Impact of Disease Prevalence Adjustment on Hospitalization Rates for Chronic Ambulatory Care–Sensitive Conditions in Germany. (22nd March 2017)

• Record Type: Journal Article
• Authors: Pollmanns, Johannes; Romano, Patrick S.; Weyermann, Maria; Geraedts, Max; Drösler, Saskia E.
• Is Part Of: Health services research. Volume 53:Number 2(2018)
• Page Start: 1180
• Page End: 1202
• Publication Date: 2017-03-22
• Subjects: Ambulatory care–sensitive conditions -- quality of care -- small area analysis; Medical care -- Periodicals; Medical care -- Evaluation -- Periodicals; Hospital care -- Periodicals; Health services administration -- Periodicals; 362
• DOI: 10.1111/1475-6773.12680
• Languages: English
• ISSNs: 0017-9124

Abstract

Abstract : Objectives: To explore effects of disease prevalence adjustment on ambulatory care–sensitive hospitalization (ACSH) rates used for quality comparisons. Data Sources/Study Setting: County‐level hospital administrative data on adults discharged from German hospitals in 2011 and prevalence estimates based on administrative ambulatory diagnosis data were used. Study Design: A retrospective cross‐sectional study using in‐ and outpatient secondary data was performed. Data Collection: Hospitalization data for hypertension, diabetes, heart failure, chronic obstructive pulmonary disease, and asthma were obtained from the German Diagnosis Related Groups (DRG) database. Prevalence estimates were obtained from the German Central Research Institute of Ambulatory Health Care. Principal Findings: Crude hospitalization rates varied substantially across counties (coefficients of variation [CV] 28–37 percent across conditions); this variation was reduced by prevalence adjustment (CV 21–28 percent). Prevalence explained 40–50 percent of the observed variation ( r = 0.65–0.70) in ACSH rates for all conditions except asthma ( r = 0.07). Between 30 percent and 38 percent of areas moved into or outside condition‐specific control limits with prevalence adjustment. Conclusions: Unadjusted ACSH rates should be used with caution for high‐stakes public reporting as differences in prevalence may have a marked impact. Prevalence adjustment should be considered in models analyzing ACSH.