This project was funded by the NIHR Health Technology Assessment programme and the Wellcome Trust and will be published in full in Health Technology Assessment; Vol. 18, No. 43. See the NIHR Journals Library website for further project information.

Record linkage is increasingly used to expand the information available for public health research. An understanding of record linkage methods and the relevant strengths and limitations is important for robust analysis and interpretation of linked data. Here, we describe the approach used by Clinical Practice Research Datalink (CPRD) to link primary care data to other patient level datasets, and the potential implications of this approach for CPRD data analysis. General practice electronic health record software providers separately submit de-identified data to CPRD and patient identifiers to NHS Digital, excluding patients who have opted-out from contributing data. Data custodians for external datasets also send patient identifiers to NHS Digital. NHS Digital uses identifiers to link the datasets using an 8-stage deterministic methodology. CPRD subsequently receives a de-identified linked cohort file and provides researchers with anonymised linked data and metadata detailing the linkage process. This methodology has been used to generate routine primary care linked datasets, including data from Hospital Episode Statistics, Office for National Statistics and National Cancer Registration and Analysis Service. 10.6 million (M) patients from 411 English general practices were included in record linkage in June 2018. 9.1M (86%) patients were of research quality, of which 8.0M (88%) had a valid NHS number and were eligible for linkage in the CPRD standard linked dataset release. Linking CPRD data to other sources improves the range and validity of research studies. This manuscript, together with metadata generated on match strength and linkage eligibility, can be used to inform study design and explore potential linkage-related selection and misclassification biases.

BackgroundPotentially inappropriate prescribing (PIP) in older people is associated with increases in morbidity, hospitalisation and mortality. The objective of this study was to estimate the prevalence of and factors associated with PIP, among those aged ≥70 years, in the United Kingdom, using a comprehensive set of prescribing indicators and comparing these to estimates obtained from a truncated set of the same indicators.MethodsA retrospective cross-sectional study was carried out in the UK Clinical Practice Research Datalink (CPRD), in 2007. Participants included those aged ≥ 70 years, in CPRD. Fifty-two PIP indicators from the Screening Tool of Older Persons Potentially Inappropriate Prescriptions (STOPP) criteria were applied to data on prescribed drugs and clinical diagnoses. Overall prevalence of PIP and prevalence according to individual STOPP criteria were estimated. The relationship between PIP and polypharmacy (≥4 medications), comorbidity, age, and gender was examined. A truncated, subset of 28 STOPP criteria that were used in two previous studies, were further applied to the data to facilitate comparison.ResultsUsing 52 indicators, the overall prevalence of PIP in the study population (n = 1,019,491) was 29%. The most common examples of PIP were therapeutic duplication (11.9%), followed by use of aspirin with no indication (11.3%) and inappropriate use of proton pump inhibitors (PPIs) (3.7%). PIP was strongly associated with polypharmacy (Odds Ratio 18.2, 95% Confidence Intervals, 18.0-18.4, P < 0.05). PIP was more common in those aged 70–74 years vs. 85 years or more and in males. Application of the smaller subset of the STOPP criteria resulted in a lower PIP prevalence at 14.9% (95% CIs 14.8-14.9%) (n = 151,598). The most common PIP issues identified with this subset were use of PPIs at maximum dose for > 8 weeks, NSAIDs for > 3 months, and use of long-term neuroleptics.ConclusionsPIP was prevalent in the UK and increased with polypharmacy. Application of the comprehensive set of STOPP criteria allowed more accurate estimation of PIP compared to the subset of criteria used in previous studies. These findings may provide a focus for targeted interventions to reduce PIP.

Purpose It is not clear whether all deaths are recorded in the Clinical Practice Research Datalink (CPRD) or how accurate a recorded date of death is. Individual‐level linkage with national data from the Office for National Statistics (ONS) and Hospital Episode Statistics (HES) in England offers the opportunity to compare death information across different data sources. Methods Age‐standardised mortality rates (ASMRs) standardised to the European Standard Population (ESP) 2013 for CPRD were compared with figures published by the ONS, and crude mortality rates were calculated for a sample population with individual linkage between CPRD, ONS, and HES data. Agreement on the fact of death between CPRD and ONS was assessed and presented over time from 1998 to 2013. Results There were 33 997 patients with a record of death in the ONS data; 33 389 (98.2%) of these were also identified in CPRD. Exact agreement on the death date between CPRD and the ONS was 69.7% across the whole study period, increasing from 53.4% in 1998 to 78.0% in 2013. By 2013, 98.8% of deaths were in agreement within ±30 days. Conclusions For censoring follow‐up and calculating mortality rates, CPRD data are likely to be sufficient, as a delay in death recording of up to 1 month is unlikely to impact results significantly. Where the exact date of death or the cause is important, it may be advisable to include the individually linked death registration data from the ONS.

Abstract