0057 A novel risk prediction tool for disability pension due to musculoskeletal disorders. (21st August 2017)

• Record Type: Journal Article
• Authors: Shiri, Raman; Heliövaara, Markku; Ahola, Kirsi; Kaila-Kangas, Leena; Haukka, Eija; Kausto, Johanna; Saastamoinen, Peppiina; Leino-Arjas, Päivi; Lallukka, Tea
• Is Part Of: Occupational and environmental medicine. Volume 74(2017)Supplement 1
• Page Start: A159
• Page End: A159
• Publication Date: 2017-08-21
• Subjects: Medicine, Industrial -- Periodicals; Environmental health -- Periodicals; 616.980305
• DOI: 10.1136/oemed-2017-104636.417
• Languages: English
• ISSNs: 1351-0711

Abstract

Abstract : Background: It is important to identify individuals at high risk of work disability and target healthcare interventions at the high risk group. The objective of this study was to develop and validate a novel risk prediction tool using a points system to predict the risk of future disability pension due to musculoskeletal disorders (MSDs). Methods: The development population, the Health 2000 Survey, consisted of a representative sample of employees aged 30–60 years (N=3676) and the validation population, the Helsinki Health Study, consisted of employees of the City of Helsinki aged 40–60 years (N=6391) living in Finland. Both survey data sources were linked to disability pension due to MSDs and mortality data from national registers for 11 years follow-up. Results: The discriminative ability of the model with six predictors was good (Gönen and Heller's K concordance statistic=0.821). We gave easy-to-use points to six predictors: sex-dependent age, high level of education, pain limiting daily activities, multisite musculoskeletal pain, arthritis, and a surgery for a spinal disorder or carpal tunnel syndrome. A score 3 or higher out of 7 (top 30% of the index) had good sensitivity (83%) and specificity (70%). Individuals at the top 30% of the risk index were at 29 (CI: 15–55) times higher risk of disability pension due to MSDs than those at the bottom 40%. Conclusion: This easy-to-use screening tool based on self-reported risk factor profiles can help to identify individuals at high risk for disability pension due to MSDs.