examine whether there is an excess of clinically suspected cases among the major ethnic minority groups, and how far this can be accounted for by differences in demographic status, or by differences in the burden of long-term conditions. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted May 26, 2020. The study population included all adults (>18 years) registered at the 157 practices at the start of the study period, 1 st January to end April 2020. Data were extracted on secure N3 terminals from EMIS Web, used by (157/162) practices in the study area. All data was extracted and managed according to UK NHS information governance requirements. We extracted routine clinical data on body mass index (BMI) and smoking status as the latest recorded codes prior to the start of the study period. BMI values were categorised as underweight, normal, overweight, obese and morbidly obese. Data on test-confirmed COVID-19 cases across London and the study CCGs were obtained from the Our primary outcome measure was prevalence of suspected COVID-19 recorded in the EHR. All statistical analysis was undertaken in Stata version 16.1 (College Station, TX: StataCorp LP.) We fitted logistic, mixed effect models, nesting patients within practices. Both univariate and multivariate models were fitted. The effect of ethnicity on the likelihood of suspected COVID-19 presentation was examined, adjusting for differences in demographic and clinical factors including long term conditions and BMI. Sensitivity analyses were undertaken using individual co-morbidities in place of counts of conditions. The clinical effectiveness group is the data processor, and the General Practices in the four CCGs are the data controllers. CEG has the written consent of all practices in the study area to use pseudonymised patient data for audit and research for patient benefit. The researchers adhere to the data protection principles of the Data Protection Act 2018, and all data was managed according to UK NHS information governance requirements. All outputs were in the form of aggregate patient data. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted May 26, 2020. . https://doi.org/10.1101/2020.05.23.20101741 doi: medRxiv preprint The NHS Health Research Authority toolkit (http://www.hra-decisiontools.org.uk/ethics/) identified that Research Ethics Approval was not required for this project as all data is pseudonomised and presented in aggregate form. This was confirmed by the Chair of the North East London Strategic Information Governance Network. Patients and members of the public were not involved in the design or reporting of this study. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted May 26, 2020. . Primary care data from the records of 1,257,130 adult patients registered at 157 practices was available for analysis. Among this population 8,985 (0.7%) had a record of suspected COVID-19 between 14 February and 31 April 2020, and 35,022 (2.8%) had a code for URTI or LRTI infection between 1 st January and 31 April. The univariate analysis (Table 1) shows a two-fold increase in odds by social deprivation, with 88% of the population falling into the 4 th and 5 th (most deprived) national quintiles of the English IMD scores. There is a steep increase of odds associated with increasing numbers of LTCs and with BMI categories. All LTCs were associated with increased odds, the odds ratio for dementia (OR 7.37) may reflect the population living in residential and nursing homes. A sensitivity analysis using individual co-morbidities, rather than numbers of LTCs did not improve the explanatory effect of the model. (see Table 1 supplementary data) . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted May 26, 2020. . https://doi.org/10.1101/2020.05.23.20101741 doi: medRxiv preprint Using patient level data from the GP record this study documents the numbers of suspected COVID-19 cases presenting to practices through the peak of the London epidemic ( Figure 2 ). Data from these GP suspected cases illuminates predictors of infection at an earlier stage of the disease trajectory than data from hospital or ONS case fatality reports. (8, 14) The close to two-fold increase in the odds of infection for South Asian and Black groups shown in the univariate analysis (Table 1) is reduced by only a small amount when adjusted by demographic and clinical factors in the multivariate analysis ( Table 2 ). The sizeable residual enhanced risk for ethnic minority groups in the fully adjusted analysis remains unexplained. The number of co-morbidities in adult patients, and being overweight or obese are both major independent risk factors, but the overall effect of social deprivation was reduced in the multivariate analysis. Figure 2 shows that GP coding for suspected COVID-19 follow the same distribution as test-positive cases, but with a threefold greater volume, reflecting the large number of community cases. Additional symptomatic individuals will have contacted NHS 111; with many others making no contact with health services -including those cases who were asymptomatic. Data on viral tests done either in community or hospital settings were not routinely available to general practice (12) . The strength of this study is based on the use of primary care data for the entire population registered at 157 general practices in adjacent CCGs in east London. The high level of ethnicity recording, coupled with the accurate recording of co-morbidities associated with the QOF, provides a unique opportunity to explore how clinical factors and demography affect the prevalence of suspected COVID-19 by ethnicity. Using UK government data on test-confirmed cases by London . