Examining GP online consultation in a primary care setting in east midlands, UK.

BACKGROUND: Increasing pressure threatens to overwhelm primary care services, affecting the quality of care and their role as gatekeepers to specialised care services. This study investigated healthcare users' acceptability of - and the effectiveness of - an e-consultation system in primary care services. METHODS: Seven GP practices in East-Midlands, all of whom use online consultation system participated in the study, with a retrospective review being undertaken of 189 electronic patients' records (age range of 18-76 years) over 5 months. The focus was on the electronic records of patients who accessed the service for five different conditions identified as presenting common conditions seen by the GPs practices. Statistical analysis was done using SPSS to perform an exploratory data analysis and descriptive statistics. RESULTS: The results showed a positive reception of the online consultation platform, with an average satisfaction score of 4.15 (most likely to recommend score = 5). Given the nature of the conditions, 47.6% of patients had experienced a previous episode of the health condition they were seeking consultation for, and a total of 72% had existing comorbidities. Follow-up activity occurred for 87.3% of patients, 66.1% of which included at least one follow-up visit for the same condition as the initial online consultation. CONCLUSION: The results suggest that online consultation is convenient for patients, and it also has the potential to relieve pressure placed on primary care services. Although a number of challenges were identified, such as patient verification, this study gives insight into - and enhances our understanding of - the use of online GP consultations.

Data-Resource Profile: United Kingdom Optimum Patient Care Research Database.

Introduction: Electronic medical records (EMRs) maintained in primary care in the UK and collected and stored in EMR databases offer a world-leading resource for observational clinical research. We aimed to profile one such database: the Optimum Patient Care Research Database (OPCRD). Methods and Participants: The OPCRD, incepted in 2010, is a growing primary care EMR database collecting data from 992 general practices within the UK. It covers over 16.6 million patients across all four countries within the UK, and is broadly representative of the UK population in terms of age, sex, ethnicity and socio-economic status. Patients have a mean duration of 11.7 years' follow-up (SD 17.50), with a majority having key summary data from birth to last data entry. Data for the OPCRD are collected incrementally monthly and extracted from all of the major clinical software systems used within the UK and across all four coding systems (Read version 2, Read CTV3, SNOMED DM+D and SNOMED CT codes). Via quality-improvement programmes provided to GP surgeries, the OPCRD also includes patient-reported outcomes from a range of disease-specific validated questionnaires, with over 66,000 patient responses on asthma, COPD, and COVID-19. Further, bespoke data collection is possible by working with GPs to collect new research via patient-reported questionnaires. Findings to Date: The OPCRD has contributed to over 96 peer-reviewed research publications since its inception encompassing a broad range of medical conditions, including COVID-19. Conclusion: The OPCRD represents a unique resource with great potential to support epidemiological research, from retrospective observational studies through to embedded cluster-randomised trials. Advantages of the OPCRD over other EMR databases are its large size, UK-wide geographical coverage, the availability of up-to-date patient data from all major GP software systems, and the unique collection of patient-reported information on respiratory health.

Characteristics of patients in platform C19, a COVID-19 research database combining primary care electronic health record and patient reported information.

BACKGROUND: Data to better understand and manage the COVID-19 pandemic is urgently needed. However, there are gaps in information stored within even the best routinely-collected electronic health records (EHR) including test results, remote consultations for suspected COVID-19, shielding, physical activity, mental health, and undiagnosed or untested COVID-19 patients. Observational and Pragmatic Research Institute (OPRI) Singapore and Optimum Patient Care (OPC) UK established Platform C19, a research database combining EHR data and bespoke patient questionnaire. We describe the demographics, clinical characteristics, patient behavior, and impact of the COVID-19 pandemic using data within Platform C19. METHODS: EHR data from Platform C19 were extracted from 14 practices across UK participating in the OPC COVID-19 Quality Improvement program on a continuous, monthly basis. Starting 7th August 2020, consenting patients aged 18-85 years were invited in waves to fill an online questionnaire. Descriptive statistics were summarized using all data available up to 22nd January 2021. FINDINGS: From 129,978 invitees, 31,033 responded. Respondents were predominantly female (59.6%), white (93.5%), and current or ex-smokers (52.6%). Testing for COVID-19 was received by 23.8% of respondents, of which 7.9% received positive results. COVID-19 symptoms lasted ≥4 weeks in 19.5% of COVID-19 positive respondents. Up to 39% respondents reported a negative impact on questions regarding their mental health. Most (67%-76%) respondents with asthma, Chronic Obstructive Pulmonary Disease (COPD), diabetes, heart, or kidney disease reported no change in the condition of their diseases. INTERPRETATION: Platform C19 will enable research on key questions relating to COVID-19 pandemic not possible using EHR data alone.

Risk Predictors and Symptom Features of Long COVID Within a Broad Primary Care Patient Population Including Both Tested and Untested Patients.

INTRODUCTION: Symptoms may persist after the initial phases of COVID-19 infection, a phenomenon termed long COVID. Current knowledge on long COVID has been mostly derived from test-confirmed and hospitalized COVID-19 patients. Data are required on the burden and predictors of long COVID in a broader patient group, which includes both tested and untested COVID-19 patients in primary care. METHODS: This is an observational study using data from Platform C19, a quality improvement program-derived research database linking primary care electronic health record data (EHR) with patient-reported questionnaire information. Participating general practices invited consenting patients aged 18-85 to complete an online questionnaire since 7th August 2020. COVID-19 self-diagnosis, clinician-diagnosis, testing, and the presence and duration of symptoms were assessed via the questionnaire. Patients were considered present with long COVID if they reported symptoms lasting ≥4 weeks. EHR and questionnaire data up till 22nd January 2021 were extracted for analysis. Multivariable regression analyses were conducted comparing demographics, clinical characteristics, and presence of symptoms between patients with long COVID and patients with shorter symptom duration. RESULTS: Long COVID was present in 310/3151 (9.8%) patients with self-diagnosed, clinician-diagnosed, or test-confirmed COVID-19. Only 106/310 (34.2%) long COVID patients had test-confirmed COVID-19. Risk predictors of long COVID were age ≥40 years (adjusted Odds Ratio [AdjOR]=1.49 [1.05-2.17]), female sex (adjOR=1.37 [1.02-1.85]), frailty (adjOR=2.39 [1.29-4.27]), visit to A&E (adjOR=4.28 [2.31-7.78]), and hospital admission for COVID-19 symptoms (adjOR=3.22 [1.77-5.79]). Aches and pain (adjOR=1.70 [1.21-2.39]), appetite loss (adjOR=3.15 [1.78-5.92]), confusion and disorientation (adjOR=2.17 [1.57-2.99]), diarrhea (adjOR=1.4 [1.03-1.89]), and persistent dry cough (adjOR=2.77 [1.94-3.98]) were symptom features statistically more common in long COVID. CONCLUSION: This study reports the factors and symptom features predicting long COVID in a broad primary care population, including both test-confirmed and the previously missed group of COVID-19 patients.