MEASURING STATE DEPENDENCE EFFECT IN HOSPITAL VALUE BASED PURCHASING PAYMENT ADJUSTMENT.

Research Question- Hospital Value Based Purchasing (HVBP) program, launched and administrated by CMS (center for Medicare and Medicaid Services), is the first national level pay for performance program for hospitals in US. Each year, CMS withholds a percentage of payments from each hospital to fund the program and re-distribute the payment based on the performance of the four dimensions (patient experience, safety, cost efficiency and clinical quality). In FY 2013, the withholding percentage is 1%. Since FY 2017, the withholding percentage was 2%. The state dependence effect, proposed by Heckman (1981), refers to the phenomenon that the realization of an event affects the probability that the same event occuring in the future. In this study, we applied the dynamic random effect probit model to analyze whether previous years' award/penalty status affect their probability of receiving award/penalty in the future (i.e. whether there is a state dependence effect), results showed that there is a significant positive state dependence effect and the effect varies across hospitals of different ownership. Method And Data- dynamic random effect probit model, payment adjustment factors, panel data, 2471 hospitals from 2013 to 2018. Summary of Findings- The results showed a positive significant state dependence effect across the three different models we estimated, and is significant with hospitals located in different geo areas (large urban/other urban/rural) and with hospitals of different ownerships (government owned/voluntary non profit/proprietary). For the factors that impact the likelihood that a hospital receive a reward from the HVBP program, we found that number of employees show a significant positive effect, suggesting that as the number of employees get larger, hospitals have more labor resources, and can manage to improve upon the quality measures to reach a reward; number of beds and discharges show a significant negative effect, suggesting that as patient volumn get heavier, hospitals become unable to meet the quality criteria, suggesting there is a potentially a negative network effect. Teaching status show a significant negative effect, this makes sense because residents in hospitals are still in their training stage and may not be able to perform in a quality level that is required by the program. Percent of Medicare/Medicaid discharge show a moderate negative effect. Comparing with proprietary hospitals, voluntary non profit and government owned hospitals are more likely to receive a reward. Among demographic variables, we observe a moderate significant negative effect from number of black and Hispanic population, household income show a significant positive effect on the probability of a hospital receive a reward, and competition show a moderate significant For geographic factors, we do observe that, comparing with hospitals located in rural area, hospitals located in urban areas are less likely to receive a reward, comparing with hospitals located in New England area, the hospitals located in Mid Atlantic, West South Central show a significant less likelihood of receiving a reward, the hospitals located in East South Central show a moderate significant less likelihood of receiving a reward, while hospitals located in other areas do not show a significant difference. Key Contributions- Previous research on this HVBP Program has focused on the impact of the program and what are the factors that lead to a hospital being penalized or rewarded, the results are mixed. The key contributions are: First, we investigated whether a state dependence effect exists in hospital payment adjustment, an effect that was largely not studied by previous studies and we found the effect is significant; Second, we find a number of factors that influenced this effect, including demographics, geographics and hospital characteristics and finally implications for policy makers are provided. [ABSTRACT FROM AUTHOR]