Background And Objectives: The aim of this study was to examine the utility of a hierarchical algorithm incorporating codes from the International Classification of Functioning, Disability and Health--ICF (WHO, 2001) and the International Statistical Classification of Diseases-ICD (WHO, 1994) to classify reasons for eligibility of young children in early intervention.
Methods: The database for this study was a nationally representative enrollment sample of more than 5,500 children in a longitudinal study of early intervention. Reasons for eligibility were reviewed and matched to the closest ICF or ICD codes under one of four major categories (Body Functions/Structures, Activities/Participation, Health Conditions, and Environmental Factors).
Results: The average number of reasons for eligibility provided per child was 1.5, resulting in a population summary exceeding 100%. A total of 305 ICF and ICD codes were used with most (77%) of the children having codes in the category of Body Function/Structures. Forty-one percent of the sample had codes of Health Conditions, whereas the proportions with codes in the Activities/Partipication and Environmental Categories were 10 and 5%, respectively.
Conclusions: The results demonstrate that ICD and ICF can be jointly used as a common language to document disability characteristics of children in early intervention.
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http://dx.doi.org/10.1016/j.jclinepi.2005.09.009 | DOI Listing |
Stud Health Technol Inform
August 2024
World Health Organization, Switzerland.
This paper presents an effort by the World Health Organization (WHO) to integrate the reference classifications of the Family of International Classifications (ICD, ICF, and ICHI) into a unified digital framework. The integration was accomplished via an expanded Content Model and a single Foundation that hosts all entities from these classifications, allowing the traditional use cases of individual classifications to be retained while enhancing their combined use. The harmonized WHO-FIC Content Model and the unified Foundation has streamlined the content management, enhanced the web-based tool functionalities, and provided opportunities for linkage with external terminologies and ontologies.
View Article and Find Full Text PDFFront Public Health
June 2024
Innovation in Healthcare and Social Services, Emilia-Romagna Region, Bologna, Emilia-Romagna, Italy.
Background: Uncertainty and inconsistency in terminology regarding the risk factors (RFs) for in-hospital falls are present in the literature.
Objective: (1) To perform a literature review to identify the fall RFs among hospitalized adults; (2) to link the found RFs to the corresponding categories of international health classifications to reduce the heterogeneity of their definitions; (3) to perform a meta-analysis on the risk categories to identify the significant RFs; (4) to refine the final list of significant categories to avoid redundancies.
Methods: Four databases were investigated.
Dig Dis Sci
September 2024
Department of Gastroenterology, St Luke's University Health Network, 701 ostrum street, Bethlehem, PA, 18015, USA.
Background: Frailty is a clinically recognizable state of increased vulnerability due to age-related decline in reserve and function across multiple physiologic systems that compromises the ability to cope with acute stress. As frailty is being identified as an important risk factor in outcomes of gastrointestinal pathologies, we aimed to assess outcomes in patients with acute pancreatitis within this cohort.
Method: We conducted a retrospective study using the Nationwide Inpatient Sample (NIS) database.
Disabil Rehabil
November 2024
National Rehabilitation Center, Seoul, South Korea.
Purpose: To develop a Korean version of simple, intuitive descriptions (SIDs) for clinical use of the generic functioning domains in the International Classification of Disease 11 revision (ICD-11) Chapter V.
Methods: The initial Korean SID version proposal for the International Classification of Functioning, Disability, and Health (ICF) Rehabilitation set was translated following the Italian version. The remaining 17 codes were developed using original ICF descriptions; WHO Disability Assessment Schedule, Model Disability Survey, Korean Classification of Functioning, Disability, and Health; and previous studies.
Healthcare (Basel)
July 2023
School of Law, Legal Medicine, University of Camerino, 62032 Camerino, Italy.
Artificial intelligence (AI) and machine learning (ML) span multiple disciplines, including the medico-legal sciences, also with reference to the concept of disease and disability. In this context, the International Classification of Diseases, Injuries, and Causes of Death (ICD) is a standard for the classification of diseases and related problems developed by the World Health Organization (WHO), and it represents a valid tool for statistical and epidemiological studies. Indeed, the International Classification of Functioning, Disability, and Health (ICF) is outlined as a classification that aims to describe the state of health of people in relation to their existential spheres (social, family, work).
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