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Survival prediction in nursing home residents using the Minimum Data Set subscales: ADL Self-Performance Hierarchy, Cognitive Performance and the Changes in Health, End-stage disease and Symptoms and Signs scales.
Eur J Public Health 2009; 19(3):308-12EJ

Abstract

BACKGROUND

With the intention to aid planning for elderly focused public health and residential care needs in rapidly aging societies, a simple model using only age, gender and three Minimum Data Set (MDS) subscales (MDS-ADL Self-Performance Hierarchy, MDS-Cognitive Performance and the MDS-Changes in Health, End-stage disease and Symptoms and Signs scales) was used to estimate long-term survival of older people moving into nursing homes.

METHODS

A total of 1820 nursing home residents were assessed by the MDS 2.0 and their mortality status 5 years later was used to develop a survival prediction model.

RESULT

In December 2006, 54.2% of subjects were dead. Older age at nursing home admission (HR = 1.036 per 1-year increment, 95% CI 1.028-1.045), men (HR = 1.895, 95% CI 1.651-2.175), higher impairment level according to the MDS-ADL (HR = 1.135 per 1-unit increment, 95% CI 1.099-1.173) and MDS-CPS (HR = 1.077 per 1-unit increment, 95% CI 1.033-1.123), and more frail on the MDS-CHESS (HR = 1.150 per 1-unit increment, 95% CI 1.042-1.268), were all independent predictors of shorter survival after nursing home admission in multivariate analysis. Survival function was derived from the fitted Cox regression model. Survival time of nursing home residents with different combinations of risk factors were estimated through the survival function.

CONCLUSION

The MDS-ADL, MDS-CPS and MDS-CHESS scales, in addition to age and gender, provide prognostic information in terms of survival time after institutionalization. The model may be useful for health care and residential care planning in an ageing community.

Authors+Show Affiliations

Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR. jleesw_2000@yahoo.comNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info available

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

19221020

Citation

Lee, Jenny S W., et al. "Survival Prediction in Nursing Home Residents Using the Minimum Data Set Subscales: ADL Self-Performance Hierarchy, Cognitive Performance and the Changes in Health, End-stage Disease and Symptoms and Signs Scales." European Journal of Public Health, vol. 19, no. 3, 2009, pp. 308-12.
Lee JS, Chau PP, Hui E, et al. Survival prediction in nursing home residents using the Minimum Data Set subscales: ADL Self-Performance Hierarchy, Cognitive Performance and the Changes in Health, End-stage disease and Symptoms and Signs scales. Eur J Public Health. 2009;19(3):308-12.
Lee, J. S., Chau, P. P., Hui, E., Chan, F., & Woo, J. (2009). Survival prediction in nursing home residents using the Minimum Data Set subscales: ADL Self-Performance Hierarchy, Cognitive Performance and the Changes in Health, End-stage disease and Symptoms and Signs scales. European Journal of Public Health, 19(3), pp. 308-12. doi:10.1093/eurpub/ckp006.
Lee JS, et al. Survival Prediction in Nursing Home Residents Using the Minimum Data Set Subscales: ADL Self-Performance Hierarchy, Cognitive Performance and the Changes in Health, End-stage Disease and Symptoms and Signs Scales. Eur J Public Health. 2009;19(3):308-12. PubMed PMID: 19221020.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Survival prediction in nursing home residents using the Minimum Data Set subscales: ADL Self-Performance Hierarchy, Cognitive Performance and the Changes in Health, End-stage disease and Symptoms and Signs scales. AU - Lee,Jenny S W, AU - Chau,Patsy P H, AU - Hui,Elsie, AU - Chan,Felix, AU - Woo,Jean, Y1 - 2009/02/12/ PY - 2009/2/18/entrez PY - 2009/2/18/pubmed PY - 2009/9/23/medline SP - 308 EP - 12 JF - European journal of public health JO - Eur J Public Health VL - 19 IS - 3 N2 - BACKGROUND: With the intention to aid planning for elderly focused public health and residential care needs in rapidly aging societies, a simple model using only age, gender and three Minimum Data Set (MDS) subscales (MDS-ADL Self-Performance Hierarchy, MDS-Cognitive Performance and the MDS-Changes in Health, End-stage disease and Symptoms and Signs scales) was used to estimate long-term survival of older people moving into nursing homes. METHODS: A total of 1820 nursing home residents were assessed by the MDS 2.0 and their mortality status 5 years later was used to develop a survival prediction model. RESULT: In December 2006, 54.2% of subjects were dead. Older age at nursing home admission (HR = 1.036 per 1-year increment, 95% CI 1.028-1.045), men (HR = 1.895, 95% CI 1.651-2.175), higher impairment level according to the MDS-ADL (HR = 1.135 per 1-unit increment, 95% CI 1.099-1.173) and MDS-CPS (HR = 1.077 per 1-unit increment, 95% CI 1.033-1.123), and more frail on the MDS-CHESS (HR = 1.150 per 1-unit increment, 95% CI 1.042-1.268), were all independent predictors of shorter survival after nursing home admission in multivariate analysis. Survival function was derived from the fitted Cox regression model. Survival time of nursing home residents with different combinations of risk factors were estimated through the survival function. CONCLUSION: The MDS-ADL, MDS-CPS and MDS-CHESS scales, in addition to age and gender, provide prognostic information in terms of survival time after institutionalization. The model may be useful for health care and residential care planning in an ageing community. SN - 1464-360X UR - https://www.unboundmedicine.com/medline/citation/19221020/Survival_prediction_in_nursing_home_residents_using_the_Minimum_Data_Set_subscales:_ADL_Self_Performance_Hierarchy_Cognitive_Performance_and_the_Changes_in_Health_End_stage_disease_and_Symptoms_and_Signs_scales_ L2 - https://academic.oup.com/eurpub/article-lookup/doi/10.1093/eurpub/ckp006 DB - PRIME DP - Unbound Medicine ER -