Special care in dentistry : official publication of the American Association of Hospital Dentists, the Academy of Dentistry for the Handicapped, and the American Society for Geriatric Dentistry · 2022
Development and validation of a nursing home mortality index to identify nursing home residents nearing the end of life in dental clinics.
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Chen Xi, Caplan Daniel J, Comnick Carissa L, Hartshorn Jennifer, Shuman Stephen K, Xie Xian-Jin
Аннотация
BACKGROUND: Nursing home (NH) residents seek care at dental offices, yet many of them are at the end of life. The uncertain life expectancy further complicates the care of NH residents. This study aimed to develop and validate a Nursing Home Mortality Index (NHMI) to identify NH residents in the last year of life.
METHODS: Logistic modeling was used to develop predictive models for death within 1 year after initial appointment by utilizing the new patient examination data and mortality data of 903 Minnesota NH residents. The final model was selected based on areas under the curve (AUC) and then validated using data from 586 Iowa NH residents. Based on the final model, the NHMI was developed with the estimated 1-year mortality for the low, medium and high risk group.
RESULTS: One-year mortalities were 21% and 26% in the development and validation cohorts, respectively. Predictors included age, gender, communication capacity, physical mobility, congestive heart failure, peripheral vascular disease, cancer, cerebrovascular disease, chronic renal disease and liver disease. AUCs for the development and validation models were 0.73 and 0.68, respectively. For the validation cohort, the sensitivity and specificity were 0.79 and 0.53, respectively. The estimated 1-year mortality risks for three risk groups were 0%-10%, 11%-19%, and ≥20%, respectively CONCLUSION: The high mortality rate of NH residents following a dental exam highlighted a need to incorporate patients' prognoses in treatment planning along with normative needs and patients' preferences. The NHMI provides a practical way to guide treatment decisions for end-of-life NH residents.
METHODS: Logistic modeling was used to develop predictive models for death within 1 year after initial appointment by utilizing the new patient examination data and mortality data of 903 Minnesota NH residents. The final model was selected based on areas under the curve (AUC) and then validated using data from 586 Iowa NH residents. Based on the final model, the NHMI was developed with the estimated 1-year mortality for the low, medium and high risk group.
RESULTS: One-year mortalities were 21% and 26% in the development and validation cohorts, respectively. Predictors included age, gender, communication capacity, physical mobility, congestive heart failure, peripheral vascular disease, cancer, cerebrovascular disease, chronic renal disease and liver disease. AUCs for the development and validation models were 0.73 and 0.68, respectively. For the validation cohort, the sensitivity and specificity were 0.79 and 0.53, respectively. The estimated 1-year mortality risks for three risk groups were 0%-10%, 11%-19%, and ≥20%, respectively CONCLUSION: The high mortality rate of NH residents following a dental exam highlighted a need to incorporate patients' prognoses in treatment planning along with normative needs and patients' preferences. The NHMI provides a practical way to guide treatment decisions for end-of-life NH residents.