1. Using Mortality Risk Scores for Long-term Prognosis of Nursing Home Residents: Caution Is Recommended.
- Author
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Kruse, Robin L., Parker Oliver, Debra, Mehr, David R., Petroski, Gregory F., Swenson, Denise L., and Zweig, Steven C.
- Subjects
COHORT analysis ,LONGITUDINAL method ,NURSING home residents ,MORTALITY risk factors ,PROGNOSIS - Abstract
Background. Determining prognosis for nursing home residents is important for care planning, but reliable prediction is difficult. We compared performance of four long-term mortality risk indices for nursing home residents—the Minimum Data Set Mortality Risk Index (MMRI), a recent revision to this index (MMRI-R), and the original and revised Flacker–Kiely models. Methods. We conducted a prospective cohort study in one 92-bed facility in Missouri. Participants were 130 residents who received a Minimum Data Set assessment from May through October, 2007. We collected the Minimum Data Set variables needed to calculate the mortality risk scores. We determined 6- and 12-month mortality for included residents. Using each mortality risk score as the sole independent predictor in logistic models predicting mortality, we determined discrimination (c-statistic) and calibration (Hosmer–Lemeshow goodness-of-fit statistic) for each model. Results. In our sample, discrimination was 0.59 for both the MMRI and the MMRI-R. Discrimination of the original Flacker–Kiely model was 0.69 for both 6 months and 1 year and 0.71 and 0.70, respectively, for the revised model. Model calibration was adequate for all models. Conclusions. Performance of four models that predict long-term mortality of nursing home residents was fair. In our population, the Flacker–Kiely models had similar and markedly better discrimination than either the MMRI or the MMRI-R. [ABSTRACT FROM PUBLISHER]
- Published
- 2010
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