The value of linking hospital discharge and mortality data for comparative effectiveness research.

Journal of comparative effectiveness research

PubMedID: 24236559

Mark TL, Lawrence W, Coffey RM, Kenney T, Chu BC, Mohler ER, Steiner C. The value of linking hospital discharge and mortality data for comparative effectiveness research. J Comp Eff Res. 2013;2(2):175-84.
Linkage of US state hospital discharge records to state death certificate records offers the possibility of tracking long-term mortality outcomes across large, diverse patient populations, which may be useful for comparative effective analyses.

To demonstrate the value of linking state community hospital discharge data to vital statistics death files for research by conducting a comparative effectiveness analysis.

Linked Patient Discharge Data and Vital Statistics Death Files from the California Office of Statewide Health Planning and Development were used to compare survival rates for patients with an elective repair for abdominal aortic aneurysm who received open aneurysm repair (OAR) versus endovascular aneurysm repair (EVAR). The sample consisted of 13,652 hospitalized patients who underwent an OAR or EVAR for abdominal aortic aneurysm between 1 July 2000 and 31 January 2006. Patients were matched using propensity scores (8966 patients in the matched sample). In-hospital, 30-day, 1-year and 5-year mortality rates were compared between the OAR and EVAR populations, before and after propensity score matching.

We found a few data anomalies (92 out of 13,652), primarily in patients' sex and date of death. The analysis revealed that in the matched cohort, in-hospital and 30-day postdischarge mortality rates were significantly lower following EVAR than OAR; however, consistent with previous clinical trials, differences in the 1- and 5-year rates were not statistically significant.

The study demonstrates that linked US state discharge and mortality data can be a valuable resource for comparative effectiveness analyses. In particular, this approach may be useful when generally available data sets such as Medicare claims data limit the generalizability of findings. Policy-makers and others should consider greater investments in these data.