Abstract

Besides the quality of life, patients' return to work is one of the most important treatment results of medical rehabilitation paid by the German Pension Insurance. In order to be able to use the return to work as a quality indicator for medical rehabilitation, a risk adjustment strategy for pre-existing characteristics of patients, rehabilitation departments and labour markets had to be developed. Multiple regression analyses and cross validation were used to develop a risk adjustment strategy, which mathematically compensates the influence of confounders and thus allows for appropriate comparisons between rehabilitation departments regarding patients' return to work after medical rehabilitation. Under the inclusion of experts, the number of employment days in the first and second year after medical rehabilitation were chosen as an appropriate operationalization of return to work. Methodological challenges in the development of the risk adjustment strategy were the identification of a suitable regression method for the distribution of the dependent variable, modelling the multilevel structure of the data appropriately and selecting relevant confounders for return to work. A user-friendly way of communicating the results was developed. The fractional logit regression was chosen as an appropriate regression method to model the U-shaped distribution of the employment days. Low intraclass correlations indicate that the multilevel structure of the data (cross-classified labour market regions and rehabilitation departments) is statistically negligible. Potential confounding factors were theoretically preselected (medical experts were involved for medical parameters) and tested for their prognostic relevance in each indication area using backwards selection. Cross validations proved the risk adjustment strategy to be stable. Adjustment results were displayed in a user-friendly report, including the users' perspective (focus groups and interviews). The developed risk adjustment strategy allows for adequate comparisons between rehabilitation departments and thus enables a quality assessment of treatment results. Methodological challenges, decisions and limitations are discussed in details throughout this paper.

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