Severity scoring in the critically ill: part 2: maximizing value from outcome prediction scoring systems.
Part 2 of this review of ICU scoring systems examines how scoring system data should be used to assess ICU performance. There often are two different consumers of these data: lCU clinicians and quality leaders who seek to identify opportunities to improve quality of care and operational efficiency, and regulators, payors, and consumers who want to compare performance across facilities. The former need to know how to garner maximal insight into their care practices; this includes understanding how length of stay (LOS) relates to quality, analyzing the behavior of different subpopulations, and following trends over time. Segregating patients into low-, medium-, and high-risk populations is especially helpful, because care issues and outcomes may differ across this severity continuum. Also, LOS behaves paradoxically in high-risk patients (survivors often have longer LOS than nonsurvivors); failure to examine this subgroup separately can penalize ICUs with superior outcomes. Consumers of benchmarking data often focus on a single score, the standardized mortality ratio (SMR). However, simple SMRs are disproportionately affected by outcomes in high-risk patients, and differences in population composition, even when performance is otherwise identical, can result in different SMRs. Future benchmarking must incorporate strategies to adjust for differences in population composition and report performance separately for low-, medium- and high-acuity patients. Moreover, because many ICUs lack the resources to care for high-acuity patients (predicted mortality >50%), decisions about where patients should receive care must consider both ICU performance scores and their capacity to care for different types of patients.
Department of Research and Product Marketing, Philips Healthcare, Baltimore, MD. Electronic address: michael.breslow@philips.com.
Michael J
MJ
Breslow
Department of Research and Product Marketing, Philips Healthcare, Baltimore, MD; Department of Pharmacy Practice and Science, University of Maryland School of Pharmacy, Baltimore, MD.
Omar
O
Badawi
D019985:Benchmarking; D003422:Critical Care; D017052:Hospital Mortality; D006801:Humans; D007362:Intensive Care Units / Q000458:organization & administration*; D017063:Outcome Assessment, Health Care; D011237:Predictive Value of Tests; D011785:Quality Assurance, Health Care / Q000458:organization & administration*; D012306:Risk; D012720:Severity of Illness Index