Using mortality risk scores for long-term prognosis of nursing home residents: caution is recommended.

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.