Consultations for clinical features of possible cancer and associated urgent referrals before and during the COVID-19 pandemic: an observational cohort study from English primary care.

BACKGROUND: It remains unclear to what extent reductions in urgent referrals for suspected cancer during the COVID-19 pandemic were the result of fewer patients attending primary care compared to GPs referring fewer patients. METHODS: Cohort study including electronic health records data from 8,192,069 patients from 663 English practices. Weekly consultation rates, cumulative consultations and referrals were calculated for 28 clinical features from the NICE suspected cancer guidelines. Clinical feature consultation rate ratios (CRR) and urgent referral rate ratios (RRR) compared time periods in 2020 with 2019. FINDINGS: Consultations for cancer clinical features decreased by 24.19% (95% CI: 24.04-24.34%) between 2019 and 2020, particularly in the 6-12 weeks following the first national lockdown. Urgent referrals for clinical features decreased by 10.47% (95% CI: 9.82-11.12%) between 2019 and 2020. Overall, once patients consulted with primary care, GPs urgently referred a similar or greater proportion of patients compared to previous years. CONCLUSION: Due to the significant fall in patients consulting with clinical features of cancer there was a lower than expected number of urgent referrals in 2020. Sustained efforts should be made throughout the pandemic to encourage the public to consult their GP with cancer clinical features.

Using Primary Care Data to Report Real-World Pancreatic Cancer Survival and Symptomatology.

Pancreatic cancer is the 10th most common cancer diagnosed; despite recent advances in many areas of oncology, survival remains poor, in part owing to late diagnosis. Whilst primary care data are used widely for epidemiology and pharmacovigilance, they are less used for observing survival. In this study we extracted a pancreatic cancer cohort from a nationally representative English primary care database of electronic health records (EHRs) and reported on their symptom and mortality data. A total of 11, 649 cases were identified within the Oxford Royal College of General Practitioners (RCGP) Clinical Informatics Digital Hub network. All-cause mortality data was recorded for 4623 (39.69%). Mean age at recording of cancer diagnosis was 71.4 years (SD 12.0 years). 1-year and 5-year survival was 22.06% and 3.27% respectively. Within a multivariate model, age had a significant impact on survival; those diagnosed under the age of 60 had the longest survival, as compared to those age 60 - 79 (HR: 1.36, 95% CI: 1.20 - 1.54, p < 0.001) and 80+ (HR: 2.13, 95% CI: 1.86 - 2.44, p < 0.01). Symptomatology was examined; at any time point abdominal pain was the most commonly reported symptom present in 5271 cases (45.2%), but within the 12 months preceding diagnosis jaundice was the most common feature, present in 2587 patients (22.2%). Future studies clarifying other contributing factors on survival outcomes and patterns of symptomatology are needed; primary care EHRs provide an opportunity to evaluate real-world cancer patient cohort data.

Disparities in the excess risk of mortality in the first wave of COVID-19: Cross sectional study of the English sentinel network.

OBJECTIVES: Few studies report contributors to the excess mortality in England during the first wave of coronavirus disease 2019 (COVID-19) infection. We report the absolute excess risk (AER) of mortality and excess mortality rate (EMR) from a nationally representative COVID-19 sentinel surveillance network including known COVID-19 risk factors in people aged 45 years and above. METHODS: Pseudonymised, coded clinical data were uploaded from contributing primary care providers (N = 1,970,314, ≥45years). We calculated the AER in mortality by comparing mortality for weeks 2 to 20 this year with mortality data from the Office for National Statistics (ONS) from 2018 for the same weeks. We conducted univariate and multivariate analysis including preselected variables. We report AER and EMR, with 95% confidence intervals (95% CI). RESULTS: The AER of mortality was 197.8/10,000 person years (95%CI:194.30-201.40). The EMR for male gender, compared with female, was 1.4 (95%CI:1.35-1.44, p<0.00); for our oldest age band (≥75 years) 10.09 (95%CI:9.46-10.75, p<0.00) compared to 45-64 year olds; Black ethnicity's EMR was 1.17 (95%CI: 1.03-1.33, p<0.02), reference white; and for dwellings with ≥9 occupants 8.01 (95%CI: 9.46-10.75, p<0.00). Presence of all included comorbidities significantly increased EMR. Ranked from lowest to highest these were: hypertension, chronic kidney disease, chronic respiratory and heart disease, and cancer or immunocompromised. CONCLUSIONS: The absolute excess mortality was approximately 2 deaths per 100 person years in the first wave of COVID-19. More personalised shielding advice for any second wave should include ethnicity, comorbidity and household size as predictors of risk.

