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Background: The range and scope of electronic health record (EHR) data assets in the UK has recently increased, which has been mainly in response to the COVID-19 pandemic. Summarising and comparing the large primary care resources will help researchers to choose the data resources most suited to their needs. Aim: To describe the current landscape of UK EHR databases and considerations of access and use of these resources relevant to researchers. Design & setting: Narrative review of EHR databases in the UK. Method: Information was collected from the Health Data Research Innovation Gateway, publicly available websites and other published data, and from key informants. The eligibility criteria were population-based open-access databases sampling EHRs across the whole population of one or more countries in the UK. Published database characteristics were extracted and summarised, and these were corroborated with resource providers. Results were synthesised narratively. Results: Nine large national primary care EHR data resources were identified and summarised. These resources are enhanced by linkage to other administrative data to a varying extent. Resources are mainly intended to support observational research, although some can support experimental studies. There is considerable overlap of populations covered. While all resources are accessible to bona fide researchers, access mechanisms, costs, timescales, and other considerations vary across databases. Conclusion: Researchers are currently able to access primary care EHR data from several sources. Choice of data resource is likely to be driven by project needs and access considerations. The landscape of data resources based on primary care EHRs in the UK continues to evolve. [ABSTRACT FROM AUTHOR]

Background: The range and scope of electronic health record (EHR) data assets in the UK has recently increased, which has been mainly in response to the COVID-19 pandemic. Summarising and comparing the large primary care resources will help researchers to choose the data resources most suited to their needs. Aim: To describe the current landscape of UK EHR databases and considerations of access and use of these resources relevant to researchers. Design & setting: Narrative review of EHR databases in the UK. Method: Information was collected from the Health Data Research Innovation Gateway, publicly available websites and other published data, and from key informants. The eligibility criteria were population-based open-access databases sampling EHRs across the whole population of one or more countries in the UK. Published database characteristics were extracted and summarised, and these were corroborated with resource providers. Results were synthesised narratively. Results: Nine large national primary care EHR data resources were identified and summarised. These resources are enhanced by linkage to other administrative data to a varying extent. Resources are mainly intended to support observational research, although some can support experimental studies. There is considerable overlap of populations covered. While all resources are accessible to bona fide researchers, access mechanisms, costs, timescales, and other considerations vary across databases. Conclusion: Researchers are currently able to access primary care EHR data from several sources. Choice of data resource is likely to be driven by project needs and access considerations. The landscape of data resources based on primary care EHRs in the UK continues to evolve.

Purpose There has been a notable progress on the development of methods for identification of pregnancies using primary care databases. We aimed to evaluate the prescription of medications during pregnancy applying a novel algorithm. Methods: We identified pregnancies in women aged 15 to 49 years registered in the Database for Pharmacoepidemiological Research in Primary Care (BIFAP) between 2002 and 2015. The algorithm applied sequential cycles that searched in hierarchical order for indicators of conception, delivery or pregnancy loss, and other codes suggestive of pregnancy. Length of pregnancy was assessed by searching for last menstrual period (LMP) date, gestational age, and outcomes of pregnancy. Prescription of specific drugs during the pre‐pregnancy period and first trimester and time trends during pregnancy were evaluated. Results: We identified a total of 155 419 pregnancies during the study period (77.5% completed pregnancies, 21.5% pregnancies losses, 0.8% ectopic pregnancies, and 0.2% stillbirths). Excluding vitamins and supplements, 43.8% of women received at least one prescription during the pre‐pregnancy period and 68.4% during the first trimester. During the first trimester, the most commonly drugs prescribed were analgesics (16.3%) followed by antibiotics (11.8%). From 2002/2003 to 2014/2015, there was an increase of prescriptions for thyroid hormones (1.0% vs 4.7%), H2 blockers (1.0% vs 2.2%), and PPIs (1.4% vs 2.2%). While antidepressants (2.0% vs 1.5%) and benzodiazepines (3.1% vs 2.4%) decreased in the last period. Conclusion: Having in mind the challenges of identifying pregnancies in health care databases, this study demonstrates the usefulness of BIFAP database for studies on drug utilization during pregnancy. [ABSTRACT FROM AUTHOR]

Simulations are a practical and reliable approach to power calculations, especially for multi-level mixed effects models where the analytic solutions can be very complex. In addition, power calculations are model-specific and multi-level mixed effects models are defined by a plethora of parameters. In other words, model variations in this context are numerous and so are the tailored algebraic calculations. This article describes ipdpower in Stata, a new simulations-based command that calculates power for mixed effects two-level data structures. Although the command was developed having individual patient data meta-analyses and primary care databases analyses in mind, where patients are nested within studies and general practices respectively, the methods apply to any two-level structure.

