Evaluating the Role of Patient Sample Definitions for Quality Indicators Sensitive to Nurse Staffing Patterns

Published in: Medical Care, v. 42, no. 2, suppl., Feb. 2004, p. II-21-II-33

Posted on RAND.org on December 31, 2003

by Soeren Mattke, Jack Needleman, Peter Buerhaus, Maureen Stewart, Katya Zelevinsky

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BACKGROUND: Administrative data are an attractive data source for the construction of quality indicators to assess and monitor quality of nursing care in hospitals. Current approaches to constructing measures from discharge abstracts apply substantial restrictions to exclude patients at high risk or with preexisting conditions. This study evaluates whether broader sample definitions combined with risk adjustment would allow for larger samples and increase analytic power. METHODS: Eight indicators were constructed from discharge abstracts of major surgical and medical patients from 799 hospitals in 11 states using existing definitions: pneumonia, urinary tract infection, decubitus ulcers, central nervous system complications, shock, sepsis, pulmonary failure, and upper gastrointestinal bleeding. The authors tested the effect of broadening the samples in 4 ways: comparing indicator rates in the broader and restrictive samples; assessing correlations of hospital ranks in the broader and restrictive samples; performing clinical reviews of cases in the added samples; and using different samples in regressions of indicators on nurse staffing variables, adjusting for patient risk. RESULTS: Indicator rates in the broader samples tended to be higher but did not change hospital rankings significantly. Clinical review suggested that many sample restrictions could be dropped. Using indicators based on broader definitions, coefficients on staffing variables increased in magnitude. CONCLUSION: Less restrictive sample definitions were shown to be feasible and increased the sensitivity of the indicators and thus the power of the analysis. Particularly in surgical patients, the samples could be broadened, although more conservative definitions appeared appropriate for medical patients.

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