Return to work after medical rehabilitation in Germany: Influence of individual factors and regional labour market based on administrative data

• Published in: Journal for labour market research 2023-01, Vol.57 (1), p.1-14, Article 4
• Main Authors: Hetzel, Christian, Leinberger, Sarah, Kaluscha, Rainer, Kranzmann, Angela, Schmidt, Nadine, Mitschele, Anke
• Format: Article
• Language: English
• Subjects: Economic conditions; Economic Policy; Economics; Economics and Finance; Employment; Human Resource Management; Labor Economics; Labor market; Labour market; Original; Original Article; Orthopaedic; Population Economics; Psychosomatic; Regional/Spatial Science; Rehabilitation; Return to work; Sociology; Unemployment
• ISSN: 2510-5027; 2510-5019; 2510-5027
• DOI: 10.1186/s12651-023-00330-1

Background The influence of both individual factors and, in particular, the regional labour market on the return to work after medical rehabilitation is to be analyzed based on comprehensive administrative data from the German Pension Insurance and Employment Agencies. Method For rehabilitation in 2016, pre- and post-rehabilitation employment was determined from German Pension Insurance data for 305,980 patients in 589 orthopaedic rehabilitation departments and 117,386 patients in 202 psychosomatic rehabilitation departments. Labour market data was linked to the district of residence and categorized into 257 labour market regions. RTW was operationalized as the number of employment days in the calendar year after medical rehabilitation. Predictors are individual data (socio-demographics, rehabilitation biography, employment biography) and contextual data (regional unemployment rate, rehabilitation department level: percentage of patients employed before). The estimation method used was fractional logit regression in a cross-classified multilevel model. Results The effect of the regional unemployment rate on RTW is significant yet small. It is even smaller (orthopaedics) or not significant (psychosomatics) when individual employment biographies (i.e., pre-rehabilitation employment status) are inserted into the model as the most important predictors. The interaction with pre-rehabilitation employment status is not substantial. Conclusions Database and methods are of high quality, however due to the nonexperimental design, omitted variables could lead to bias and limit causal interpretation. The influence of the labour market on RTW is small and proxied to a large extent by individual employment biographies. However, if no (valid) employment biographies are available, the labour market should be included in RTW analyses.