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted May 26, 2020. . https://doi.org/10.1101/2020.05.23.20101741 doi: medRxiv preprint borough, (22) we confirm that GP coded data for suspected COVID-19 follows the same time course as the London epidemic (Figures 1,2) . The inclusion of all episodes of URTI and LRTI from January suggest good separation of these clinical syndromes in east London practices. Data from RCGP surveillance practices suggest BAME populations present to GPs with URTI at similar rates to the white population. (24) Limitations common to studies using routinely collected clinical data include potential diagnostic inaccuracies, and under-recording of some conditions. General practitioners did not have access to COVID-19 viral testing, hence the majority of recorded cases reflect suspected disease. It is likely that this report underestimates the effect size, there will be many asymptomatic, mildly ill, or patients who contacted NHS 111 (but not their practice) in the population not coded for suspected COVID-19. In contrast to studies which use an extended list of co-morbidities or weighted comorbidity scores (25) we used a simple count of 16 conditions in the UK pay for performance QOF, as these are well recorded across practices. (20) We were unable to include potentially important measures, such as household size and intergenerational composition, employment factors including travel and activity more likely to result in exposure, or the availability of personal protective equipment. Such social and cultural factors are likely to make significant contributions to the observed differences in disease prevalence by ethnicity, but may require bespoke data sets to provide answers. The trends in risk from this report are largely consistent with the findings on ethnicity, socioeconomic status and risk of death from COVID-19 based on hospital deaths, and with ONS reports which include deaths in hospital and community settings, adjusted by aggregate data on self-reported health and household composition, albeit collected in 2011. (26) This similarity in risk of disease for BAME adults is surprising, in that this report includes milder episodes of disease, many among younger people and mostly managed within primary care. In contrast with other reports we did not see an excess of male cases. This may reflect a reluctance to consult, or that gender differences only become apparent further along the disease trajectory. The risks of disease associated with smoking have been disputed, with some studies showing lower risks of positive tests, hospital admission or death among current smokers. (9, 27) A recent meta-. CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted May 26, 2020. . https://doi.org/10.1101/2020.05.23.20101741 doi: medRxiv preprint analysis suggests higher risks for smokers and those with COPD. (28) The coded smoking data in our report was limited to current smoking/non-smoking-status. This may introduce bias, in that recent ex-smokers -who may stop because of respiratory symptoms or cardiovascular disease -are included among the non-smokers. Hence smoking was not included in the multivariate analysis. This study demonstrates that much of the Covid-19 epidemic is being managed in primary care, which has rapidly adjusted to requirements for non face-to-face consultations. Consultations in general practice may be useful as an early warning system for detection and monitoring of new outbreaks of disease which may follow the relaxation of lockdown restrictions. Practice infrastructure should be utilised to support testing and contact tracing. Ensuring the timely reporting of COVID-19 test results to practices, and diagnostic information from NHS 111, is a necessary part of this strategy, and will enable practices to provide continuing care to patients with more severe episodes. Unpicking the underlying reasons for the higher risk of COVID-19 infection among those from ethnic minority populations will require studies which include data from a range of other sources, including household composition, overcrowding and a range of factors associated with occupational exposure. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted May 26, 2020. . https://doi.org/10.1101/2020.05.23.20101741 doi: medRxiv preprint No project specific funding Based on the NHS Health Research Authority Questionnaire (http://www.hradecisiontools.org.uk/ethics/) Research Ethics approval was not required for this project as patientlevel data are anonymised, and only aggregated patient data are reported in this study. All GPs in the participating east London practices consented to the use of their anonymised patient data for research and development for patient benefit. All data relevant to the study are included in the article. The authors have declared no competing interests. The study was designed by KB and SH. Data analysis was by CW. The report was written by SH with contributions from all authors. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted May 26, 2020. . Study area test positive cases GP suspected case in the study area . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted May 26, 2020. . . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted May 26, 2020. . . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted May 26, 2020. . https://doi.org/10.1101/2020.05.23.20101741 doi: medRxiv preprint Clinical Characteristics of Coronavirus Disease 2019 in China World Health Organisation. Rolling updates on coronavirus disease (COVID-19). World Health Organisation Presenting Characteristics, Comorbidities, and Outcomes Among 5700 Patients Hospitalized With COVID-19 in the UK care homes body estimates 4,000 residents died from coronavirus. The Guardian UK patients with COVID-19 using the ISARIC WHO Clinical Characterisation Protocol Coronavirus: 38 days when Britain sleepwalked into disaster. The Sunday Times Estimating the asymptomatic proportion of coronavirus disease 2019 (COVID-19) cases on board the Diamond Princess cruise ship Deaths involving COVID-19 by local area and socioeconomic deprivation: deaths occurring between 1 OpenSAFELY: factors associated with COVID-19-related hospital death in the linked electronic health records of 17 million adult NHS patients Covid-19 test results not getting to us, say GPs and local authorities. The Guardian UK: intensive care national audit and research centre; 2020. 15. Office for National Statistics Population and patient factors affecting emergency department attendance in London: retrospective cohort analysis of linked primary and secondary care records. The British journal of general practice : the journal of the Clinical SNOMED CT coding information in relation to COVID-19 www.emisnow.com2020 19. NHS Digital. Quality and Outcomes Framework (QOF) business rules v44 Keep it simple? Predicting primary health care costs with clinical morbidity measures Newham 2,732 (30.4) 377,171 (30.2) IMD = Index of Multiple Deprivation, OR = odds ratio, BMI = body mass index, QOF = Quality and Outcomes Framework, ref = reference The authors are grateful to the participating GPs for their cooperation, without which, such studies would be impossible. The authors wish to thank staff at CEG for supporting practices with guidance and data entry tools which support this project.