Deriving a risk-adjustment formula for hospital financing: integrating the impact of socio-economic status on length of stay.

The imperfect risk adjustment of prospective payment for hospitals may have dramatic consequences on equity. If the hospital is able to distinguish subgroups of patients with different expected costs within a group for which the risk-adjusted payment per admission is the same, it is likely to select the most profitable cases and deny care to the others. Meanwhile, hospitals refusing to practice patients' selection may experience solvency problems. In the long term, either those hospitals fail and access to care is at risk, or they decrease the quality of treatments and access to quality is at risk. In Belgium, since 1995, a prospective payment per case has replaced the traditional per diem payments for non-medical expenditures. A fixed number of days are paid to each admission, based on the patient's characteristics, namely diagnosis, age and geriatric profile. In this paper, we examine the imperfect risk adjustment related to the non-inclusion of socio-economic factors in the hospital financing formula. Using data from 61 Belgian hospitals from 1995, we observe that socio-economic status, which is currently not accounted for as risk adjuster, has a significant impact on length of stay (LOS). We estimate that patients in the upper-income categories, patients with a self-employed status and patients with an employee status are beneficial for hospitals' financial results, due to their shorter stays. On the contrary, the non-active, the low-income patients and patients benefiting from an insurance preferential regime represent, on average, a financial loss for hospitals. Finally, we find that financial results under the current financing scheme are biased due to the non-inclusion of SES risk-adjustors. Hospitals with the most beneficial social case-mix are shown to experience a shift from a positive to a negative financial outcome when SES risk adjustors are included, while the reverse is observed for hospitals with the worst social case-mix.