Theoretical framework of rehabilitation big data based on ICF
10.3969/j.issn.1006-9771.2024.09.007
- VernacularTitle:基于ICF的康复大数据理论架构研究
- Author:
Yifan TIAN
1
;
Di CHEN
;
Yaning CHENG
;
Haiyan YE
;
Ye LIU
;
Yingxin ZHANG
;
Xueli LÜ
Author Information
1. 中国康复科学所康复信息研究部,北京市 100068
- Keywords:
International Classification of Functioning,Disability and Health;
rehabilitation big data;
health metrics network;
rehabilitation services
- From:
Chinese Journal of Rehabilitation Theory and Practice
2024;30(9):1043-1052
- CountryChina
- Language:Chinese
-
Abstract:
Objective To construct the theoretical framework of rehabilitation big data based on International Classification of Func-tioning,Disability and Health(ICF). Methods Drawing upon international rehabilitation policy documents,such as the World Health Organization's Rehabili-tation 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 Rehabilita-tion 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 com-position and function of rehabilitation big data.The content structure of the rehabilitation big data domain was an-alyzed 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,dis-ease and function,and disease,function and intervention.A comprehensive model for generating and applying re-habilitation big data in rehabilitation services was developed in line with the requirements for constructing big da-ta 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.
