ArticleJournal of occupational medicine and toxicology (London, England)2025
Referral criteria for occupational musculo-skeletal diseases: analysis of 7-year (2012-2018) NODIS data.
Article in Journal of occupational medicine and toxicology (London, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
objectivesDiagnosing occupational diseases (ODs) needs both primary care clinicians and occupational physicians to make clinical diagnoses and evaluate work-relatedness. Thus, a precise and efficient referral mechanism between them could be crucial for the diagnosis of ODs. ICD codes have once been used as referral criteria, yet novel ODs with multiple etiologies, like musculoskeletal diseases (MSDs), make ICD codes poor referral criteria with low positive predictive values. Thus, the aim of our cross-sectional study is identifying criteria that are associated with work-relatedness and may have better positive predictive values to the existing ICD codes.
methodsUsing data from Network of Occupational Diseases and Injuries Service (NODIS), Taiwan’s ODs surveillance system, during 2012 to 2018, we calculate the odds of cases being recognized as probable according to different demographic factors. A binomial regression model is further used to identify predictors of work-relatedness, and subgroup analysis is then carried out for each MSDs diagnosis.
results4651 reported cases of occupational MSDs are included in our study, and 2901 (62.37%) cases are probable cases. Using our binomial regression model, characteristics including tenure, gender, sick leaves, industries and job titles are the predictors of work-relatedness of MSDs, and each MSD is associated with a unique set of predictors, which reflects its occupational etiologies and how occupational physicians evaluate work-relatedness.
conclusionsUsing this method, we could not only identify high-risk characteristics and its diagnostic odd ratio (DOR) for each MSD, but also combine different characteristics into a set of referral criteria and calculate the odds of cases being recognized as probable, which could improve referral mechanisms between occupational medicine and other specialties.
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