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Development of a Conversion Table Linking Functional Independence Measure Scores to International Classification of Functioning, Disability, and Health Qualifiers: Insights from a Survey of Healthcare Professionals

In clinical practice, patient assessments rely on established scales. Integrating data from these scales into the International Classification of Functioning, Disability, and Health (ICF) framework has been suggested; however, a standardized approach is lacking. Herein, we tested a new approach to d...

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Bibliographic Details
Published in:Healthcare (Basel) 2024-04, Vol.12 (8), p.831
Main Authors: Umemori, Shu, Ogawa, Mao, Yamada, Shin, Komatsu, Masayo, Oikawa, Emiko, Okamoto, Yasuyo, Katoh, Masaki, Shirasaka, Tomohide, Abiko, Kagari, Moriizumi, Shigehiro, Matsuo, Yuichiro, Tohyama, Harukazu, Mukaino, Masahiko
Format: Article
Language:English
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Summary:In clinical practice, patient assessments rely on established scales. Integrating data from these scales into the International Classification of Functioning, Disability, and Health (ICF) framework has been suggested; however, a standardized approach is lacking. Herein, we tested a new approach to develop a conversion table translating clinical scale scores into ICF qualifiers based on a clinician survey. The survey queried rehabilitation professionals about which functional independence measure (FIM) item scores (1-7) corresponded to the ICF qualifiers (0-4). A total of 458 rehabilitation professionals participated. The survey findings indicated a general consensus on the equivalence of FIM scores with ICF qualifiers. The median value for each item remained consistent across all item groups. Specifically, FIM 1 had a median value of 4; FIM 2 and 3 both had median values of 3; FIM 4 and 5 both had median values of 2; FIM 6 had a median value of 1; and FIM 7 had a median value of 0. Despite limitations due to the irreconcilable differences between the frameworks of existing scales and the ICF, these results underline the ICF's potential to serve as a central hub for integrating clinical data from various scales.
ISSN:2227-9032
2227-9032
DOI:10.3390/healthcare12080831