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Thomas KS, Ogarek JA, Teno JM, Gozalo PL, Mor V. Development and Validation of the Nursing Home Minimum Data Set 3.0 Mortality Risk Score (MRS3). The journals of gerontology. Series A, Biological sciences and medical sciences. 2019 Jan 16; 74(2):219-225.
To develop a score to predict mortality using the Minimum Data Set 3.0 (MDS 3.0) that can be readily calculated from items collected during nursing home (NH) residents' admission assessments.
We developed a training cohort of Medicare beneficiaries newly admitted to United States NHs during 2012 (N = 1,426,815) and a testing cohort from 2013 (N = 1,160,964).
Data came from the MDS 3.0 assessments linked to the Medicare Beneficiary Summary File. Using the training dataset, we developed a composite MDS 3.0 Mortality Risk Score (MRS3) consisting of 17 clinical items and patients' age groups based on their relation to 30-day mortality. We assessed the calibration and discrimination of the MRS3 in predicting 30- and 60-day mortality and compared its performance to the Charlson Comorbidity Index and the clinician's assessment of 6-month prognosis measured at admission.
The 30- and 60-day mortality rates for the testing population were 2.8% and 5.6%, respectively. Results from logistic regression models suggest that the MRS3 performed well in predicting death within 30 and 60 days (C-Statistics of 0.744 [95% confidence limit (CL) = 0.741, 0.747] and 0.709 [95% CL = 0.706, 0.711], respectively). The MRS3 was a superior predictor of mortality compared to the Charlson Comorbidity Index (C-statistics of 0.611 [95% CL = 0.607, 0.615] and 0.608 [95% CL = 0.605, 0.610]) and the clinicians' assessments of patients' 6-month prognoses (C-statistics of 0.543 [95% CL = 0.542, 0.545] and 0.528 [95% CL = 0.527, 0.529]).
The MRS3 is a good predictor of mortality and can be useful in guiding decision-making, informing plans of care, and adjusting for patients' risk of mortality.