Does global capitation prospective payment promote integrated delivery networks? Evidence from China’s compact county medical communities

Abstract

Background

Compact county medical communities (CCMCs) have emerged as a key strategy to strengthen primary healthcare delivery in China. The objective of this study was to assess the impact of the global capitation prospective payment (GCP) reform on CCMCs performance.

Methods

This research collected data from 2018 to 2022 across three pilot regions in China. Using interrupted time series analysis (ITSA), we assessed how the implementation of GCP affected CCMCs development.

Results

The ITSA results show that the average length of stay at the lead hospital decreased by 0.105 days (P < 0.001) after the reform in pilot A, while the average hospital cost increased by 62.272 yuan per month (P < 0.05). The lead hospital in Pilot B had a decrease in average inpatient costs of 54.203 yuan per month (P < 0.001). Conversely, Pilot C’s the lead hospital had an increase in average inpatient costs of 26.610 yuan per month (P < 0.001), and the average length of stay at the lead hospital increased by 0.028 days (P < 0.05).

Conclusion

GCP has reasonably promoted the benign development of CMCCs. However, the diversity of strategies and operations has resulted in a different focus on effectiveness. Based on local resource endowments, future reforms should pay more attention to the synchronization of payment reforms and organizational changes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12939-025-02490-7.

Introduction

Improving the efficiency of limited healthcare resources remains a central challenge for health reforms worldwide [1]. As a country with a large population, especially with the high incidence of chronic diseases leading to a surge in healthcare demand [2], the construction of an integrated healthcare service system has become a priority for China’s healthcare reform [3].

Counties play a vital role in China’s healthcare system by connecting urban and rural areas and serving populations of 500,000 to 1 million residents. County-level hospitals, typically classified as Grade 2 A or higher, manage approximately 90% of common health conditions within their jurisdictions [4]. Drawing from the international experience of integrated healthcare delivery networks (IDNs) [5], China has developed its approach through Compact County Medical Communities (CCMCs) that connect three tiers of service, including county hospitals, township health centers, and village clinics. This vertical integration creates a comprehensive system with shared responsibilities and benefits among participating facilities [6]. Specifically, under the leadership of county hospitals, CCMCs consolidate county and township healthcare resources through unified management of personnel, finances, medications, equipment, information systems, and performance assessment, to build a full-cycle service network that encompasses disease prevention, diagnosis, treatment, and rehabilitation [7]. This model enhances overall healthcare efficiency, strengthens primary care capacity, promotes complementary service functions, and reduces regional healthcare disparities [4, 5]. China is currently implementing pilot programs to explore and refine various CCMCs [6, 8, 9].

Health insurance payment mechanisms as a critical policy instrument for regulating healthcare service delivery [6, 10, 11]. Among these mechanisms, global capitation prospective payment (GCP) has emerged as an effective tool in integrated healthcare systems [12]. By allocating health insurance funds to CCMCs based on their enrolled population [13], this innovative payment structure offers multiple advantages. Patients receive comprehensive, continuous healthcare services, potentially improving their overall health outcomes. Healthcare providers are motivated to optimize resource utilization and expand their patient base. Moreover, the health insurance system can potentially achieve greater financial stability through more efficient resource allocation and reduced unnecessary medical interventions [14]. Existing research has emphasized that prospective payment systems represented by capitation, can incentivize physicians to focus on cost efficiency and revenue growth by increasing the number of people served rather than the intensity of services provided [15].

Despite promising innovations in healthcare financing, China’s system remains predominantly reliant on traditional payment methods such as Fee-For-Service (FFS) and payment by type of disease. While limited regional experiments with prospective payment systems exist in areas like Anhui Tianchang and Shenzhen Luohu, comprehensive implementation of capitation approaches has not yet occurred nationwide [16–20]. Moreover, Current studies have typically examined only isolated effects in single locations [3, 21, 22], leaving a significant knowledge gap regarding the potential simultaneous benefits for insurers, providers, and patients. This research deficiency is particularly notable given how alternative payment mechanisms could fundamentally transform healthcare delivery and resource allocation across the system.

