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.