Background: The major fault with existing reimbursement systems lies in their failure to discriminate for the effectiveness of stay, both when paying per day and when paying per episode of treatment.
Objectives: We sought to define an average length of effective stay and recovery trends by impairment category, to design a prospective payment system that takes into account costs and expected recovery trends, and to compare the calculated reimbursement with the predicted costs estimated in a previous study (Saitto C, Marino C, Fusco D, et al. A new prospective payment system for inpatient rehabilitation. Part I: predicting resource consumption. Med Care. 2005;43:844-855).
Research design: We considered all rehabilitation admissions from 5 Italian inpatient facilities during a 12-month period for which total cost of care had already been estimated and daily cost predicted through regression model. We ascertained recovery trends by impairment category through repeated MDS-PAC schedules and factorial analysis of functional status. We defined effective stay and daily resource consumption by impairment category and used these parameters to calculate reimbursement for the admission. We compared our reimbursement with predicted cost through regression analysis and evaluated the goodness of fit through residual analysis.
Results: We calculated reimbursement for 2079 admissions. The r(2) values for the reimbursement to cost correlation ranged from 0.54 in the whole population to 0.56 for "multiple trauma" to 0.85 for "other medical disorders." The best fit was found in the central quintiles of the cost and severity distributions.
Conclusion: For each impairment category, we determined the number of days of effective hospital stay and the trends of functional gain. We demonstrated, at least within the Italian health care system, the feasibility of a reimbursement system that matches costs with functional recovery. By linking reimbursement to effective stay adjusted for trends of functional gain, we suggest it is possible to avoid both needless cuts and extensions of hospital admissions.