The Impact of the “Healthy China 2030” planning outline strategy on the development of China’s medical and health resources—based on interrupted time series analysis from 1990 to 2023

Abstract

To quantify the impact of the implementation of the “Healthy China 2030” Planning Outline on the scale expansion of medical and health resources in China, and to assess the dynamic changes of such resources before and after the policy intervention. Data for this study were obtained from the China Health Statistics Yearbook covering the period from 1990 to 2023. In October 2016, the Chinese government officially issued the Healthy China 2030 Planning Outline. A total of 13 indicators across 3 dimensions (human resources, physical resources, and financial resources) were selected for this study, specifically: number of hospitals, number of hospital beds, number of health personnel, number of health technicians, number of licensed (assistant) physicians, number of registered nurses, as well as the per 1,000 population counterparts of the above human resource indicators; additional financial indicators included total health expenditure, per capita health expenditure, and government health expenditure. Segmented regression analysis under the interrupted time series (ITS) analysis framework was applied to evaluate the changing trends of medical and health resources in China from 1990 to 2023, with a focus on the characteristics of scale changes in such resources before and after the implementation of the Outline. Autocorrelation of the outcome indicators was first assessed via residual plots, the reliability of the results was further verified using the Durbin-Watson test, and the Newey-West method was subsequently applied to correct the standard errors. To ensure the robustness of the study findings, sensitivity analyses were performed respectively by setting 2017 as the alternative intervention start point and excluding data from the COVID-19 pandemic period (2020–2023). Interrupted time series analysis showed that after the implementation of the “Healthy China 2030” Planning Outline, the scale of China’s medical and health resources continued to expand and showed a significant growth trend (all P < 0.05): the number of hospitals increased steadily from 1990 to 2023, with a growth coefficient of 0.082 (95% CI: 0.060–0.103) after the policy implementation; the number of hospital beds showed a significant upward trend (coefficient = 20.687, 95% CI: 16.001–25.373); the growth coefficients of human resource indicators all increased significantly, among which the growth coefficient of health personnel was 0.429 (95% CI: 0.363–0.495), health technical personnel was 0.429 (95% CI: 0.375–0.484), licensed (assistant) physicians was 0.181 (95% CI: 0.164–0.198), and registered nurses was 0.223 (95% CI: 0.195–0.251), while the growth coefficients of indicators related to per 1,000 population ranged from 0.133 to 0.309; When the financial resource indicators were analyzed in absolute terms, all indicators of financial resources showed a rapid increasing trend: total health expenditure increased by an average of 495.552 (95% CI: 450.222-540.882) billion yuan annually, per capita health expenditure increased by an average of 342.651 (95% CI: 310.002-375.301) yuan annually, and government health expenditure increased by an average of 116.142 (95% CI: 95.688-136.596) billion yuan annually. After log-transformation of the financial resource indicators, the results showed that the annual relative growth rate of total health expenditure decreased by 0.060 (95% CI: -0.072 to -0.047), the annual relative growth rate of per capita health expenditure decreased by 0.054 (95% CI: -0.065 to -0.043), and the annual relative growth rate of government health expenditure decreased by 0.090 (95% CI: -0.104 to -0.076) after the intervention. These findings indicate that although the absolute scale of health investment continued to expand, its relative growth rate slowed down, reflecting that China’s health investment has become more rational, efficient and sustainable, which is consistent with the policy goal of pursuing high-quality development and curbing unreasonable growth. Sensitivity analyses further verified the robustness of the main findings. The implementation of the Healthy China 2030 Planning Outline is positively associated with the significant growth in the total scale of medical and health resources and the level of per capita accessibility in China, with multiple indicators having reached the 2030 targets set out in the Outline ahead of schedule. This study, based on a quasi-experimental analysis of long-term national-level data, provides robust empirical evidence for the evaluation of the policy effects of national health strategies. Looking ahead, it is necessary to dynamically adjust the policy focus, maintain sustained attention to the fiscal sustainability of health investment and the long-term mechanism for health workforce training, so as to promote the high-quality development of medical and health resources.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-026-49076-z.

Introduction

Medical and health resources, which encompass human, physical, and financial core elements, serve as the fundamental cornerstone of medical service delivery. The scale growth and spatial allocation of these resources constitute the two core dimensions of health system development. The rational allocation of medical and health resources aims to achieve an efficient and equitable match between resource supply and health service demand, which is a common challenge faced by health systems worldwide¹. Against the multifaceted backdrop of accelerated population aging, the rising burden of chronic non-communicable diseases, and the shocks from acute public health emergencies such as the COVID-19 pandemic, promoting the expansion of medical and health resource supply through systematic policy interventions has become a core priority in global public health governance^2,3. Meanwhile, the scale growth of total resource volume is both a core prerequisite and a direct manifestation of the enhancement of health service supply capacity. The World Health Organization (WHO) explicitly stated in its World Report on Ageing and Health that expanding the supply of medical resources and optimizing resource allocation patterns are key measures to address global population aging and achieve universal health coverage (UHC)⁴.

Over the past decades, China has continuously rolled out a series of medical and health policies, one of the core objectives of which is to expand the total supply of medical and health resources and enhance resource supply capacity. Despite the continuous advancement of comprehensive medical and health system reforms, the development of medical and health resources in China still faces core challenges: Driven by the combined effects of multiple factors including its vast territory, large population size, accelerated urbanization and population aging, and epidemiological transition, the overall scale of resources still cannot fully match the growing multi-level health needs of residents^5,6. Previous studies have shown that although the density of medical infrastructure and health human resources in China increased from 2010 to 2021, with the density of medical institutions per 10,000 population rising from 6.99 to 7.30, medical facilities and health workforce remain insufficient amid continuous population growth and escalating health needs⁷. In addition, following the new round of medical and health system reform, the number of health personnel per 1,000 population in hospitals and primary medical and health institutions nationwide increased from 2010 to 2021, with the total volume of medical resources rising gradually. However, compared with residents’ actual demand for medical and health services, the supply level still needs to be improved⁸.

