• Eduard E Vasilevskis, Michael W Kuzniewicz, Mitzi L Dean, Ted Clay, Eric Vittinghoff, Deborah J Rennie, and R Adams Dudley.
• Philip R. Lee Institute for Health Policy Studies and Division of General Internal Medicine, University of California-San Francisco, CA, USA. eduard.vasilevskis@vanderbilt.edu
• Med Care. 2009 Jul 1;47(7):803-12.

ContextCurrent 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.ObjectiveDetermine 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 ParticipantsData were retrospectively collected on 10,502 eligible intensive care unit patients across 35 California hospitals between 2001 and 2004.MeasuresWe 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.ResultsIn 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.ConclusionsVariations 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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