In June 2019, the National Health Commission of the People’s Republic of China issued the Guidance Programme on the Pilot Construction of Compact County Medical Communities. This policy outlined requirements for establishing financial management mechanisms, implementing global budget approaches, and developing frameworks for balance retention and shared costs [23]. Responding to these national guidelines, several pilot areas in Henan Province, specifically locations A (January 2019), B, and C (January 2020), began implementing global capitation prospective payment models within Compact County Medical Communities. Therefore, this study aims to comprehensively analyze these multiple pilot cases, examining healthcare service transformations before and after the reform, and assessing the impact of the global capitation payment model on integrated delivery networks.

Methods

Study site

We selected three pilot sites (A, B, C) with early and experienced implementation in Henan Province as the sample. First, all three pilot regions have explored global capitation prospective payment, thereby providing representative examples of CCMCs under the GCP. Site A initiated implementation in 2019, while Sites B and C followed in 2020. Second, no other healthcare policy reforms were introduced in these regions during the observation period, the GCP and CCMCs policies in these pilot areas remained stable, allowing for a more accurate assessment of GCP impacts. Third, according to the official report from the National Health Commission of the People’s Republic of China, the construction experiences of the three pilot counties in Henan Province, as the pilot of the early county medical communities were demonstrated as typical experiences [24]. Moreover, the data we collected from 2018 to 2022 have shown an upward trend following the reform implementation (Table S1). The specific implementation practices across all three sites are detailed in Table 1.

Table 1.

Basic information on the construction of County medical communities in three pilot cities

Item	A	B	C
Lead hospital	County People’s Hospital	County People’s Hospital	County People’s Hospital
	County Hospital of Traditional Chinese Medicine
	County Central Hospital
	County Maternal and Child Health Center
Membership units	Private hospitals; Township Health Centers; Village clinics	Public hospitals; Community health centers; Township Health Centers; Village clinics	Public hospitals; Private hospitals; District CDC; Community health service centers; Township Health Centers; Village clinics
Resources integration	Administration, Staffing, Finance, Operations, Performance, Pharmaceuticals; Information
Informatization	County-level information master platform, and four medical health service group platforms	Unified intelligent information platform; smart public health data-collection system in village clinics	Medical, Public health, and other business information systems are integrated
Evaluation	Medical quality, Operational efficiency, Sustainability, Satisfaction
Incentive funding	GCP	GCP + Basic Public Health Fund	GCP
Patient Hospitalization Payment Methods	DRG (35 types) /FFS	DIP	DRG
Balance allocation	County: Township: Village5:3:2	County: Township: Village5:3:2	County: Township: Village5:3:2
Subject of assessment	Management Committee of CCMC	County Medical Insurance Bureau	Management Committee of CCMC

Notes: DIP: Diagnosis-Intervention Packet; DRG: Diagnosis Related Groups; FFS: Fee-For-Service

Study design

This study used interrupted time series analysis (ITSA) to assess the impact of the GCP policy on average hospital days and average hospital costs in three regions (A: January 2019, B and C: January 2020). In addition, based on theoretical analysis, we identified and measured 12 performance output indicators (Table 2), and analyzed the differences in the pre- and post-reform effectiveness of Pilot B and Pilot C through t-tests. The data were obtained from the information management system of the Compact Medical Association in the three pilot regions of Henan Province, covering the healthcare service data from 2018 to 2022.

Table 2.

Information on the outcome variable measures

Evaluation indicators	variables
Service capacity	percentage of outpatient emergency department visits in primary institutions (%)
	percentage of hospital discharges in primary institutions(%)
	percentage of tertiary and quaternary surgeries in lead hospitals (%)
Operational efficiency	utilization rate of beds in primary institutions (%)
	average number of consultations carried out by physicians in primary institutions per day (times)
	average hospitalization days in the lead hospital (days)
Cost control	average cost of hospitalization for insured persons (yuan)
	proportion of expenditure of health insurance funds in primary institutions (%)
	average cost of hospitalization in the lead hospital (yuan)
Health outcomes	primary management rate of chronic disease patients (%)
	hypertension control rate of managed population (%)
	diabetes control rate of managed population (%)

The governance of CCMCs in China utilizes GCP to optimize resource allocation and reconfigure incentives under budget constraints. Through the principal-agent theory perspective, we found that the CCMCs operate within a two-tiered principal-agent framework. In the first tier, the healthcare insurance department establishes a “purchasing services” relationship by allocating insurance funds to the healthcare community through GCP. As the agent, the CCMCs must balance cost control with service quality, navigating both incentive compatibility and risk transfer considerations. In the second tier, the lead hospital functions as a sub-principal, creating a collaborative network through integrated resource management, including personnel, finances, technical support, and information. This integration restructures incentives for member institutions, forming the analytical framework of “Payment Reform - Behavioral Response - Performance Outputs” (Fig. 1).

