Development and Validation of the Nursing Home Minimum Data Set 3.0 Mortality Risk Score (MRS3)

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 201...

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Veröffentlicht in:The journals of gerontology. Series A, Biological sciences and medical sciences Jg. 74; H. 2; S. 219
Hauptverfasser: Thomas, Kali S, Ogarek, Jessica A, Teno, Joan M, Gozalo, Pedro L, Mor, Vincent
Format: Journal Article
Sprache:Englisch
Veröffentlicht: United States 16.01.2019
Schlagworte:
Aged
Aged, 80 and over
Cause of Death - trends
Female
Follow-Up Studies
Humans
Male
Medicare - statistics & numerical data
Nursing Homes - statistics & numerical data
Prognosis
Retrospective Studies
Risk Assessment - methods
Survival Rate - trends
Time Factors
United States - epidemiology
United States
ISSN:1758-535X, 1758-535X
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Zusammenfassung: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.
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ISSN:1758-535X
1758-535X
DOI:10.1093/gerona/gly044