Objective To explore the performance management intervention effect and optimization mode analysis of prefecture-level city hospitals under the reform of diagnosis-intervention packet (DIP) payment system. Methods Taking Deyang peopel’s hospital as the research object and 2021 as the time node of the DIP payment system reform, the data related to the hospital’s operational performance before the implementation of DIP payment (2019-2020) and the hospital’s operational performance after the implementation of DIP (2021-2022) were collected. The performance management evaluation system of Deyang peopel’s hospital was constructed based on game combination weights. The performance management level of Deyang People’s Hospital was measured, and the changes in hospital performance before and after the implementation of DIP payment system reform were analyzed through the construction of the interrupted time series model. Results After the implementation of DIP payment system reform in Deyang People’s Hospital, it had a significant impact on drug revenue, consumables revenue, and medical service revenue (P<0.05). Among them, drug revenue, examination revenue, acceptance revenue before the DIP payment system reform all showed a downward trend, medical service revenue showed an overall upward trend. However, there was no significant impact on the average hospitalization days of the patients, inpatient per capita medical costs, outpatient per capita medical costs, and the proportion of hospitalization income from the health insurance fund for patients (P>0.05). Conclusion The implementation of the DIP payment system can effectively improve the comprehensive level of performance of Deyang peopel’s hospital.
Objective To analyze the changing trends of economic operation indicators in public hospitals in Deyang City, explore the root causes of increasing operational pressure, and propose targeted countermeasures and suggestions. Methods Based on the annual health financial reports of 23 public hospitals in Deyang City from 2016 to 2024, the Joinpoint regression model was used to analyze the time-series trends of 20 economic operation indicators (covering four dimensions: revenue, operational efficiency, cost control and surplus capacity, and debt-paying ability). The annual percent change (APC) was calculated, and important turning points were identified. Meanwhile, a root cause analysis team was established. Fishbone diagram was used to analyze proximal causes from five aspects (man, machine, material, method, and environment), and the “5WHY method” was applied to trace the root causes. Results Among the 20 indicators, 6 showed significant changing trends. Total medical revenue continued to grow, but the growth rate slowed markedly after 2019 (P=0.035, APC decreased from 10.66 to 4.58). The average length of stay for discharged patients showed a trend of first increasing and then decreasing, with 2020 as the turning point (P<0.001, APC changed from 2.42 to ?4.79). The average medical cost per discharged patient shifted from growth to decline in 2020 (P<0.001, APC changed from 9.34 to ?4.57). Total medical activity costs continued to grow, and although the growth rate slowed after 2019 (P=0.027, APC decreased from 11.35 to 5.30), it remained higher than that of total medical revenue. The proportion of personnel expenses continued to grow, tending to flatten after 2018 (P=0.019, APC decreased from 3.91 to 0.79). Health materials consumed per 100 yuan of medical revenue first increased and then decreased, with 2022 as the turning point (P=0.008, APC changed from 1.90 to ?5.44). Root cause analysis showed that the root causes of increasing operational pressure were lack of overall planning for regional healthcare institutions, inadequate internal management level of medical institutions, revenue pressure brought by medical insurance fund management and payment reform, and defects in the medical service price adjustment mechanism that failed to fully reflect true value. Conclusion It is recommended that health authorities strengthen regional overall planning and functional positioning of medical institutions, medical institutions promote refined management and disease-based cost control, medical insurance departments improve the coordinated use and settlement mechanisms of insurance funds, and incorporate cost factors into the pricing mechanism and improve the dynamic adjustment mechanism.