Fig. 1.

Theoretical framework for the impact of GCP on CCMCs

Statistical analysis

Descriptive analyses were used for outcomes in the pilot regions, and t-tests were used to analyze differences before and after the reforms. ITSA was widely recognized as a robust quasi-experimental method that offers strong internal validity for assessing policy interventions [25]. The analysis follows a standard regression model:

In this equation, Y_t represents outcome measures at each time point, while T_t indicates the time elapsed since the study began. The intervention variable (X_t) is coded as 0 for the pre-reform period and 1 for the post-reform period. The model includes an interaction term (X_tT) to capture changes in trends. The coefficients provide key insights: β₀ establishes the baseline outcome level, β₁ shows the pre-reform trend, β₂ indicates immediate changes following the reform, and β₃ reveals how the trend changed after implementation. To ensure statistical validity, we tested for serial autocorrelation using the Durbin-Watson statistic and applied ordinary least squares regression with Newey-West standard errors where necessary to address any autocorrelation in the data (Table S5 in Additional file 2). All statistical analyses were performed using Stata 15.0.

Sensitivity checks

To check the robustness of the findings and the validity of the conclusions, we performed sensitivity checks. China conducted COVID-19 outbreak prevention and control from January 2020 to April 2020. Medical institutions exerted their utmost effort to manage this surge of respiratory infections, resulting in the inability to sustain regular operations. According to the National Health Commission of the People’s Republic of China, after April 2020, the epidemic in the three pilot regions was relatively stable, and the medical service organizations gradually resumed normal operations. According to previous relevant studies, the sensitivity analysis will be set to the time point after May or June 2020 after the outbreak [26–28]. Therefore, to test whether the global capitation reforms had an effect, we set up 1 false intervention time (6 months after the true implementation time) to fit the model to test whether there was an immediate increase or decrease in the outcome variable.

Result

Descriptive analysis

Table 3 reveals statistically significant changes in operational efficiency, cost control, and health outcomes following the implementation of the GCP reforms. In Pilot B, the average cost of hospitalization for participants increased after the implementation of the policy (P < 0.05), and the rate of diabetes control in the managed population increased (P < 0.05). Pilot C the average number of visits per day for primary care physicians decreased (P < 0.05).

Table 3.