Taken together, China’s current medical and health system architecture is facing multiple unsustainable challenges, including insufficient medical resources, and the existing supply is still far from meeting the growing practical needs of the general public for medical treatment and health promotion. On this basis, effectively addressing these challenges has become a critical priority that must be advanced at the current stage.

To address the above mentioned challenges, the Central Committee of the Communist Party of China and the State Council of the People’s Republic of China issued the Healthy China 2030 Planning Outline (hereafter referred to as “the Outline”) in October 2016. For the first time, it elevated the development of medical and health resources to the top-level design of the national strategy, explicitly put forward the core objective of expanding the total supply of medical and health resources, and set clear quantitative assessment indicators (for example, the number of licensed physicians per 1,000 population will reach 3.0 by 2030).

In addition, the Outline clearly stipulates the goal of “promoting the coordinated development of all regions across the country”, and drives the systematic transformation of the medical and health system through major projects including the development of national medical centers and the downward shift of high-quality medical resources to primary care settings SCIO. By 2030, the institutional system for promoting national health will be more robust, the development of the health sector will be more coordinated, healthy lifestyles will be widely popularized, the quality of health services and the level of health security will be continuously improved, the health industry will achieve prosperous development, and health equity will be basically realized. Over the nearly ten years since the implementation of the Outline, the Healthy China strategy has been fully implemented from concept to practice, driving profound transformation in the medical and health sector. Its core orientation has shifted from a sole focus on disease treatment to whole life cycle health management. Against this backdrop, China’s health care undertakings have developed steadily, the scale of medical and health resources has expanded significantly, and the diversified health needs of residents have been further met⁹.

Health is an essential prerequisite for the all-round development of individuals and a fundamental cornerstone for economic and social development. Abundant academic achievements have been made in research related to medical and health resources, and existing studies can be mainly categorized into the following core streams: The first stream focuses on the equity evaluation of medical and health resource distribution, with mainstream methods including the Gini coefficient and Lorenz curve, Theil index, Concentration index, and Health Resource Agglomeration Degree (HRAD). Using these methods, domestic and international scholars have extensively verified the regional disparities in the distribution of medical and health resources across different countries and regions^10,11. The second stream centers on the assessment of medical and health resource utilization efficiency, for which Data Envelopment Analysis (DEA) is the mainstream method in this field. Existing studies based on this method have analyzed the disparities in resource utilization efficiency of medical institutions across different regions and administrative levels^12,13. Third, regarding the analytical scope of existing research on China’s medical and health resources, the vast majority of analyses are conducted at the national or provincial level. Liu et al.¹⁴ evaluated the regional disparities in the individual and allocation efficiency of health resources in China, and found that the efficiency related to the number of health institutions in eastern and western China was relatively close, at 0.61 and 0.59 respectively, which was significantly higher than the value of 0.49 in central China. Ren et al.¹⁵ explored the regional disparities, spatiotemporal patterns, and development characteristics of medical resource allocation in China. The study found that intra-regional disparities in medical resource allocation tended to narrow, while inter-regional disparities tended to widen. In terms of spatial patterns, Xizang, Xinjiang, Qinghai, Ningxia, Gansu, Inner Mongolia, and Sichuan presented the spatial characteristics of High-High (HH) clusters geographically, while southeastern coastal provinces including Zhejiang, Fujian, Guangdong, and Hainan showed the spatial characteristics of Low-Low (LL) clusters. Yang et al.¹⁶ calculated the EHRA index of 22 Chinese provinces from 2011 to 2020 using the Theil index and entropy method, based on medical resource data from 287 prefecture-level cities. The results revealed substantial differences in both the static values and inter-annual variation trends of the EHRA index across different provinces.

The aforementioned studies have systematically characterized the regional distribution disparities, spatiotemporal evolution patterns, and utilization efficiency characteristics of medical and health resources in China, laying a solid academic foundation for understanding the spatial pattern of medical resources in the country. However, such studies have consistently focused on the equity of regional resource allocation and utilization efficiency. Few studies have quantitatively evaluated the long-term policy effects of national top-level health strategies on the growth of the total scale of medical and health resources at the national level, and there is even a lack of research on the identification of net policy effects based on quasi-experimental design. Overall, there are still key research gaps in the existing literature that remain to be addressed:

First, there is a misalignment in research focus. The vast majority of existing studies center on the equity of regional distribution and utilization efficiency of resources, while few have quantified the long-term cumulative effects of national top-level strategies on the scale growth of total medical and health resources, failing to answer the core question of whether the implementation of the Outline has truly driven the systematic growth of total resources at the national level. Second, there are limitations in research methodologies. Most existing evaluations rely on cross-sectional data or descriptive statistics, which can only capture the static characteristics of resources. They cannot effectively disentangle “policy-driven resource growth” from “the natural growth of resources along with socioeconomic development”, and also struggle to control for the confounding effects of external shocks such as the COVID-19 pandemic, making it impossible to achieve accurate quantification of policy effects. Third, there is a critical gap in policy evaluation. Over the nearly 9 years since the implementation of the Outline, no studies have adopted a quasi-experimental design to systematically evaluate its net effects on the scale growth of medical and health resources across China. In particular, there is a lack of research on the decomposition of policy effects based on interrupted time series (ITS) analysis. As a well-established method for health policy evaluation, ITS can effectively separate the immediate level shift effect and the long-term trend acceleration effect of the policy, and accurately identify the net impact of policy intervention. However, this method has not yet been applied to evaluate the national-level resource scale effects of the Outline¹⁷.

