基于ICF的康复大数据理论架构研究

doi:10.3969/j.issn.1006-9771.2024.09.007

Abstract

Abstract:

Objective To construct the theoretical framework of rehabilitation big data based on International Classification of Functioning, Disability and Health (ICF).
Methods Drawing upon international rehabilitation policy documents, such as the World Health Organization's Rehabilitation in health systems; Rehabilitation in health systems: guide for action; Rehabilitation indicator menu: a tool accompanying the Framework for Rehabilitation Monitoring and Evaluation (‎FRAME); Template for Rehabilitation Information Collection (TRIC): a tool accompanying the Systematic Assessment of Rehabilitation Situation (STARS); and Framework and Standards for Country Health Information Systems; this study examined the composition and function of rehabilitation big data. The content structure of the rehabilitation big data domain was analyzed using the World Health Organization Family of International Classifications (WHO-FICs). Furthermore, the generation patterns of rehabilitation big data was constructed drawing on the Health Metrics Network and big data hierarchical classification.
Results Within the six primary elements of the health service system, the information system element was particularly significant, encompassing a substantial branch known as rehabilitation big data. There were three components of rehabilitation big data: health condition, health-related factors and health services. The content framework for this data was derived from the WHO-FICs framework, which covered three dimensions: health and function, disease and function, and disease, function and intervention. A comprehensive model for generating and applying rehabilitation big data in rehabilitation services was developed in line with the requirements for constructing big data architectures. The sources of this data included population censuses, social registration information, population surveys, resources, services and personal records. The result chain of rehabilitation big data encompassed five major processes: input, process, output, outcome and impact. The processing and utilization of this data involved collection, storage, management, analysis and application.
Conclusion A theoretical framework for rehabilitation big data has been constructed based on the ICF theory.

Key words: International Classification of Functioning, Disability and Health, rehabilitation big data, health metrics network, rehabilitation services

CLC Number:

TIAN Yifan, CHEN Di, CHENG Yaning, YE Haiyan, LIU Ye, ZHANG Yingxin, LÜ Xueli. Theoretical framework of rehabilitation big data based on ICF[J]. Chinese Journal of Rehabilitation Theory and Practice, 2024, 30(9): 1043-1052.

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References 32

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Theoretical framework of rehabilitation big data based on ICF

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