Literature DB >> 26602760

Predicting Adverse Health Outcomes in Nursing Homes: A 9-Year Longitudinal Study and Development of the FRAIL-Minimum Data Set (MDS) Quick Screening Tool.

Hao Luo, Terry Y S Lum, Gloria H Y Wong, Joseph S K Kwan, Jennifer Y M Tang, Iris Chi.   

Abstract

OBJECTIVES: To examine the predictive validity of a quick frailty screening tool, the FRAIL-NH, for adverse health outcomes in nursing home residents, using variables from the Minimum Data Set (MDS). The screening items were compiled from the MDS for potential direct application in long-term care facilities using this health information system.
DESIGN: Longitudinal follow-up study of nursing home residents with annual clinical assessment using the MDS and mortality data between 2005 and 2013.
SETTING: Six nursing homes operated by a nongovernmental organization in Hong Kong. PARTICIPANTS: Participants included 2380 nursing home residents aged 65 years or older at study baseline. MEASUREMENTS: Frailty assessed using the FRAIL-NH model with items from the MDS. The model covers 8 areas: fatigue, resistance, ambulation, incontinence, polypharmacy, weight loss, nutritional approach, and help with dressing. Adverse health outcomes in subsequent years were measured: incident falls, worsening activities of daily living (ADL) function, hospitalization, and death.
RESULTS: Using a cutoff score of 5 on the FRAIL-NH, the prevalence of frailty was 58.5% in this nursing home sample. Frailty as identified using the FRAIL-NH predicts incident falls, worsening ADL function, hospitalization, and death (hazard ratios [HR] 2.00-3.73). This remained significant after adjusting for sociodemographic and other clinical characteristics. Each level of increase on the FRAIL-NH has strong distinguishing power on the incidence of adverse outcomes. Intermediate frailty status (score 1-4) also significantly predicts adverse health outcomes (HR 1.57-2.06).
CONCLUSION: The FRAIL-NH is a quick screening tool that can be used to identify frail and prefrail nursing home residents at risk of adverse health outcomes. It can be applied using variables from the MDS, allowing direct adoption in long-term care facilities already using this health information system.

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Year:  2015        PMID: 26602760     DOI: 10.1016/j.jamda.2015.09.006

Source DB:  PubMed          Journal:  J Am Med Dir Assoc        ISSN: 1525-8610            Impact factor:   4.669


  13 in total

1.  Assessing Frailty in Chinese Nursing Home Older Adults: A Comparison between the Frail-NH Scale and Frailty Index.

Authors:  F Ge; M Liu; S Tang; Y Lu; S L Szanton
Journal:  J Nutr Health Aging       Date:  2019       Impact factor: 4.075

2.  F3ALLS Approach to Preventing Falls.

Authors:  J E Morley
Journal:  J Nutr Health Aging       Date:  2018       Impact factor: 4.075

3.  Editorial: Weight Loss is a Major Cause of Frailty.

Authors:  B Fougère; J E Morley
Journal:  J Nutr Health Aging       Date:  2017       Impact factor: 4.075

4.  Screening mammography among nursing home residents in the United States: Current guidelines and practice.

Authors:  Deborah S Mack; Mara M Epstein; Catherine Dubé; Robin E Clark; Kate L Lapane
Journal:  J Geriatr Oncol       Date:  2018-06-04       Impact factor: 3.599

5.  Minimum Data Set Changes in Health, End-Stage Disease and Symptoms and Signs Scale: A Revised Measure to Predict Mortality in Nursing Home Residents.

Authors:  Jessica A Ogarek; Ellen M McCreedy; Kali S Thomas; Joan M Teno; Pedro L Gozalo
Journal:  J Am Geriatr Soc       Date:  2018-03-02       Impact factor: 5.562

Review 6.  Frailty and sarcopenia in elderly.

Authors:  John E Morley
Journal:  Wien Klin Wochenschr       Date:  2016-09-26       Impact factor: 1.704

7.  Relationship between frailty, polypharmacy, and underprescription in older adults living in nursing homes.

Authors:  Marta Gutiérrez-Valencia; Mikel Izquierdo; Esther Lacalle-Fabo; Itxaso Marín-Epelde; María Fernanda Ramón-Espinoza; Thamara Domene-Domene; Álvaro Casas-Herrero; Arkaitz Galbete; Nicolás Martínez-Velilla
Journal:  Eur J Clin Pharmacol       Date:  2018-03-27       Impact factor: 2.953

8.  FRAIL-NH Predicts Outcomes in Long Term Care.

Authors:  E W Kaehr; L C Pape; T K Malmstrom; J E Morley
Journal:  J Nutr Health Aging       Date:  2016-02       Impact factor: 4.075

9.  Physical Frailty and Cognitive Impairment in Older Adults in United States Nursing Homes.

Authors:  Yiyang Yuan; Kate L Lapane; Jennifer Tjia; Jonggyu Baek; Shao-Hsien Liu; Christine M Ulbricht
Journal:  Dement Geriatr Cogn Disord       Date:  2021-04-22       Impact factor: 2.959

10.  Aging, Frailty, and the Microbiome-How Dysbiosis Influences Human Aging and Disease.

Authors:  John P Haran; Beth A McCormick
Journal:  Gastroenterology       Date:  2020-12-08       Impact factor: 22.682

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