In the context of China’s health care development, it is imperative to be guided by the Healthy China strategy to scientifically plan medical resources and effectively expand the scale of resources, so as to better meet the medical and health needs of residents. This study aims to analyze the impact of the Healthy China strategy on the current status of health resources from the perspective of the total volume of medical and health resources in China. The findings of this study will provide valuable references for health policy formulation in China and other developing countries, and facilitate the comprehensive and effective implementation of integrated health service systems. Accordingly, to address the aforementioned research gaps, this study applies a quasi-experimental design with interrupted time series (ITS) analysis, based on 34 years of national longitudinal time series data from 1990 to 2023, to quantitatively evaluate the policy effects of the Healthy China 2030 Planning Outline on the scale growth of total medical and health resources in China. This study pre-specifies the following two formal research hypotheses:

1. The implementation of the Outline will lead to a significant short-term level shift in the total volume of medical and health resources in China, with a significantly positive immediate level change after policy implementation;

2. The implementation of the Outline will significantly accelerate the long-term growth trend of medical and health resources in China, with the growth slope of resources after policy intervention being significantly higher than the baseline growth slope before intervention.

The core focus of this study is the changes in the total scale of medical and health resources at the national level, and it does not cover the evaluation of the effects of the Outline on the coordinated development of inter-regional resource allocation. In addition, this study compares the actual 2023 values of core indicators with the 2030 target values set out in the Outline, with a view to providing rigorous empirical evidence for the dynamic optimization of the Healthy China strategy and the formulation of subsequent health policies.

Methods

Data sources

All data in this study are derived from the China Statistical Yearbook and China Health Statistics Yearbook—both are authoritative statistical materials publicly released by the National Bureau of Statistics of China (NBS) and the National Health Commission of the People’s Republic of China (NHC). The data cover core information on China’s medical and health resources across 31 provinces (autonomous regions and municipalities directly under the Central Government) of China, and belong to standardized national-level panel data. The data used in this study are all publicly available aggregated statistical data that do not involve any personal privacy information, so no de-identification is required. The data usage meets the compliance requirements of academic research.

Definition of the intervention point

The data in this study cover the time period from 1990 to 2023. The Chinese government released the “Healthy China 2030” Planning Outline in October 2016. Given the impact of this policy on the total amount of medical and health resources in China after its implementation, combined with its strategic implementation timeline, this study identifies 2016 as the main intervention time point.

Procedures

This study aims to evaluate the overall changing trends of medical and health resources in China and analyze the variation characteristics of the scale of China’s medical and health resources before and after the implementation of the “Healthy China 2030” Planning Outline. For this purpose, relevant data were extracted from public databases and analyzed.

Outcomes

Thirteen indicators were selected to evaluate the overall changing trends of China’s medical and health resources from 1990 to 2023. These indicators cover three dimensions: human resources, material resources, and financial resources, which are specified as follows:

Material resources: (1) Number of hospitals; (2) Number of hospital beds;

Human resources: 3) Health personnel: Refers to the staff and workers working in hospitals, primary medical and health institutions, specialized public health institutions, and other medical and health institutions, including health technical personnel, rural doctors and health workers, other technical personnel, administrative personnel, and logistics support personnel. All the above shall be counted as on-the-job staff and workers who receive year-end wages; 4) Health technical personnel: Includes licensed physicians, licensed assistant physicians, registered nurses, pharmacists (assistants), laboratory technicians (assistants), imaging technicians (assistants), health supervisors, and probationary medical (pharmaceutical, nursing, technical) practitioners (assistants) and other health professionals. It excludes health technical personnel engaged solely in management work (e.g., hospital directors, deputy directors, Party Committee Secretaries); 5) Licensed (assistant) physicians: Refers to personnel whose “level” in the Physician Practice Certificate is “licensed assistant physician” and who actually engage in medical treatment and preventive health care work, excluding licensed assistant physicians engaged in management work. Licensed assistant physicians are classified into four categories: clinical, traditional Chinese medicine, stomatology, and public health; 6) Registered nurses: Refers to personnel who hold a registered nurse certificate and actually engage in nursing work, excluding nurses engaged in management work; 7) Health personnel per 1,000 population = Number of health personnel / Total population at the end of the year × 1,000; 8) Health technical personnel per 1,000 population = Number of health technical personnel / Total population at the end of the year × 1,000; 9) Licensed (assistant) physicians per 1,000 population = Number of licensed (assistant) physicians / Total population at the end of the year × 1,000; 10) Registered nurses per 1,000 population = Number of registered nurses / Total population at the end of the year × 1,000.

Financial resources: 11) Total health expenditure: Refers to the total monetary amount of health resources raised from the whole society for health service activities in a country or region during a certain period, calculated using the source-of-funds method. It reflects the attention and cost-bearing level of the government, society, and individuals to health care under certain economic conditions, as well as the main characteristics of the health financing model and the equity and rationality of health financing; 12) Per capita health expenditure: The ratio of total health expenditure in a given year to the average population during the same period; 13) Government health expenditure: Refers to funds used by governments at all levels for various undertakings such as medical and health services, medical security subsidies, administration of health and medical security, and family planning services.

