NDLI: Influencing factors of Barthel index scores among the community-dwelling elderly in Hong Kong: a random intercept model

Content Provider	Springer Nature : BioMed Central
Author	Pan, Hao Zhao, Yang Wang, Hailiang Li, Xinyue Leung, Eman Chen, Frank Cabrera, Javier Tsui, Kwok Leung
Abstract	Background Barthel Index (BI) is one of the most widely utilized tools for assessing functional independence in activities of daily living. Most existing BI studies used populations with specific diseases (e.g., Alzheimer’s and stroke) to test prognostic factors of BI scores; however, the generalization of these findings was limited when the target populations varied. Objectives The aim of the present study was to utilize electronic health records (EHRs) and data mining techniques to develop a generic procedure for identifying prognostic factors that influence BI score changes among community-dwelling elderly. Methods Longitudinal data were collected from 113 older adults (81 females; mean age = 84 years, SD = 6.9 years) in Hong Kong elderly care centers. Visualization technologies were used to align annual BI scores with individual EHRs chronologically. Linear mixed-effects (LME) regression was conducted to model longitudinal BI scores based on socio-demographics, disease conditions, and features extracted from EHRs. Results The visualization presented a decline in BI scores changed by time and health history events. The LME model yielded a conditional R2 of 84%, a marginal R2 of 75%, and a Cohen’s f2 of 0.68 in the design of random intercepts for individual heterogeneity. Changes in BI scores were significantly influenced by a set of socio-demographics (i.e., sex, education, living arrangement, and hobbies), disease conditions (i.e., dementia and diabetes mellitus), and EHRs features (i.e., event counts in allergies, diagnoses, accidents, wounds, hospital admissions, injections, etc.). Conclusions The proposed visualization approach and the LME model estimation can help to trace older adults’ BI score changes and identify the influencing factors. The constructed long-term surveillance system provides reference data in clinical practice and help healthcare providers manage the time, cost, data and human resources in community-dwelling settings.
Related Links	https://bmcgeriatr.biomedcentral.com/counter/pdf/10.1186/s12877-021-02422-4.pdf
Ending Page	12
Page Count	12
Starting Page	1
File Format	HTM / HTML
ISSN	14712318
DOI	10.1186/s12877-021-02422-4
Journal	BMC Geriatrics
Issue Number	1
Volume Number	21
Language	English
Publisher	BioMed Central
Publisher Date	2021-09-06
Access Restriction	Open
Subject Keyword	Geriatrics Gerontology Aging Rehabilitation Barthel index Influencing factors Electronic health records Linear mixed effects model Geriatrics/Gerontology
Content Type	Text
Resource Type	Article
Subject	Geriatrics and Gerontology
Journal Impact Factor	3.4/2023
5-Year Journal Impact Factor	4.1/2023

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