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This paper examined cost efficiency differences between rural hospitals participating in the Critical Access Hospital (CAH) Program and a group of non-converting, prospectively paid rural hospitals using both a two-stage semi-parametric approach as well as stochastic frontier analysis (SFA). CAHs receive Medicare cost-based reimbursement, in contrast with the rest of the hospitals reimbursed under Medicare prospective payment system (PPS). However, cost-based reimbursement has been associated with inefficiency in hospital operations and, consequently, concerns have been raised about the efficiency of CAHs. Results showed a positive and significant effect of CAH status on cost inefficiency under both model specifications suggesting that CAHs were less cost efficient than non-converting rural hospitals.

This study examined differences in technical efficiency between two groups of rural hospitals operating under different Medicare reimbursement systems: cost-based reimbursed Critical Access Hospitals (CAHs) and non-converting, prospectively paid (PPS) rural hospitals. To control for hospital size, two different groups of PPS rural hospitals were specified based on bed size. We use a two-stage approach, where data envelopment analysis (DEA) is used in the first stage to estimate technical efficiency. In the second stage, we estimate the effects of environmental variables (CAH status, ownership, Medicare and Medicaid) on hospital efficiency using a truncated regression with bootstrap. Density analysis of efficiency scores suggests that CAHs are more technically efficient than both groups of non-converting, PPS rural hospitals. Similarly, the results of bootstrapped truncated regression showed a positive and significant marginal effect of CAH status suggesting that CAHs are more technically efficient than non-converting, PPS rural hospitals.

This study examines technical efficiency of Critical Access Hospitals (CAH) using a two-stage approach and bootstrap procedures for making valid inference about the impact of environmental variables on CAH efficiency. In the first stage, a data envelopment analysis (DEA) efficiency estimator is used to estimate technical efficiency of each hospital in the sample. In the second stage, efficiency scores are regressed on environmental variables using a truncated regression with bootstrap. Alternatively, a double bootstrap procedure is used, where bias-corrected DEA efficiency scores, obtained by means of bootstrap in the first stage, are used in the second stage bootstrapped truncated regression. While both procedures provide valid inference in the second stage analysis, the double bootstrap procedure has also been shown to improve statistical efficiency in the second stage truncated regression. Our results indicate that, while the two procedures yield in general similar and consistent results, only the double bootstrap procedure unveiled the direct association between Medicare cost-based reimbursement and CAH inefficiency.

This study examines, post-conversion, cost inefficiency of Critical Access Hospitals (CAH) using a two-stage approach. While the results suggest that Medicare cost-based reimbursement and longer participation in the CAH program may increase the cost inefficiency of CAHs, the extent of this inefficiency increase is lower than what previous literature showed.

This study used a stochastic frontier cost model to analyze whether the policy changes that created Critical Access Hospitals (CAHs) caused an increase in the cost inefficiency of these hospitals or their cost inefficiency was brought about by other factors that were similar to all rural hospitals. The estimated mean cost inefficiency of CAH was 25 percent while that of non-CAH rural hospitals was 17.6 percent. However, the estimated results did not provide sufficient evidence to conclude that Medicare cost-based reimbursement was the main cause of higher cost inefficiency of CAHs. There might be other causes that can explain the higher cost inefficiency of CAHs such as the larger number of Medicaid and uninsured patients and the higher levels of uncompensated care that CAHs provide.

This study analyzes difference in efficiency among the U.S. rural hospitals using a two-stage, semi-parametric approach. Data Envelopment Analysis is used in the first stage to calculate cost, technical and allocative efficiencies of Critical Access Hospitals (CAH) and non-CAH rural hospitals. Following Simar and Wilson (2007), bootstrapped truncated regressions are used in the second stage to infer on relationship between the cost, technical and allocative inefficiencies of hospitals and some environmental variables. The estimated results show that CAHs are less cost, technical and allocative efficient than non-CAH rural hospitals. The results also show that Medicare cost-based reimbursement for CAHs has a negative effect on the efficiency of these hospitals while Medicare prospective payment system for non-CAH rural hospitals has a positive effect on hospital efficiency.