Analysis of differences in the implementation of reforms in pilot regions

Variable		B				C
		pre-reform(±S)	post-reform(±S)	t	P	pre-reform(±S)	post-reform(±S)	t	P
Service capacity	percentage of outpatient emergency department visits in primary institutions(%)	26.28 ± 1.23	28.53 ± 3.37	-0.867	0.450	25.80 ± 3.16	35.33 ± 3.62	-3.006	0.057
	percentage of hospital discharges in primary institutions(%)	36.68 ± 1.24	31.22 ± 3.10	2.273	0.108	24.06 ± 1.53	26.27 ± 3.45	-0.821	0.472
	percentage of tertiary and quaternary surgeries in lead hospitals(%)	38.70 ± 1.56	49.73 ± 16.36	-0.903	0.433	42.22 ± 9.64	54.19 ± 3.74	-1.674	0.310
Operational efficiency	utilization rate of beds in primary institutions (%)	58.93 ± 9.23	40.91 ± 9.90	2.039	0.134	57.21 ± 2.96	43.37 ± 0.69	6.484	0.086
	average number of consultations carried out by physicians in primary institutions per day (times)	10.79 ± 2.27	21.11 ± 6.29	-2.134	0.123	19.28 ± 0.42	14.12 ± 1.27	5.319	0.013
	average hospitalization days in the lead hospital (days)	8.85 ± 0.07	9.90 ± 0.61	-2.308	0.104	8.53 ± 0.45	7.62 ± 0.22	3.144	0.051
Cost control	average cost of hospitalization for insured persons (yuan)	7623.02 ± 123.83	8439.08 ± 274.98	-3.795	0.032	6914.01 ± 209.96	6931.62 ± 978.12	-0.024	0.982
	proportion of expenditure of health insurance funds in primary institutions (%)	12.62 ± 0.72	14.17 ± 1.36	-1.443	0.245	13.51 ± 0.41	21.34 ± 4.97	-2.112	0.125
	average cost of hospitalization in the lead hospital (yuan)	4317.12 ± 51.99	4663.76 ± 511.15	-0.908	0.431	7127.80 ± 430.77	7368.42 ± 153.55	-0.758	0.571
Health outcomes	primary management rate of chronic disease patients (%)	80.04 ± 0.28	82.80 ± 2.06	-1.792	0.171	79.80 ± 0.57	83.97 ± 2.08	-2.637	0.078
	hypertension control rate of managed population (%)	79.34 ± 2.64	84.65 ± 0.80	-2.756	0.199	79.30 ± 0.28	81.70 ± 3.90	-0.825	0.470
	diabetes control rate of managed population (%)	79.34 ± 1.24	83.76 ± 0.71	-5.276	0.013	76.55 ± 1.63	78.62 ± 2.72	-0.939	0.417

Notes: Pilot city A began implementing the global capitation payment in 2019, while pilot cities B and C began in 2020

Interrupted time series analysis in the three pilot regions

Effect on the average hospitalization days

The results of ITSA for average hospitalization days in County A showed significant changes observed in β2 (P < 0.001) and β3 (P < 0.001), specifically, after the reform, the average hospitalization day in the lead hospital decreased by 0.105 days. Moreover, the average length of stay at the lead hospital β3 (p < 0.05) increased by 0.028 days in polit C (Table 4) (Fig. 2).

Table 4.

ITSA results of the effect on the average hospital days

Region	Baseline slope β1 (95%CI)	Step change β2 (95%CI)	Slope change β3 (95%CI)
A	0.072(-0.032-0.176)	-2.120(-2.886- -1.354)***	-0.105(-0.209 - -0.001)*
B	-0.035(-0.056- -0.014)**	-0.178(-0.490-0.135)	0.019(-0.005-0.043)
C	0.011(-0.003-0.026)	0.210(-0.281-0.701)	0.028(0.004–0.053)*

Note: * P < 0.05, ** P < 0.01, *** P < 0.001

Fig. 2.

ITSA results of the effect on the average hospital days. (A) Explain the ITSA results for Pilot City A, (B) Describe the ITSA results for Pilot City C

Effect on the average hospital costs

In polit A, the average hospitalization costs β1 and β3 were statistically significant (P < 0.05), before the reform, with the average hospitalization cost demonstrating a decrease of 51.647 yuan per month, while after the reform an increase of 62.272 yuan per month. The average hospitalization costs β2 (p < 0.001) and β3 (p < 0.001) were statistically significant for the lead hospitals in Pilot C. At the time point of the reform, the average hospitalization cost was reduced by 541.075 yuan per month, while it was elevated by 26.610 yuan per month after the reform. The results confirmed the statistical significance of the average hospitalization costs β1 (p < 0.001) and β3 (p < 0.001) in the lead hospital of Pilot B city. After the reform, it was reduced by 54.203 yuan per month (Table 5) (Fig. 3).

Table 5.

ITSA results of the effect on the average hospital costs

Region	Baseline slope β1 (95%CI)	Step change β2 (95%CI)	Slope change β3 (95%CI)
A	-51.647(-121.355-18.062)*	-176.70(-669.074-549.160)	62.272(-7.544-132.088)**
B	53.180(40.400-65.960)***	-241.953(-635.120-151.214)	-54.203(-77.557 - -30.849)***
C	14.054(3.122–24.987)*	-541.075(-774.018- -308.133)***	26.610(10.250-42.971)**

Note: * P < ;0.05, ** P < 0.01, *** P < 0.001

Fig. 3.

