Improving the Continuum of Care by Bridging the Gap between Prehospital and Hospital Discharge Data through Stepwise Deterministic Linkage

Abstract

Objective: To describe the process, benefits, and challenges of linking Arizona’s prehospital registry to hospital discharge data. Methods: Data were queried from the Arizona Prehospital Information and Emergency Medical Services Registry System (AZ-PIERS) and the Arizona Hospital Discharge Database (HDD) for the calendar year 2015. To maximize the number of matched records, the databases were deterministically linked in 17 steps using different combinations/variations of patient personal identifiers. Random samples of at least 1% of matched pairs from each of 16 linkage steps (excluding Step 1) were manually reviewed to assess the rate of false positive matches. Results: A total of 626,413 records were reported to AZ-PIERS in 2015. Of those, 503,715 qualified for linkage. These records were matched against 3,125,689 discharge records reported to the HDD in 2015. The first step, which involved exact matching on first name, last name, date of birth, gender, and date of incident/date of admission, yielded a linkage of 64.6% (n = 325,156). The 16 successive steps yielded a further linkage of 26.6% (n = 134,006) for a total linkage of 91.2% (n = 459,162). The manual review indicated an overall false positive match rate for the 16 reviewed steps of 6.96% (n = 99). The 2 steps with the highest false positive match rates were Step 16 (43.02%, n = 77) and Step 17 (31.43%, n = 11). Conclusion: It is feasible to link prehospital and hospital data using stepwise deterministic linkage; this method returns a high linkage rate with a low false positive error rate. Data linkage is vital to identifying and bridging gaps in the continuum of care and is a useful tool in statewide and agency-specific research and quality improvement.