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Purpose\ud UK primary care provides a rich data source for research. The impact of proposed data collection restrictions is unknown. This study aimed to assess the impact of restricting the scope of electronic health record (EHR) data collection on the ability to conduct research. The study estimated the consequences of restricted data collection on published Clinical Practice Research Datalink studies from high impact journals or referenced in clinical guidelines.\ud \ud Methods\ud A structured form was used to systematically analyse the extent to which individual studies would have been possible using a database with data collection restrictions in place: (1) retrospective collection of specified diseases only; (2) retrospective collection restricted to a 6‐ or 12‐year period; (3) prospective and retrospective collection restricted to non‐sensitive data. Outcomes were categorised as unfeasible (not reproducible without major bias); compromised (feasible with design modification); or unaffected.\ud \ud Results\ud Overall, 91% studies were compromised with all restrictions in place; 56% studies were unfeasible even with design modification. With restrictions on diseases alone, 74% studies were compromised; 51% were unfeasible. Restricting collection to 6/12 years had a major impact, with 67 and 22% of studies compromised, respectively. Restricting collection of sensitive data had a lesser but marked impact with 10% studies compromised.\ud \ud Conclusion\ud EHR data collection restrictions can profoundly reduce the capacity for public health research that underpins evidence‐based medicine and clinical guidance. National initiatives seeking to collect EHRs should consider the implications of restricting data collection on the ability to address vital public health questions.

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.