Inter-DRG resource dynamics in a prospective payment system: a stochastic kernel approach.
This paper empirically investigates the resource distribution dynamics across Diagnosis Related Groups (DRGs) of elective surgery patients, in a continuing Prospective Payment System (PPS). Existing econometric literature has mainly focussed on the impact of PPS on average Length of Stay (LOS) concluding that the average LOS has declined post PPS. There is little literature on the distribution of this decline across DRGs, in a PPS. The present paper helps fill this gap. It models the evolution over time of the empirical distribution of LOS across DRGs. The empirical distributions are estimated using a non parametric "stochastic kernel approach" based on Markov Chain theory. The results for inlier episodes suggest that resource redistribution will increase capacity and expected number of admissions for DRGs having increasing waiting times. In addition, adjustments in relative cost weights are perceived as price signals by hospitals leading to a change in their casemix. The results for high outlier patients reveal that improved quality of care is one of the factors causing reduction in high outlier episodes.
Sharma
Anurag
A
Centre for Health Economics, Monash University, Clayton 3800, Victoria, Australia. anurag.sharma@buseco.monash.edu.au
D003953:Diagnosis-Related Groups; D017558:Elective Surgical Procedures; D006739:Hospital Administration; D006801:Humans; D007902:Length of Stay / Q000639:trends; D011445:Prospective Payment System; D011787:Quality of Health Care; D040841:Resource Allocation; D013269:Stochastic Processes; D014850:Waiting Lists