ITSA results of the effect on the average hospital costs

Sensitivity checks

Tables S2, S3, and S4 in Additional File 1 illustrate the results of the analyses after adjusting for the timing of the reforms in the three pilot districts, which are consistent with the total sample results. As can be seen from Tables S2-S4 in Additional file 1, GCP implementation was not significantly associated with direct changes in most of the outcome variables at the adjusted intervention dates, or their changes were smaller than the impact of the actual intervention anticipating GCP implementation (Additional file 1).

Discussion

This study has evaluated data on health services in the three-county medical community implementing a global capitation prospective payment pilot areas. The results show significant improvements in Pilot B, including better glycemic control among diabetic patients and reduced average hospitalization costs in the lead hospital. These findings align with previous research demonstrating that integrated healthcare services effectively improve blood pressure management, diabetes self-care, and cost containment [29].

Specifically, the GCP created economic incentives for the medical community to invest in preventive care in Pilot B, while the integration of basic public health funding fostered collaboration among member units, creating a shared financial interest in effective chronic disease management.

Thus, the pilot regional implementation strategy prioritized technology enablement through a three-phase approach that includes the establishment of a smart information platform for the healthcare network; the deployment of an intelligent public health data-collection system in village clinics; and the construction of a combined specialist-generalist model for hierarchical chronic disease management based on health records. This digital framework enhances the services of family doctors while optimizing the allocation of resources through collaboration between specialists and general practitioners. Previous studies have also suggested that enhanced collaboration between specialists and general practitioners is not only conducive to saving health insurance funds but also promotes the integration of doctor-patient interests [30–32]. Additionally, the Diagnosis Intervention Packet (DIP) payment for inpatients in Pilot B promotes standardized medical practices under total prepayment constraints. Previous research indicates that DIP payment systems can reduce per-case inpatient expenditures by approximately 3–5%, further supporting the cost-effectiveness of this model [33].

This research confirmed that the average length of stay in the lead hospital of Pilot A showed a downward trend after the reform, while the opposite trend was observed in Pilot C. Theoretically, the total prepayment system prompts medical institutions to take the initiative to optimize the service process through the risk-sharing mechanism. For example, through economic incentives to regulate diagnosis and treatment behaviors to reduce unreasonable medical expenditures [34]; relying on the sinking of resources to enhance the capacity of grass-roots services, the reform of redistribution of workload, and improve the efficiency of services [35]. A large number of studies have also shown that the total prepayment system of capitation payment has prompted hospitals to assume operational risks, thus controlling the improvement of medical resource utilization efficiency and reduction of service costs [36–38].

Similarly, the practice of Pilot A has verified the effectiveness of this mechanism. We discovered that Pilot A developed a comprehensive efficiency improvement strategy. This included establishing integrated clinical pathway guidelines across county and township levels, implementing mutual recognition of examination results, and incorporating clinical pathway adherence into performance evaluations. This multifaceted approach created favorable conditions for standardizing medical practices and improving service efficiency. Other domestic studies have similarly found that effective oversight of member agencies reduces unnecessary medical services, including inappropriate admissions, examinations, and medication use, the average length of stay of hospitalized patients in the county is shortened [16, 39]. In addition, The organizational structure of Pilot A featured four lead hospitals, including the County People’s Hospital, the County Hospital of Traditional Chinese Medicine, the County Maternal and Child Health Hospital, and the County Central Hospital. Under the prepayment framework, these institutions maintained a balance of competition and collaboration. This controlled competitive environment appears to have contributed to improved healthcare quality and reduced hospitalization duration, consistent with both national and international evidence that moderate competition enhances care quality [40–42]. It should be noted that Pilot C’s average hospitalization days (pre-reform and post-reform) showed an overall downward trend. Although the above difference is not statistically significant, it still indicates a gradual improvement in service efficiency. The performance across pilots reveals complex interactions between institutional environments and policy instruments.