All the definitions of the above indicators are derived from the official definitions in the China Statistical Yearbook and China Health Statistics Yearbook.

Statistical analyses

The average annual growth rate is used to describe the quantity and changing trends of China health resources in different periods. The data start from 1990; since the government issued the “Healthy China 2030” Planning Outline in October 2016, this time series analysis takes 2016 as the node to divide the stages. The modeling periods are set as 1990–2016 and 2016–2023, and segmented regression analysis in interrupted time series analysis is adopted to explore the changing trends of medical and health resources before and after the implementation of the “Healthy China 2030” Planning Outline^18,19.In this study, residual plots are used to assess whether there is autocorrelation in the outcome indicators (Supplementary Figures S1, S2, S3, S4), and then the Durbin-Watson test is applied to verify its reliability (Supplementary Table S1), followed by adjustment using the Newey-West method²⁰.

Interrupted time series analysis is conducted using Stata 19.0 statistical software.To assess the impact of the “Healthy China 2030” Planning Outline policy on the scale development of China medical and health resources, the following segmented linear regression model is constructed²¹:

Y represents the number of hospitals, number of hospital beds, health personnel, health technical personnel, licensed (assistant) physicians, registered nurses, health personnel per 1,000 population, health technical personnel per 1,000 population, licensed (assistant) physicians per 1,000 population, registered nurses per 1,000 population, total health expenditure, per capita health expenditure, and government health expenditure. Policy is a policy dummy variable referring to the “Healthy China 2030” Planning Outline, with a value of 0 for the period 1990–2015 (before policy implementation) and 1 for the period 2016–2023 (after policy implementation). The coefficient β₀ represents the baseline level in 1990. β₁ represents the annual change before policy implementation (baseline trend/slope); β₂ and β₃ respectively represent the changes in the level and trend of outcome indicators after policy implementation (relative to β₀ and β₁), corresponding to the short-term effect and long-term effect of the intervention. T is the number of consecutive years since the start of the study, and (T – T₀) represents the number of consecutive years after policy implementation. The ε term is the residual term. To evaluate the model fitting performance, goodness-of-fit statistics including R², AIC, and BIC were calculated for each model (Supplementary Table S3). A t-test on regression coefficients was conducted to compare β₃ and β₁. Given that financial indicators exhibited an obvious exponential growth pattern, logarithmic transformation was applied to financial outcome variables prior to modeling, and the fitting performance of models before and after transformation was compared. Furthermore, to ensure the robustness of the results, sensitivity analyses were performed by setting 2017 as an alternative intervention starting point and excluding data during the COVID-19 pandemic (2020–2023). P < 0.05 indicates that the difference is statistically significant.

Results

Interrupted time series analysis of material resources for medical and health care in China

Interrupted time series analysis of the number of hospitals in China (ten thousand)

From 1990 to 2023, the number of hospitals in China showed a steady growth trend, with an average annual growth rate of 3.018% (Supplementary Table S2). Results of the interrupted time series analysis showed that after the implementation of the “Healthy China 2030” Planning Outline policy, the number of hospitals in China increased (Coefficient = 0.082; 95% CI: 0.060–0.103) (Table 1; Fig. 1A). Meanwhile, a comparative test between β₃ (post-intervention slope) and β₁ (pre-intervention slope) showed that the difference was statistically significant (P < 0.001, Supplementary Table S4).

Table 1.

Interrupted time series analysis of material resources for medical and health care in China.

	Time (β1)		Level change (β2)		Trend change (β3)		Constant (β0)
	Coef.	95% CI	Coef.	95% CI	Coef.	95% CI	Coef.	95% CI
Number of hospitals (ten thousand)	0.044*	0.033–0.056	0.535*	0.300–0.770	0.082*	0.060–0.103	1.305*	1.179–1.430
Number of hospital beds (ten thousand)	11.300*	6.870–15.730	153.371*	72.570-234.173	20.687*	16.001–25.373	133.468*	84.420-182.516

Note:^*P < 0.05.

Fig. 1.

(A) Interrupted time series analysis chart of the number of hospitals (ten thousand), 1990 to 2023; (B) Interrupted time series analysis chart of the number of hospital beds (ten thousand), 1990 to 2023. Points are observed data; colored lines are modeled data; the shaded area is the 95% confidence interval for the predicted trend line; the dashed line represents the counterfactual curve; and the vertical line represents the implementation of the “Healthy China 2030” Planning Outline.

Interrupted time series analysis of the number of hospital beds in China (ten thousand)

From 1990 to 2023, the number of hospital beds in China increased from 1.8689 million beds to 8.0045 million beds, with an average annual growth rate of 4.507% (Supplementary Table S2), and its development trend was consistent with the changing trend of the number of hospitals in China (Fig. 1B). After the implementation of the “Healthy China 2030” Planning Outline policy, the number of hospital beds showed a significant upward trend (Coefficient = 20.687; 95% CI: 16.001–25.373) (Table 1). Meanwhile, a comparative test between β₃ and β₁ showed that the difference was statistically significant (P = 0.007, Supplementary Table S4).

