Benchmarking patient outcomes

Purpose: To examine the usefulness of three types of benchmarking for inter preting patient outcome data. Design: This study was part of a multiyear, multihospital longitudinal surv ey of 10 patient outcomes. The patient outcome used for this methodologic p resentation was central line infections (CLI). The sample included eight ho spitals in an integrated healthcare system, with a range in size from 144 t o 861 beds. The unit of analysis for CLI was the number of line days, with the CLI rate defined as the number of infections per 1,000 patient-line day s per month. Methods: Data on each outcome were collected at the unit level according to standardized protocols. Results were submitted via standardized electronic forms to a central data management center. Data for this presentation were analyzed using a Bayesian hierarchical Poisson model. Results are presente d for each hospital and the system as a whole. Findings: In comparison to published benchmarks, hospital performances were mixed with regard to CLL Five of the 8 hospitals exceeded 2.2 infections p er 1,000 patient-line days. When benchmarks were established for each hospi tal using 95% credible intervals, hospitals did reasonably well with only i solated months reaching or going beyond the benchmark limits. When the enti re system was used to establish benchmarks with the 95% credible intervals, the hospitals that reached or exceeded the benchmark limits remained the s ame, but some hospitals bad CLI rates more frequently in the upper 50% of t he benchmarking limits. Conclusions: Benchmarking of quality indicators can be accomplished in a va riety of ways as a means to quantify patient care and identify areas needin g attention and improvement. Hospital-specific and system-wide benchmarks p rovide relevant feedback for improving performance at individual hospitals.