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

Kali S. Thomas, Jessica A. Ogarek, Joan Teno, Pedro L. Gozalo, Vincent Mor

Research output: Contribution to journalArticle

Abstract

Background: 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. Participants: 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). Methods: 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. Results: 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]). Conclusions: 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.

Original languageEnglish (US)
Pages (from-to)219-225
Number of pages7
JournalThe journals of gerontology. Series A, Biological sciences and medical sciences
Volume74
Issue number2
DOIs
StatePublished - Jan 16 2019

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Nursing Homes
Mortality
Medicare
Comorbidity
Logistic Models
Datasets
Calibration
Decision Making
Patient Care
Age Groups
Population

ASJC Scopus subject areas

  • Aging
  • Geriatrics and Gerontology

Cite this

Development and Validation of the Nursing Home Minimum Data Set 3.0 Mortality Risk Score (MRS3). / Thomas, Kali S.; Ogarek, Jessica A.; Teno, Joan; Gozalo, Pedro L.; Mor, Vincent.

In: The journals of gerontology. Series A, Biological sciences and medical sciences, Vol. 74, No. 2, 16.01.2019, p. 219-225.

Research output: Contribution to journalArticle

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abstract = "Background: 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. Participants: 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). Methods: 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. Results: 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]). Conclusions: 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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