Interrupted time series analysis of human resources for medical and health care in China

Interrupted time series analysis of the total volume of human resources for medical and health care in China

From 1990 to 2023, the total volumes of health personnel, health technical personnel, licensed (assistant) physicians, and registered nurses in China all showed a steady growth trend (Fig. 2C, D, E and F); the total number of health personnel increased from 6.138 million in 1990 to 15.237 million in 2023, with an average annual growth rate of 2.794%, and results of the interrupted time series analysis showed that the growth coefficient was 0.135 (95% CI: 0.072–0.198) from 1990 to 2016, while after the implementation of the “Healthy China 2030” Planning Outline, the growth coefficient increased to 0.429 (95% CI: 0.363–0.495) (Table 2); the total number of health technical personnel increased from 3.898 million in 1990 to 12.488 million in 2023, with an average annual growth rate of 3.591%, and the growth coefficient was 0.133 (95% CI: 0.084–0.183) from 1990 to 2016, while after the policy implementation, the growth coefficient rose to 0.429 (95% CI: 0.375–0.484); the total number of licensed (assistant) physicians increased from 1.763 million in 1990 to 4.782 million in 2023, with an average annual growth rate of 3.070%, and the growth coefficient was 0.041 (95% CI: 0.028–0.054) from 1990 to 2016, while after the policy implementation, the growth coefficient increased to 0.181 (95% CI: 0.164–0.198); the total number of registered nurses increased from 0.975 million in 1990 to 5.637 million in 2023, with an average annual growth rate of 5.463%, and the growth coefficient was 0.075 (95% CI: 0.048–0.102) from 1990 to 2016, while after the policy implementation, the growth coefficient rose to 0.223 (95% CI: 0.195–0.251) (Table 2). Among them, the post-intervention growth coefficients of “health personnel” and “health technical personnel” were exactly the same (both 0.429). This may be due to a certain overlap in the definition of the two indicators; since health technical personnel are the core component of health personnel, the estimated values of the post-intervention slope coefficients of the two are consistent. In addition, a comparative test between β₃ and β₁ for each indicator showed that the differences were statistically significant (all P < 0.05, Supplementary Table S4).

Fig. 2.

(C) Interrupted time series analysis chart of the health personnel (million), 1990 to 2023; (D) Interrupted time series analysis chart of the number of the health technical personnel (million), 1990 to 2023; (E) Interrupted time series analysis chart of the number of licensed (assistant) physicians (million), 1990 to 2023; (F) Interrupted time series analysis chart of the number of registered nurses (million), 1990 to 2023. Points are observed data; colored lines are modeled data; the shaded area is the 95% confidence interval for the predicted trend line; the dashed line represents the counterfactual curve; and the vertical line represents the implementation of the “Healthy China 2030” Planning Outline. (G) Interrupted time series analysis chart of the number of health personnel per thousand population, 1990 to 2023; (H) Interrupted time series analysis chart of the number of health technical personnel, 1990 to 2023; (I) Interrupted time series analysis chart of the number of licensed (assistant) physicians per thousand population, 1990 to 2023; (J) Interrupted time series analysis chart of the number of registered nurses per thousand population, 1990 to 2023. Points are observed data; colored lines are modeled data; the shaded area is the 95% confidence interval for the predicted trend line; the dashed line represents the counterfactual curve; and the vertical line represents the implementation of the “Healthy China 2030” Planning Outline.

Table 2.

Interrupted time series analysis of human resources for medical and health care in China.

	Time (β1)		Level change (β2)		Trend change (β3)		Constant (β0)
	Coef.	95% CI	Coef.	95% CI	Coef.	95% CI	Coef.	95% CI
Health personnel (million)	0.135*	0.072–0.198	2.030*	0.860–3.200	0.429*	0.363–0.495	5.648*	5.004–6.292
Health technical personnel (million)	0.133*	0.084–0.183	1.604*	0.722–2.485	0.429*	0.375–0.484	3.363*	2.835–3.891
Licensed (assistant) physicians (million)	0.041*	0.028–0.054	0.479*	0.238–0.720	0.181*	0.164–0.198	1.643*	1.511–1.774
Registered nurses (million)	0.075*	0.048–0.102	0.918*	0.436-1.400	0.223*	0.195–0.251	0.648*	0.357–0.940
Health personnel per thousand population	0.063*	0.014–0.112	1.517*	0.616–2.418	0.301*	0.252–0.351	4.932*	4.417–5.447
Health technical personnel per thousand population	0.072*	0.035–0.109	1.166*	0.505–1.828	0.309*	0.265–0.353	3.057*	2.666–3.448
Licensed (assistant) physicians per thousand population	0.017*	0.007–0.028	0.361*	0.171–0.550	0.133*	0.119–0.147	1.482*	1.379–1.585
Registered nurses per thousand population	0.048*	0.029–0.068	0.651*	0.299–1.003	0.155*	0.134–0.176	0.629*	0.418–0.841

Note:^*P < 0.05.

Interrupted time series analysis of healthcare human resources allocation per 1,000 population in China

From 1990 to 2023, the trend of healthcare human resources allocation per 1,000 population in China was consistent with the change trend of the total healthcare human resources (Fig. 2G, H, I and J). The number of healthcare personnel per 1,000 population increased from 5.37 in 1990 to 10.69 in 2023, with an average annual growth rate of 2.108%; interrupted time series analysis results showed that the growth coefficient was 0.063 (95% CI: 0.014–0.112) during 1990–2016; after the implementation of the Healthy China 2030 Plan Outline, the growth coefficient increased to 0.301 (95% CI: 0.252–0.351) (Table 2). The number of health technical personnel per 1,000 population increased from 3.45 in 1990 to 8.87 in 2023, with an average annual growth rate of 2.903%; the growth coefficient was 0.072 (95% CI: 0.035–0.109) during 1990–2016; after the policy implementation, the growth coefficient rose to 0.309 (95% CI: 0.265–0.353) (Table 2). The number of licensed (assistant) physicians per 1,000 population increased from 1.56 in 1990 to 3.40 in 2023, with an average annual growth rate of 2.389%; the growth coefficient was 0.017 (95% CI: 0.007–0.028) during 1990–2016; after the policy was launched, the growth coefficient increased to 0.133 (95% CI: 0.119–0.147) (Table 2). The number of registered nurses per 1,000 population increased from 0.86 in 1990 to 4.00 in 2023, with an average annual growth rate of 4.768%; the growth coefficient was 0.048 (95% CI: 0.029–0.068) during 1990–2016; after the policy implementation, the growth coefficient rose to 0.155 (95% CI: 0.134–0.176) (Table 2). Meanwhile, a comparative test between β₃ and β₁ for each indicator showed that the differences were statistically significant (all P < 0.05, Supplementary Table S4).

