Value and role of intensive care unit outcome prediction models in end-of-life decision making☆
Section snippets
History and context
Evaluation of hospital treatment outcomes is said to have begun in the late nineteenth century with Florence Nightingale's 1863 publication of Notes on Hospitals, in which she identified broad variation in British hospital mortality rates. In the early twentieth century, Ernest Codman challenged his surgical colleagues at the Massachusetts General Hospital to evaluate the effects of specific interventions on patients' outcomes, which he labeled the “end results idea.” Both pioneers acknowledged
Current role
The most common explicit use for mortality prediction models in the United States health care system is for the calculation of “risk-adjusted” mortality rates for groups of patients treated in hospitals (eg, patients admitted after an acute myocardial infarction), organizational units (eg, patients admitted to an ICU), or by individual providers (eg, patients undergoing bypass surgery by Dr. Smith). Ostensibly, this allows for the identification of quality outliers whose observed mortality rate
Quality improvement
Efforts to improve upon the statistical performance of mortality prediction models — as distinct from risk-adjustment models for hospital and ICU quality profiling—would be welcome and cannot go unmentioned. Furthermore, efforts to develop models that incorporate data on long-term outcomes, such as functional independence and cognition, would provide patients and their proxies with the information that may most significantly affect their preferences for intensive medical care. However, the most
Acknowledgements
We would like to thank Mark S. Roberts, MD, MPP, for help with the figures used in this chapter.
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Funding by the Robert Wood Johnson Foundation; National Institute on Aging, Grant # 1 K08 AG021921-01.