Using Functional Independence Measure Subscales to Predict Falls-Rapid Assessment.


Journal

Rehabilitation nursing : the official journal of the Association of Rehabilitation Nurses
ISSN: 2048-7940
Titre abrégé: Rehabil Nurs
Pays: United States
ID NLM: 8104825

Informations de publication

Date de publication:
Historique:
pubmed: 21 3 2018
medline: 17 9 2019
entrez: 21 3 2018
Statut: ppublish

Résumé

Falls remain a major issue in inpatient rehabilitation. Decreased scores on the Functional Independence Measure (FIM), given to every patient, have been shown to predict falls risk. The aim of the study was to extend previous research using FIM to predict falls by using only subscales assessed earliest during admissions to indicate high risk of falls. Retrospective cohort study. Two consecutive samples of patients (n1 = 1,553, n2 = 12,301) admitted to a rehabilitation hospital over 9-month and 5-year periods, respectively, were used to evaluate the predictive utility of using only a small number of FIM subscales. Subscales were selected from those assessed earliest and were related to previously published research on falls risk factors. The metric was developed using a historical data set and was validated with a second, separate group of patients. Receiver operating characteristic curves were used to evaluate predictive utility. The combination of Toileting and Expression subscales yielded a comparable area under the curve to the full FIM, and both were greater than the existing method of falls risk assessment. Likelihood of falling was strongly linearly related to score on the Toileting/Expression metric. The sum of two FIM subscales can be used to predict which patients may fall during their stay in a rehabilitation hospital. The FIM scores are assessed early during a patient's stay, are required for all Medicare patients, and may be useful for simple, rapid, and accurate assignment of falls risk.

Sections du résumé

BACKGROUND BACKGROUND
Falls remain a major issue in inpatient rehabilitation. Decreased scores on the Functional Independence Measure (FIM), given to every patient, have been shown to predict falls risk.
PURPOSE OBJECTIVE
The aim of the study was to extend previous research using FIM to predict falls by using only subscales assessed earliest during admissions to indicate high risk of falls.
DESIGN METHODS
Retrospective cohort study.
METHODS METHODS
Two consecutive samples of patients (n1 = 1,553, n2 = 12,301) admitted to a rehabilitation hospital over 9-month and 5-year periods, respectively, were used to evaluate the predictive utility of using only a small number of FIM subscales. Subscales were selected from those assessed earliest and were related to previously published research on falls risk factors. The metric was developed using a historical data set and was validated with a second, separate group of patients. Receiver operating characteristic curves were used to evaluate predictive utility.
FINDINGS RESULTS
The combination of Toileting and Expression subscales yielded a comparable area under the curve to the full FIM, and both were greater than the existing method of falls risk assessment. Likelihood of falling was strongly linearly related to score on the Toileting/Expression metric.
CONCLUSIONS CONCLUSIONS
The sum of two FIM subscales can be used to predict which patients may fall during their stay in a rehabilitation hospital.
CLINICAL RELEVANCE CONCLUSIONS
The FIM scores are assessed early during a patient's stay, are required for all Medicare patients, and may be useful for simple, rapid, and accurate assignment of falls risk.

Identifiants

pubmed: 29557822
doi: 10.1097/rnj.0000000000000130
doi:

Types de publication

Journal Article

Langues

eng

Pagination

236-244

Auteurs

Benjamin Fusco-Gessick (B)

Sunnyview Rehabilitation Hospital, Schenectady, NY, USA.

Articles similaires

[Redispensing of expensive oral anticancer medicines: a practical application].

Lisanne N van Merendonk, Kübra Akgöl, Bastiaan Nuijen
1.00
Humans Antineoplastic Agents Administration, Oral Drug Costs Counterfeit Drugs

Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
1.00
Humans Male Smoking Cessation Cardiovascular Diseases Female
Humans United States Aged Cross-Sectional Studies Medicare Part C
1.00
Humans Yoga Low Back Pain Female Male

Classifications MeSH