Interrupted time series analysis of healthcare financial resources in China

Interrupted time series analysis of the total health expenditure in China (billion yuan)

The total healthcare expenditure in China was 74.739 billion yuan in 1990 and increased to 9057.581 billion yuan in 2023, with an average annual growth rate of 15.647%. When the absolute value of total health expenditure is adopted, China’s total healthcare expenditure showed an upward trend from 1990 to 2016 (Coefficient = 138.693; 95% CI: 93.988-183.398). Notably, following the implementation of the “Healthy China 2030” Planning Outline, total health expenditure experienced an instantaneous level increase. The counterfactual estimate of the immediate increment was 1638.176 billion yuan (95% CI: 876.875-2399.477). This estimate is the net policy effect fitted by the model, reflecting the magnitude of the increase in the actual 2016 value compared with the trend predicted value in the absence of policy intervention, rather than the actual year-on-year increase from 2016 to 2015. After the implementation of the policy, total health expenditure continued to increase at a rate of 495.552 billion yuan per year (95% CI: 450.222-540.882) (Table 3; Fig. 3K). Meanwhile, a comparative test between β₃ and β₁ showed that the difference was statistically significant (P <0.001, Supplementary Table S4). These findings indicate that total health expenditure exhibited a significant upward trend after the policy implementation.

Table 3.

Interrupted time series analysis of healthcare financial resources in China.

	Time (β1)		Level change (β2)		Trend change (β3)		Constant (β0)
	Coef.	95% CI	Coef.	95% CI	Coef.	95% CI	Coef.	95% CI
Total health expenditure (billion yuan)	138.693*	93.988-183.398	1638.176*	876.875-2399.477	495.552*	450.222-540.882	-603.670*	-1124.812--82.528
Per capita health expenditure (yuan)	100.868*	69.539–132.197	1113.420*	583.604- 1643.236	342.651*	310.002–375.301	-415.574*	-782.841 --48.308
Government health expenditure (billion yuan)	41.708*	25.545–57.871	516.711*	238.687–794.734	116.142*	95.688 -136.596	-224.351*	-415.063 --33.640

Note:^*P < 0.05.

Fig. 3.

(K) Interrupted time series analysis chart of the total health expenditure (100 million yuan), 1990 to 2023; (L) Interrupted time series analysis chart of the per capita health expenditure (yuan), 1990 to 2023; (M) Interrupted time series analysis chart of the government health expenditure (100 million yuan), 1990 to 2023. Points are observed data; colored lines are modeled data; the shaded area is the 95% confidence interval for the predicted trend line; the dashed line represents the counterfactual curve; and the vertical line represents the implementation of the “Healthy China 2030” Planning Outline.

Interrupted time series analysis of the per capita health expenditure in China (yuan)

The per capita healthcare expenditure in China was 65.40 yuan in 1990 and rose to 6425.30 yuan in 2023, with an average annual growth rate of 14.914%. From 1990 to 2016, China’s per capita healthcare expenditure showed an upward trend (Coefficient = 100.868; 95% CI: 69.539-132.197); the implementation of the Healthy China 2030 Plan Outline resulted in an immediate increase of 1113.420 yuan (95% CI: 583.604-1643.236); after the policy was launched, it increased at an annual rate of 342.651 yuan (95% CI: 310.002-375.301) (Table 3; Fig. 3L). Meanwhile, a comparative test between β₃ and β₁ showed that the difference was statistically significant (P <0.001, Supplementary Table S4).

Interrupted time series analysis of the government health expenditure in China (billion yuan)

The government healthcare expenditure in China was 18.728 billion yuan in 1990 and increased to 2414.789 billion yuan in 2023, with an average annual growth rate of 15.865%. From 1990 to 2016, China’s government healthcare expenditure showed an upward trend (Coefficient = 41.708; 95% CI: 25.545–57.871); the implementation of the Healthy China 2030 Plan Outline resulted in an immediate increase of 516.711 (95% CI: 238.687-794.734) billion yuan; after the policy implementation, it grew at an annual rate of 116.142 (95% CI: 95.688- 136.596) billion yuan (Table 3; Fig. 3M). Meanwhile, a comparative test between β₃ and β₁ showed that the difference was statistically significant (P <0.001, Supplementary Table S4).

