Relationship between discharge practices and intensive care unit in-hospital mortality performance: evidence of a discharge bias
- PMID: 19536006
- DOI: 10.1097/MLR.0b013e3181a39454
Relationship between discharge practices and intensive care unit in-hospital mortality performance: evidence of a discharge bias
Abstract
Context: Current intensive care unit performance measures include in-hospital mortality after intensive care unit admission. This measure does not account for deaths occurring after transfer to another hospital or soon after discharge and therefore, may be biased.
Objective: Determine how transfer rates to other acute care hospitals and early post-discharge mortality rates impact hospital performance assessments using an in-hospital mortality model.
Design, setting, and participants: Data were retrospectively collected on 10,502 eligible intensive care unit patients across 35 California hospitals between 2001 and 2004.
Measures: We calculated the rates of acute care hospital transfers and early post-discharge mortality (30-day overall mortality-30-day in-hospital mortality) for each hospital. We assessed hospital performance with standardized mortality ratios (SMRs) using the Mortality Probability Model III. Using regression models, we explored the relationship between in-hospital SMRs and the rates of hospital transfers or early post-discharge mortality. We explored the same relationship using a 30-day SMR.
Results: In multivariable models, for each 1% increase in patients transferred to another acute care hospital, there was an in-hospital SMR reduction of -0.021 (-0.040-0.001). Additionally, a 1% increase in early post-discharge mortality was associated with an in-hospital SMR reduction of -0.049 (-0.142-0.045). Assessing hospital performance based upon 30-day mortality end point resulted in SMRs closer to 1.0 for hospitals at high and low ends of in-hospital mortality performance.
Conclusions: Variations in transfer rates and potentially discharge timing appear to bias in-hospital SMR calculations. A 30-day mortality model is a potential alternative that may limit this bias.
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