We further found that both pilot A and pilot C showed an upward trend in the average inpatient hospitalization costs in the lead hospitals, and the conclusions were not entirely consistent with the results of previous related studies [14, 43–45]. Ronald evaluated the cost-control effect of the Maryland Medicare Global Budgets Revenue program and found that the average inpatient costs of knee replacement and hip replacement patients were significantly reduced under the total payment method [46]. Similarly, a related study in China found that the global capitation prospective payment system of Medicare reduced the average inpatient sub-costs, as well as the total outpatient medical cost expenditure [47]. However, previous studies have recommended that cost-containment objectives of the capitation budget reform were achieved immediately after the reform, yet were not sustainable [48]. In this study, we also observed that Pilot A and Pilot C experienced a decrease in average hospitalization costs at the immediate pilot of the reform, followed by a softer increase. The GCP has prompted the lead hospitals to optimize the allocation of resources by diverting some patients with common and chronic illnesses to primary care, while the lead hospitals concentrate more on complex and serious illnesses, which may explain the increase in average hospitalization costs in the pilot areas. It should be emphasized that ancillary measures such as clinical pathway optimization and a robust quality monitoring system are still needed to ensure that cost increases are justified.

CCMCs have restructured the power and responsibility of the three tiers of health institutions, with county hospitals focusing on difficult and serious diseases, township health centers strengthening the first diagnosis and triage, and village health offices responsible for health management, forming a graded and orderly closed loop of services [49, 50]. The surplus distribution mechanism based on workload and efficiency has improved the performance of medical and nursing staff enhanced their motivation [51], and provided a supportive environment for collaboration through resource integration, technology empowerment, and management innovation [52]. Practices in three pilot regions validate that the healthcare delivery system achieves behavioral adjustments through systemic incentive reconfiguration when healthcare payment shifts from “fee-for-service” to “value-based payment” [44, 53–55]. It’s worth noting that the performance outputs of healthcare community reforms are deeply influenced by the institutional environment and the combination of policy tools. The experience of Pilot B suggests that an effective combination of information technology infrastructure and specialty-general practice collaborative mechanisms can significantly improve the quality of chronic disease management. The differentiated performance of Pilots A and C highlights that a moderately competitive multi-agent structure is more conducive to stimulating quality improvement dynamics compared with a single-agent model. Therefore, while continuing to promote payment reform, it’s crucial to focus on the synergistic innovation of digital technology empowerment, service process reengineering, and organizational structure optimization.

This study has some strengths. Firstly, it draws on empirical data from three representative regional reforms for empirical analysis. To the best of our knowledge, this is the current empirical study using multiple case samples within this context, enhancing the generalizability; secondly, the research adopts a comprehensive analytical framework to explore the different behavioral responses of county medical communities under GCP and analyze the impact on implementation effectiveness. It can provide guidance for the selection of construction strategies in other reform pilot regions.

Limitations

Some limitations should be considered. First, the construction of county medical communities is a national policy, and most cities in the country are in the process of gradual exploration. Data on implementation in some of the reform areas couldn’t be collected comprehensively, for example, behavioral initiatives from the meso-organizational level could not be assessed quantitatively, which limited the ability to exclude confounding factors and external events. Second, the epidemic pandemic affected the data collection period over a considerable period, and the interpretability of the impact of the reforms needs to be assessed through multi-period data validation, which can be further validated by long-term tracking data in subsequent studies.

Conclusion

The implementation of global capitation prospective payment in the construction of compact county medical communities has promoted the improvement of medical service efficiency and eased the sharp rise in medical costs. However, the implementation and construction strategies of the pilot cities were not fully aligned, and the differentiated behavioral responses allowed for diverse performance. Depending on the reality of the governance environment of the real resource endowment, focusing on the two key areas of accurately calculating the prospective payment amount and improving the supervision and management mechanism may be an important direction for subsequent reforms.

Electronic supplementary material

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Abbreviations

CCMC

Compact County Medical Communities

GCP

Global capitation prospective payment

IDNs

Integrated Delivery Networks

MAs

Medical Alliances

ITSA

Interrupted Time Series Analysis

DIP

Diagnosis-Intervention Packet

DRG

Diagnosis Related Groups

Author contributions

LYC, YG, GLXD, and HBT were involved in the conception and design of the project.LYC was involved in the analysis and interpretation of the data and drafted the article. All authors contributed significant revisions to the manuscript and approved the final version for publication.

Funding

This research is supported by the National Natural Science Foundation of China (Grant No: 72074093).

Data availability

No datasets were generated or analysed during the current study.

Declarations

Ethical approval

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.