Purpose There is widespread concern about increases in antibiotic use, but comparative data from different European countries on rates of use are lacking. This study was designed to measure and understand the variation in antibiotic utilization across five European countries. Methods Seven European healthcare databases with access to primary care data from Denmark, Germany, the Netherlands, Spain and the UK were used to measure and compare the point and 1-year-period prevalence of antibiotic use between 2004 and 2009. Descriptive analyses were stratified by gender, age and type of antibiotic. Separate analyses were performed to measure the most common underlying indications leading to the prescription of an antibiotic. Results The average yearly period prevalence of antibiotic use varied from 15 (Netherlands) to 30 (Spain) users per 100 patients. A higher prevalence of antibiotic use by female patients, the very young (0-9 years) and old (80+ years), was observed in all databases. The lowest point prevalence was recorded in June and September and ranged from 0.51 (Netherlands) to 1.47 (UK) per 100 patients per day. Twelve percent (Netherlands) to forty-nine (Spain) percent of all users were diagnosed with a respiratory tract infection, and the most common type of antibiotic prescribed were penicillin. Conclusion Using identical methodology in seven EU databases to assess antibiotic use allowed us to compare drug usage patterns across Europe. Our results contribute quantitatively to the true understanding of similarities and differences in the use of antibiotic agents in different EU countries. © 2015 The Authors. Pharmacoepidemiology and Drug Safety Published by John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Purpose To assess the impact of varying study designs, exposure and outcome definitions on the risk of acute liver injury (ALI) associated with antibiotic use. Methods The source population comprised of patients registered in two primary care databases, in the UK and in Spain. We identified a cohort consisting of new users of antibiotics during the study period (2004-2009) and non-users during the study period or in the previous year. Cases with ALI were identified within this cohort and classified as definite or probable, based on recorded medical information. The relative risk (RR) of ALI associated with antibiotic use was computed using Poisson regression. For the nested case-control analyses, up to five controls were matched to each case by age, sex, date and practice (in CPRD) and odds ratios (OR) were computed with conditional logistic regression. Results The age, sex and year adjusted RRs of definite ALI in the current antibiotic use periods was 10.04 (95% CI: 6.97-14.47) in CPRD and 5.76 (95% CI: 3.46-9.59) in BIFAP. In the case-control analyses adjusting for life-style, comorbidities and use of medications, the OR of ALI for current users of antibiotics was and 5.7 (95% CI: 3.46-9.36) in CPRD and 2.6 (95% CI: 1.26-5.37) in BIFAP. Conclusion Guided by a common protocol, both cohort and case-control study designs found an increased risk of ALI associated with the use of antibiotics in both databases, independent of the exposure and case definitions used. However, the magnitude of the risk was higher in CPRD compared to BIFAP. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study was to ascertain acute liver injury (ALI) in primary care databases using different computer algorithms. The aim of this investigation was to study and compare the incidence of ALI in different primary care databases and using different definitions of ALI. Methods: The Clinical Practice Research Datalink (CPRD) in UK and the Spanish 'Base de datos para la Investigación Farmacoepidemiológica en Atención Primaria' (BIFAP) were used. Both are primary care databases from which we selected individuals of all ages registered between January 2004 and December 2009. We developed two case definitions of idiopathic ALI using computer algorithms: (i) restrictive definition (definite cases) and (ii) broad definition (definite and probable cases). Patients presenting prior liver conditions were excluded. Manual review of potential cases was performed to confirm diagnosis, in a sample in CPRD (21 %) and all potential cases in BIFAP. Incidence rates of ALI by age, sex and calendar year were calculated. Results: In BIFAP, all cases considered definite after manual review had been detected with the computer algorithm as potential cases, and none came from the non-cases group. The restrictive definition of ALI had a low sensitivity but a very high specificity (95 % in BIFAP) and showed higher rates of agreement between computer search and manual review compared to the broad definition. Higher incidence rates of definite ALI in 2008 were observed in BIFAP (3.01 (95 % confidence interval (CI) 2.13-4.25) per 100,000 person-years than CPRD (1.35 (95 % CI 1.03-1.78)). Conclusions: This study shows that it is feasible to identify ALI cases if restrictive selection criteria are used and the possibility to review additional information to rule out differential diagnoses. Our results confirm that idiopathic ALI is a very rare disease in the general population. Finally, the construction of a standard definition with predefined criteria facilitates the timely comparison across databases. [ABSTRACT FROM AUTHOR]

Background It has been hypothesized that early-life exposure to vaccinations, infections or antibacterials influence allergic disease development. Concurrent exposure to grass pollens may alter any effect. Objective To test the hypothesis that exposure to antibacterials, vaccinations (DTP or MMR) or specific infections during the first grass pollen seasons of life influences the risk of hayfever more than at any other time of the year. Methods Nested case–control studies were based on birth cohorts within two large databases of computerized patient records from UK general practices: the General Practice Research Database (GPRD) and Doctors' Independent Network (DIN). Seven thousand ninety-eight hayfever cases, diagnosed after age 2, were matched to controls for practice, age, sex and follow-up of control to case ascertainment date. Conditional logistic regression was used to compare exposure by age 1 (age 2 for MMR) inside vs. outside the grass pollen season (May, June, July). Odds ratios (ORs) were pooled across databases. Results There were no associations in either database between MMR during vs. outside the grass pollen season and later hayfever. Of 23 infections studied, none were statistically significant; although analyses for the less common conditions were limited by low statistical power. The pooled OR for hayfever comparing exposure to antibacterials only in the grass pollen season with only outside it was 1.20 (95% CI 0.98–1.47) and for DTP was 0.84 (95% CI 0.72–0.98). Conclusion Although an interaction between early exposure to microbial agents and concurrent grass pollen exposure on hayfever risk seemed plausible, there was little evidence to support it across a range of analyses. However, the effect of DTP though weak deserves further study. [ABSTRACT FROM AUTHOR]

