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  4. Developing a referral protocol for community-based occupational therapy services in Taiwan: A logistic regression analysis
 
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Developing a referral protocol for community-based occupational therapy services in Taiwan: A logistic regression analysis

Journal
PLoS ONE
Journal Volume
11
Journal Issue
2
Pages
e0148414
Date Issued
2016
Author(s)
HUI-FEN MAO  
Chang L.-H.
Tsai A.Y.-J.
Huang W.-N.
Wang J.
DOI
10.1371/journal.pone.0148414
URI
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84959386699&doi=10.1371%2fjournal.pone.0148414&partnerID=40&md5=d7269b1862e7e1ec2cc2187366ab1d01
https://scholars.lib.ntu.edu.tw/handle/123456789/504133
Abstract
Because resources for long-term care services are limited, timely and appropriate referral for rehabilitation services is critical for optimizing clients' functions and successfully integrating them into the community. We investigated which client characteristics are most relevant in predicting Taiwan's community-based occupational therapy (OT) service referral based on experts' beliefs. Data were collected in face-to-face interviews using the Multidimensional Assessment Instrument (MDAI). Community-dwelling participants (n = 221) ? 18 years old who reported disabilities in the previous National Survey of Long-term Care Needs in Taiwan were enrolled. The standard for referral was the judgment and agreement of two experienced occupational therapists who reviewed the results of the MDAI. Logistic regressions and Generalized Additive Models were used for analysis. Two predictive models were proposed, one using basic activities of daily living (BADLs) and one using instrumental ADLs (IADLs). Dementia, psychiatric disorders, cognitive impairment, joint range-ofmotion limitations, fear of falling, behavioral or emotional problems, expressive deficits (in the BADL-based model), and limitations in IADLs or BADLs were significantly correlated with the need for referral. Both models showed high area under the curve (AUC) values on receiver operating curve testing (AUC = 0.977 and 0.972, respectively). The probability of being referred for community OT services was calculated using the referral algorithm. The referral protocol facilitated communication between healthcare professionals to make appropriate decisions for OT referrals. The methods and findings should be useful for developing referral protocols for other long-term care services. ? 2016 Mao et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
SDGs

[SDGs]SDG3

Other Subjects
adult; Article; behavior disorder; clinical protocol; cognitive defect; community assessment; controlled study; daily life activity; decision making; dementia; disability; emotional disorder; fear; health care need; health program; health service; home care; human; interpersonal communication; occupational therapist; occupational therapy; patient referral; prediction; professional competence; professional knowledge; program development; range of motion; rehabilitation care; social welfare; Taiwan; young adult; aged; algorithm; area under the curve; community care; disabled person; female; joint characteristics and functions; long term care; male; mental disease; middle aged; multivariate analysis; occupational therapy; organization and management; pathophysiology; procedures; receiver operating characteristic; rehabilitation; statistical model; very elderly; Activities of Daily Living; Adult; Aged; Aged, 80 and over; Algorithms; Area Under Curve; Community Health Services; Dementia; Disabled Persons; Female; Humans; Logistic Models; Long-Term Care; Male; Mental Disorders; Middle Aged; Multivariate Analysis; Occupational Therapy; Range of Motion, Articular; Referral and Consultation; Rehabilitation; ROC Curve; Taiwan; Young Adult
Publisher
Public Library of Science
Type
journal article

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