| Summary: | 碩士 === 義守大學 === 醫務管理學系 === 100 === Background： The DM-P4P program designed by the National Health Insurance (NHI) in Taiwan has been the most comprehensive, mature P4P program in Taiwan. The program not only required healthcare providers to participate in clinical training to become certified in Taiwan’s Diabetes Shared Care System , hoping to provide patients for complete service including examinations, patients instructions and tracing to decrease or suspend the complications of diabetes, due to those who has been well trained medical staff’s cooperation ,but it also encouraged healthcare providers to increase monitoring and follow-up care for patients. By this way, it not only can maintain the patients health, but also control the cost of medication, and turn into a medical environment that the patients, the hospitals and the government are all satisfied, and accomplish the goal of three win!
Purpose： It is becoming more important now in the healthcare to consider the issue of P4P efficiency. Most recent studies on the efficiency still use the traditional single-stage evaluation of the operation of a hospital, which might not fully understand the influence of environmental factors, such as hospital size and ownership type during which production stage. Hence, this article employs the two-production-stage data envelopment analysis (DEA) to investigate P4P efficiency and then implement the bootstrap truncated regression to discuss in-depth the difference in efficiency and its driving factors. We hope to provide insurers and hospital executives with a roadmap during their decision making on efficiency improvement.
Method： Data are from the National Health Insurance’s claim database and P4P database from 2005 to 2008. The stages we adopt in this study are separated by accountability and outcome. We respectively apply the double bootstrap method (DB method) proposed into these two stages. At every stage, the bootstrap DEA is used to receive the corrected inefficiency value, and then the bootstrap truncated regression model is taken to examine the factors that influence the difference in hospitals’ efficiency.
Result：The main finding is that regional hospitals perform the worst. Other factors that negatively influence management efficiency in the first stage include a hospital treating patients with more comorbidity, hospital volume and hospital level. The factors that negatively influence management efficiency in the two stage age, gender and district hospitals hospital characteristics (such as public ownership).Only one factor, a hospital treating patients with more comorbidity, negatively influences management efficiency in the second stage.
Discussion： Using the two stage method, it could be found that different factors affect the two-staged efficiency. This finding may provide to prove which factors impact on efficiency when making decision by insurer.
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