Background and objectives: Primary care databases form a unique source of population-based clinical information on the prevalence and management of diagnosed disorders. Historically such databases have lacked individual level socio-economic markers. We describe the development of the Doctors’ Independent Network (DIN) database for epidemiological and health services research. DIN includes a socio-economic marker (ACORN) based on postcode linkage at individual patient level. The validity of DIN is assessed against the General Practice Research Database (GPRD). Methods: External validity is assessed by comparing the demographic structure and prevalence rates for treated ischemic heart disease (IHD) and treated hay fever with those from the GPRD. We assess the utility of a socio-economic measure (ACORN) based on postcode-linkage at individual patient level by examining the trend in prevalence rates of IHD and hay fever by ACORN index. Results: 142 practices providing high quality data were selected, with 1,827,361 fully registered patients contributing data between 1992 and 2001, representing an identical age–sex structure to that for England & Wales and GPRD. Regionally adjusted prevalence of treated IHD (7.29 and 5.37%, respectively for men and women aged 35+ in 1998) in DIN was highly comparable to GPRD (7.27 and 5.42%). In DIN, the odds ratio of IHD was 1.37 (95% CI 1.30–1.44) in subjects living in “striving” compared to “thriving” areas. The prevalence of treated hay fever prevalence was similar across databases, with inverse associations seen with ACORN in DIN (higher rates in “thriving” areas). Conclusions: DIN provides comparable period prevalence rates to GPRD for two common conditions, with social trends as expected. Primary care databases such as these have the potential to replace the decennial national morbidity surveys carried out in UK general practices, with DIN having the important advantage of including a socio-economic index. [Copyright &y& Elsevier]

(1) Background: There is a major gap of knowledge towards the natural history of miscarriages in electronic medical records. We aimed to calculate the frequency of miscarriages using data from BIFAP database. (2) Methods: We identified all pregnancy losses and carried out a multistep validation exercise. Potential cases with positive predictive values (PPV) of miscarriage confirmation <85% or those confirming other pregnancy loss were excluded. Kaplan–Meier figures and incidence rates (IRs) of miscarriage with 95% confidence intervals (CIs) expressed by 1000 person-weeks were calculated. Stratifying analysis by age, specific high-risk groups, and drug exposure within the pre-pregnancy period were performed restricted to women with recording last menstrual period (LMP). (3) Results: Women with confirmed miscarriage (N = 18,070), tended to be older, with higher frequency of comorbidities and drug utilization. Restricting to women with LPM recorded, IR of miscarriage was 10.89 (CI 95% 10.68–11.10) per 1000 women-weeks, with a median follow-up of 10 weeks (IQR: 8–12). The IR according to age was: 2.71 (CI 95% 2.59–2.84) in those aged <30 years compared to 9.11 (CI 95% 8.55–9.70) in women aged ≥40 years. Advanced maternal age (Hazard Ratio (HR, 95% confidence interval) CI 95%: 3.34 (3.08–3.62)), use of antihypertensives (1.49 (1.21–1.84), and use of drugs classified as D or X during pregnancy (1.17 (1.07–1.29)) showed to be positive predictors associated with increased risk of miscarriages. (4) Conclusion: BIFAP database can be used to identify women suffering from miscarriages, which will serve to further study risk factors associated with miscarriages with special attention to drug utilization. [ABSTRACT FROM AUTHOR]

Background: Quality improvement (QI) is a priority for general practice, and GPs are expected to participate in and provide evidence of QI activity. There is growing interest in harnessing the potential of electronic health records (EHR) to improve patient care by supporting practices to find cases that could benefit from a medicines review. Aim: To develop scalable and reproducible prescribing safety reports using patient-level EHR data. Design and setting: UK general practices that contribute de-identified patient data to the Clinical Practice Research Datalink (CPRD). Method: A scoping phase used stakeholder consultations to identify primary care QI needs and potential indicators. QI reports containing real data were sent to 12 pilot practices that used Vision GP software and had expressed interest. The scale-up phase involved automating production and distribution of reports to all contributing practices that used both Vision and EMIS software systems. Benchmarking reports with patient-level case review lists for two prescribing safety indicators were sent to 457 practices in December 2017 following the initial scale-up (Figure 2). Results: Two indicators were selected from the Royal College of General Practitioners Patient Safety Toolkit following stakeholder consultations for the pilot phase involving 12 GP practices. Pilot phase interviews showed that reports were used to review individual patient care, implement wider QI actions in the practice, and for appraisal and revalidation. Conclusion: Electronic health record data can be used to provide standardised, reproducible reports that can be delivered at scale with minimal resource requirements. These can be used in a national QI initiative that impacts directly on patient care. [ABSTRACT FROM AUTHOR]