Interrupted time series analysis of healthcare financial resources in China (log-transformed)

When growth is exponential and the model is linear, the fitted slope in the post-intervention period will absorb some of the nonlinearity, potentially overstating the apparent acceleration. Given that the financial indicators exhibited a clear exponential growth pattern, analyses were conducted after logarithmic transformation, and the model fitting performance before and after transformation was compared. The results demonstrated that the model fit remained stable before and after transformation, with R² ranging from 0.954 to 0.997 (Supplementary Table S3). The ITS analysis revealed that following the intervention, the annual relative growth rate of total health expenditure decreased by 0.060 (95% CI: -0.072 to -0.047), that of per capita health expenditure decreased by 0.054 (95% CI: -0.065 to -0.043), and that of government health expenditure decreased by 0.090 (95% CI: -0.104 to -0.076) (Supplementary Table S5, Supplementary Figure S5). These findings indicate that although the absolute scale of health input continues to expand, its relative growth rate has slowed down, reflecting a more rational, efficient and sustainable path of health investment in China. This is consistent with the policy orientation of pursuing high-quality development and curbing unreasonable growth. In addition, a comparative test between β₃ and β₁ for each indicator showed that the differences were statistically significant (all P < 0.05, Supplementary Table S4).

Sensitivity analysis

The “Healthy China 2030” Planning Outline was issued in October 2016 and was only effective for approximately two months in that year. In the main analysis of this study, 2016 was coded as the first year after policy intervention (dummy variable = 1). To ensure the robustness of the results, sensitivity analysis was performed with 2017 (the first full implementation year of the policy) as the intervention starting point. The results were consistent with those of the main analysis (Supplementary Tables S6, S7, and S8), indicating that the implementation of the Healthy China 2030 Planning Outline was associated with a significant expansion in the overall scale of medical and health resources in China.

In addition, the observation period after 2016 in this study included the COVID-19 pandemic period (2020–2023). The pandemic may have increased government health expenditure and altered the number and structure of health personnel in ways unrelated to the Healthy China 2030 Planning Outline. Therefore, sensitivity analysis was conducted again after excluding data from 2020 to 2023. The results showed that China’s medical and health resources still exhibited a significant and robust growth trend from 2016 to 2019 (Supplementary Tables S9, S10, and S11).

Discussion

This study conducts a national-level analysis in China, and applies interrupted time series (ITS) analysis based on 34 years of time series data spanning 1990 to 2023, to investigate the association between the Healthy China 2030 Planning Outline and the scale growth of medical and health resources in China. The study findings reveal that following the implementation of the Outline, the growth trends of all 13 core indicators of national medical and health resources presented statistically significant positive changes. These results provide robust empirical evidence for evaluating the implementation effects of the national health strategy and deepening the optimization of subsequent health policies.

Characteristics of changes in the total volume of medical and health resources in china before and after the implementation of the healthy china 2030 strategy

Sustained improvement in the supply capacity of physical medical service infrastructure

From 1990 to 2023, the number of hospitals and hospital beds in China showed a long-term steady growth trend. Following the implementation of the Outline, the growth trends of both indicators were significantly strengthened, with a trend change coefficient of 0.082 for the number of hospitals and 20.687 for the number of hospital beds. This change is consistent with the implementation timeline of the special projects proposed in the Outline, including the development of regional medical centers and the upgrading and renovation of county-level hospitals²², and aligns with the direction of findings from similar domestic studies²³. The growth in the number of hospitals lays a fundamental foundation for optimizing the spatial accessibility of medical services, while the expansion of hospital bed capacity provides physical support for alleviating the imbalance between supply and demand for inpatient services, and consolidates the material basis for the bottom-line guarantee capacity of the medical service system²⁴.

Dual growth in the total volume and per capita level of health human resources

Health human resources are the core pillar for ensuring the quality of medical services and a key embodiment of the high-quality development of the health care sector²⁵. The results of this study show that China’s health human resources maintained a continuous growth trend from 1990 to 2023, and the growth trends of all indicators were significantly strengthened after the implementation of the Outline, presenting the characteristics of dual growth in both total volume and per capita level.

In terms of total volume: the average annual growth rates of the total number of health personnel, health technicians, licensed (assistant) physicians, and registered nurses reached 2.794%, 3.591%, 3.070%, and 5.463%, respectively. Following the implementation of the Healthy China 2030 strategy, the growth coefficients of all indicators increased significantly (e.g., the trend change coefficient of health technicians rose from 0.133 to 0.429), which is consistent with the findings of Chen et al. in domestic related research²⁶. This change is highly aligned with the implementation of supporting policy tools under the Outline, including the Special Program for Health Talent Training and Job Transfer Training for General Practitioners, and existing studies have confirmed that this strategy has significantly increased investment in the development of the health workforce²⁷. In terms of per capita level: the number of health technicians per 1,000 population increased from 3.45 in 1990 to 8.87 in 2023, with its trend change coefficient rising from 0.072 before policy intervention to 0.309 after intervention; the trend change coefficient of registered nurses per 1,000 population rose from 0.048 before intervention to 0.155 after intervention. The improvement in per capita resource availability has laid a quantitative foundation for enhancing the universal accessibility of medical services²⁸. It should be noted that the analysis of per capita indicators in this study is based on national aggregated data, which can only reflect the changes in the overall national level of per capita accessibility of health human resources, and cannot characterize the inter-provincial and inter-regional disparities in resource distribution.

In addition, this study found that the average annual growth rate of the total number of registered nurses (5.463%) was significantly higher than that of licensed (assistant) physicians (3.070%), and this difference carries important policy and health economic implications. This growth trend has driven the continuous optimization of China’s doctor-nurse ratio, which is consistent with the core objectives of “optimizing the structure of medical and nursing staff and improving the supply capacity of nursing services” proposed in the Outline. Meanwhile, it is fully aligned with the global initiative of the World Health Organization (WHO) on strengthening the primary health care system and enhancing primary care nursing capacity²⁹. The faster expansion of the nursing workforce can not only address the long-standing shortfall in the supply of nursing services in China, but also provide human resource support for core primary care scenarios, including the development of the hierarchical diagnosis and treatment system, elderly health services, and chronic disease management, serving as a critical foundation for the high-quality advancement of the health service system.

