Abstract/Summary

Objectives To link five national data sets (three registries, two administrative) and create longitudinal healthcare trajectories for patients with congenital heart disease (CHD), describing the quality and the summary statistics of the linked data set. Design Bespoke linkage of record-level patient identifiers across five national data sets. Generation of spells of care defined as periods of time-overlapping events across the data sets. Setting National Congenital Heart Disease Audit (NCHDA) procedures in public (National Health Service; NHS) hospitals in England and Wales, paediatric and adult intensive care data sets (Paediatric Intensive Care Audit Network; PICANet and the Case Mix Programme from the Intensive Care National Audit & Research Centre; ICNARC-CMP), administrative hospital episodes (hospital episode statistics; HES inpatient, outpatient, accident and emergency; A&E) and mortality registry data. Participants Patients with any CHD procedure recorded in NCHDA between April 2000 and March 2017 from public hospitals. Primary and secondary outcome measures Primary: number of linked records, number of unique patients and number of generated spells of care. Secondary: quality and completeness of linkage. Results There were 143 862 records in NCHDA relating to 96 041 unique patients. We identified 65 797 linked PICANet patient admissions, 4664 linked ICNARC-CMP admissions and over 6 million linked HES episodes of care (1.1M inpatient, 4.7M outpatient). The linked data set had 4 908 153 spells of care after quality checks, with a median (IQR) of 3.4 (1.8–6.3) spells per patient-year. Where linkage was feasible (in terms of year and centre), 95.6% surgical procedure records were linked to a corresponding HES record, 93.9% paediatric (cardiac) surgery procedure records to a corresponding PICANet admission and 76.8% adult surgery procedure records to a corresponding ICNARC-CMP record. Conclusions We successfully linked four national data sets to the core data set of all CHD procedures performed between 2000 and 2017. This will enable a much richer analysis of longitudinal patient journeys and outcomes. We hope that our detailed description of the linkage process will be useful to others looking to link national data sets to address important research priorities.