Trends in the inpatient quality indicators: the Veterans Health Administration experience.
BACKGROUND
The Agency for Healthcare Research and Quality Inpatient Quality Indicators (IQIs), which include in-hospital mortality and utilization rates, have received little attention in the Veterans Health Administration (VA), despite extensive private sector use for quality improvement.


OBJECTIVE
We examined the following: the feasibility of applying the IQIs to VA data; temporal trends in national VA IQI rates; temporal and regional IQI trends in geographic areas defined by Veterans Integrated Service Networks' (VISNs); and VA versus non-VA (Nationwide Inpatient Sample) temporal trends.


METHODS
We derived VA- and VISN-level IQI observed rates, risk-adjusted rates, and observed to expected ratios (O/Es), using VA inpatient data (2004-2007). We examined the trends in VA- and VISN-level rates using weighted linear regression, variation in VISN-level O/Es, and compared VA to non-VA trends.


RESULTS
VA in-hospital mortality rates from selected medical conditions (stroke, hip fracture, pneumonia) decreased significantly over time; procedure-related mortality rates were unchanged. Laparoscopic cholecystectomy rates increased significantly. A few VISNs were consistently high or low outliers for the medical-related mortality IQIs. Within any given year, utilization indicators, especially cardiac catheterization and cholecystectomy, showed the most inter-VISN variation. Compared with the non-VA, VA medical-related mortality rates for the above-mentioned conditions decreased more rapidly, whereas laparascopic cholecystectomy rates rose more steeply.


CONCLUSIONS
The IQIs are easily applied to VA administrative data. They can be useful to tracks rate trends over time, reveal variation between sites, and for trend comparisons with other healthcare systems. By identifying potential quality events related to mortality and utilization, they may complement existing VA quality improvement initiatives.
Borzecki
Ann M
AM
Center for Health Quality, Outcomes and Economic Research, Bedford VAMC, Bedford, MA, USA. amb@bu.edu
Christiansen
Cindy L
CL
Loveland
Susan
S
Chew
Priscilla
P
Rosen
Amy K
AK
D000368:Aged; D005240:Feasibility Studies; D005260:Female; D006296:Health Services / Q000706:statistics & numerical data; D006787:Hospitals, Veterans; D006801:Humans; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D019984:Quality Indicators, Health Care; D011787:Quality of Health Care / Q000639:trends*; D020379:Risk Adjustment; D016019:Survival Analysis; D014481:United States