• Medical care · Oct 2009

    Development and validation of hospital "end-of-life" treatment intensity measures.

    • Amber E Barnato, Max H Farrell, Chung-Chou H Chang, Judith R Lave, Mark S Roberts, and Derek C Angus.
    • Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania 15213, USA. aeb2@pitt.edu
    • Med Care. 2009 Oct 1;47(10):1098-105.

    BackgroundHealth care utilization among decedents is increasingly used as a measure of health care efficiency, but decedent-based measures may be biased estimates of care received by "dying" patients.ObjectiveTo develop and validate new measures of hospital "end-of-life" treatment intensity.Research DesignRetrospective cohort study using Pennsylvania Health Care Cost Containment Council (PHC4) discharge data (April 2001-March 2005) and Centers for Medicare and Medicaid Services (CMS) data (January 1999-December 2003).SubjectsPatients 65 and older admitted to 174 Pennsylvania acute care hospitals.MeasuresHospital-specific standardized ratios of intensive care unit (ICU) and life-sustaining treatment (LST) use among terminal admissions (decedents) and admissions with a high probability of dying, and spending and use of hospitals, ICUs, and physicians among patients in their last 6 months of life.ResultsThere was marked between-hospital variation in the use of the ICU and LSTs among decedents and admissions with high probability of dying. All hospital decedent and high probability of dying measures were highly correlated (P < 00001). In principal components factor analysis, all 4 of the last-6-months cohort-based measures, the decedent and high-risk admission-based ICU measures, and 8 of the 12 decedent and high probability of dying LST measures loaded onto a single factor, explaining 42% of the variation in the data.ConclusionsHospitals' end-of-life intensity varies in the use of specific life-sustaining treatments that are somewhat emblematic of aggressive end-of-life care. End-of-life intensity is a relatively stable hospital attribute that is robust to multiple measurement approaches.

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