To assess productivity loss (PL) variations across a set of chronic diseases and analyze significant PL drivers (demographics, health status, healthcare resource use) in Hungary.
Data from 11 cost-of-illness studies (psoriasis, dementia, systemic sclerosis, multiple sclerosis, benign prostatic hyperplasia, Parkinson's disease, psoriatic arthritis, rheumatoid arthritis, schizophrenia, epilepsy, and diabetes) were pooled, and patient-level data were analyzed. A weighted multiple linear regression analysis was run to identify significant PL indicators. All costs were adjusted to 2018 euro rates and PL was further presented as a proportion of gross domestic product/capita, facilitating results comparability and transferability.
The dataset comprised 1888 patients from 11 chronic diseases. The average indirect cost/(gross domestic product/capita) ratio was highest in schizophrenia (72.4%) and rheumatoid arthritis (71.3%) and lowest in benign prostatic hyperplasia (1.6%). Correlation results infer that a higher EuroQol 5-dimension 3-level index score was significantly associated with lower PL. The number of hospital admissions was the main contributor toward increasing PL among resource use indicators. Age and sex showed inconsistent and insignificant correlations with PL. In regression analysis, a better EuroQol 5-dimension 3-level index score and higher education were consistently associated with decreasing PL in all models.
This article will enable health decision makers to understand the importance of adopting a societal perspective for chronic disease reimbursement decisions. The correlation between PL and health status supports that timely started effective treatments may prevent patients from losing their workability.