Reorganisation of primary care for older adults during COVID-19: a cross-sectional database study in the UK.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has resulted in a rapid change in workload across healthcare systems. Factors related to this adaptation in UK primary care have not yet been examined. AIM: To assess the responsiveness and prioritisation of primary care consultation type for older adults during the COVID-19 pandemic. DESIGN AND SETTING: A cross-sectional database study examining consultations between 17 February and 10 May 2020 for patients aged ≥65 years, drawn from primary care practices within the Oxford Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) sentinel network, UK. METHOD: The authors reported the proportion of consultation type across five categories: clinical administration, electronic/video, face-to-face, telephone, and home visits. Temporal trends in telephone and face-to-face consultations were analysed by polypharmacy, frailty status, and socioeconomic group using incidence rate ratios (IRR). RESULTS: Across 3 851 304 consultations, the population median age was 75 years (interquartile range [IQR] 70-82); and 46% (n = 82 926) of the cohort (N = 180 420) were male. The rate of telephone and electronic/video consultations more than doubled across the study period (106.0% and 102.8%, respectively). Face-to-face consultations fell by 64.6% and home visits by 62.6%. This predominantly occurred across week 11 (week commencing 9 March 2020), coinciding with national policy change. Polypharmacy and frailty were associated with a relative increase in consultations. The greatest relative increase was among people taking ≥10 medications compared with those taking none (face-to-face IRR 9.90, 95% CI = 9.55 to 10.26; telephone IRR 17.64, 95% CI = 16.89 to 18.41). CONCLUSION: Primary care has undergone an unprecedented in-pandemic reorganisation while retaining focus on patients with increased complexity.

Primary Care Prostate Cancer Case Ascertainment.

Although routine healthcare data are not collected for research, they are increasingly used in epidemiology and are key real-world evidence for improving healthcare. This study presents a method to identify prostate cancer cases from a large English primary care database. 19,619 (1.3%) men had a code for prostate cancer diagnosis. Codes for medium and high Gleason grading enabled identification of additional 94 (0.5%) cases. Many studies do not report codes used to identify patients, and if published, the lists of codes differ from study to study. This can lead to poor research reproducibility and hinder validation. This work demonstrates that carefully developed comprehensive lists of clinical codes can be used to identify prostate cancer; and that approaches that do not solely rely on clinical codes such as ontologies or data linkage should also be considered.

Computerised medical record systems that guide and protect - reflections on the Bawa-Garba case.

Lawrence Weed proposed we develop computerised, problem orientated medical records that guide and teach.  The Bawa-Garba case outcomes might have been different if care had been supported by computerised medical record (CMR) systems. CMR systems can reduce prescribing errors and could be develop to flag gaps in supervision.   However, CMR systems are not a panacea and need to be fit for purpose.  Our informatics perspective on this case is to call for widespread use of CMR systems - designed to guide and protect.

An ontological approach to identifying cases of chronic kidney disease from routine primary care data: a cross-sectional study.

BACKGROUND: Accurately identifying cases of chronic kidney disease (CKD) from primary care data facilitates the management of patients, and is vital for surveillance and research purposes. Ontologies provide a systematic and transparent basis for clinical case definition and can be used to identify clinical codes relevant to all aspects of CKD care and its diagnosis. METHODS: We used routinely collected primary care data from the Royal College of General Practitioners Research and Surveillance Centre. A domain ontology was created and presented in Ontology Web Language (OWL). The identification and staging of CKD was then carried out using two parallel approaches: (1) clinical coding consistent with a diagnosis of CKD; (2) laboratory-confirmed CKD, based on estimated glomerular filtration rate (eGFR) or the presence of proteinuria. RESULTS: The study cohort comprised of 1.2 million individuals aged 18 years and over. 78,153 (6.4%) of the population had CKD on the basis of an eGFR of < 60 mL/min/1.73m2, and a further 7366 (0.6%) individuals were identified as having CKD due to proteinuria. 19,504 (1.6%) individuals without laboratory-confirmed CKD had a clinical code consistent with the diagnosis. In addition, a subset of codes allowed for 1348 (0.1%) individuals receiving renal replacement therapy to be identified. CONCLUSIONS: Finding cases of CKD from primary care data using an ontological approach may have greater sensitivity than less comprehensive methods, particularly for identifying those receiving renal replacement therapy or with CKD stages 1 or 2. However, the possibility of inaccurate coding may limit the specificity of this method.

An instrument to identify computerised primary care research networks, genetic and disease registries prepared to conduct linked research: TRANSFoRm International Research Readiness (TIRRE) survey.

PURPOSE: The Translational Research and Patients safety in Europe (TRANSFoRm) project aims to integrate primary care with clinical research whilst improving patient safety. The TRANSFoRm International Research Readiness survey (TIRRE) aims to demonstrate data use through two linked data studies and by identifying clinical data repositories and genetic databases or disease registries prepared to participate in linked research. METHOD: The TIRRE survey collects data at micro-, meso- and macro-levels of granularity; to fulfil data, study specific, business, geographical and readiness requirements of potential data providers for the TRANSFoRm demonstration studies. We used descriptive statistics to differentiate between demonstration-study compliant and non-compliant repositories. We only included surveys with >70% of questions answered in our final analysis, reporting the odds ratio (OR) of positive responses associated with a demonstration-study compliant data provider. RESULTS: We contacted 531 organisations within the Eurpean Union (EU). Two declined to supply information; 56 made a valid response and a further 26 made a partial response. Of the 56 valid responses, 29 were databases of primary care data, 12 were genetic databases and 15 were cancer registries. The demonstration compliant primary care sites made 2098 positive responses compared with 268 in non-use-case compliant data sources [OR: 4.59, 95% confidence interval (CI): 3.93-5.35, p < 0.008]; for genetic databases: 380:44 (OR: 6.13, 95% CI: 4.25-8.85, p < 0.008) and cancer registries: 553:44 (OR: 5.87, 95% CI: 4.13-8.34, p < 0.008). CONCLUSIONS: TIRRE comprehensively assesses the preparedness of data repositories to participate in specific research projects. Multiple contacts about hypothetical participation in research identified few potential sites.