Finally, the results of this study indicate that multiple core indicators of health resources have met or exceeded the 2030 targets set out in the Outline ahead of schedule. Specifically, the number of licensed (assistant) physicians per 1,000 population in China reached 3.40 in 2023, which significantly exceeded the 2030 target of 3.0 set in the Outline, 7 years ahead of the target completion deadline. Indicators including the number of registered nurses per 1,000 population and the number of hospital beds per 1,000 population have also approached or exceeded the 2030 expected targets. This finding is the core policy-relevant conclusion of this study, and provides quantitative empirical evidence for evaluating the implementation effectiveness of the Outline.

Continuous optimization of the input intensity and structure of health financial resources

Changes in health financial resources are a direct reflection of the implementation effectiveness of input policies in the health care sector. In terms of input scale: total health expenditure in China increased from 74.739 billion yuan in 1990 to 9,057.581 billion yuan in 2023, with an average annual growth rate of 15.647%. Following the implementation of the Outline, total health expenditure not only presented a significant immediate level shift, but also sustained acceleration in its long-term growth trend, reflecting a marked increase in the investment of social resources in the health sector. This finding is consistent with the results of similar domestic studies³⁰. In terms of input structure: the average annual growth rate of government health expenditure from 1990 to 2023 reached 15.865%, slightly higher than that of total health expenditure. Meanwhile, a significant positive level change was observed after the implementation of the Outline, which aligns with the policy orientation of “strengthening the government’s responsibility for health input” proposed in the Outline.

From a health economics perspective, the consistently higher growth rate of government health expenditure than that of total health expenditure will drive a steady increase in the share of public financing in China’s health financing structure, which carries explicit implications for health equity. Existing studies have confirmed that tax-based government public health financing has a stronger income redistribution effect and progressivity than out-of-pocket health expenditure. It can effectively reduce the economic burden of disease among low-income groups, narrow the gap in health service utilization between different income groups, and advance the realization of health equity³¹. This finding echoes the core positioning of the Outline of “integrating health into all policies and promoting health equity”, and also provides empirical support for the continuous optimization of China’s health financing structure. Meanwhile, the characteristic observed in this study that “sustained government health input drives the synchronous and stable growth of the three major categories of medical and health resources, namely physical, human and financial resources”, conforms to the dynamic law of Wagner’s Law in the context of middle-income countries. That is, with the continuous improvement of national income levels, government public expenditure in people’s livelihood sectors such as health and social services will show a faster growth trend, and this classic theory provides a core theoretical anchor for the findings of this paper³². The stable growth of government health expenditure not only provides stable financial guarantee for the development of medical and health resources, but also lays an institutional foundation for guiding resources to weak areas through measures such as central fiscal transfer payments to the central and western regions and subsidies for primary medical equipment³³.

The policy intervention period of this study (2016–2023) largely overlapped with the COVID-19 pandemic period (2020–2022), and thus the potential impact of the pandemic on health financial resource indicators requires special clarification: national government health expenditure jumped from 180.2 billion yuan in 2019 to 219.4 billion yuan in 2020, with a year-on-year increase of 22% in a single year. This part of the growth mainly came from emergency medical resource input related to pandemic prevention and control, rather than the routine development of medical resources driven by the Outline. This study has verified the robustness of the core results through sensitivity analysis excluding data from the pandemic years (2020–2023). The results showed that the implementation of the Outline still had a significant positive association with the long-term growth trend of health financial resources, ruling out the confounding effect of the pandemic on the core conclusions.

Correlation characteristics between the policy framework of the healthy china 2030 strategy and resource growth

“Target anchoring” of top-level design and national policy coordination

One of the core characteristics of the Outline is that it incorporates the development of medical and health resources into the top-level planning of the national health strategy. By clarifying unified national development goals and quantitative standards, it provides a consistent framework and guidance for the formulation of supporting policies across all provinces and departments³⁴. For example, in response to the inadequacy of medical resources, the Outline defines the goal of “the downward shift of high-quality medical resources to primary care settings” and promotes hospitals to establish a paired assistance mechanism. In view of the supply gap of health human resources, it puts forward specific quantitative targets such as “the number of general practitioners per 1,000 population will reach 3.5 by 2030”. This is consistent with the research findings and policy orientation in the field of domestic health human resources³⁵. This nationally unified “target anchoring” framework is highly correlated with the increased consistency in the growth trend of medical and health resources at the national level after 2016, and provides top-level support for reducing the fragmentation of local reforms and forming a unified national orientation for resource development.

Targeted alignment between supporting policy instruments and resource growth

To address the core shortfalls in the development of medical and health resources, the Outline has formulated a series of implementable special policy instruments, which present a targeted correspondence with the synchronous growth of the three core categories of resources (physical, human and financial resources) observed in this study. For the shortfalls in medical physical infrastructure supply, it has rolled out special projects including the Regional Medical Center Construction Program and the Standardized Construction of County-Level Hospitals³⁶. For the supply bottlenecks of health human resources, it has introduced talent development policies such as the Rural Order-Oriented Medical Student Training Program and the Improvement of the Standardized Residency Training System. For financial security, it has clarified the core orientation of “strengthening the government’s responsibility for health input”, improved the responsibility mechanism for health expenditure between central and local fiscal authorities, and guided social capital to participate in the development of the health sector, thus forming a government-led, multi-stakeholder input framework. Existing studies have confirmed that systematic supporting health policies are a critical foundation for driving the steady scale growth of medical resources. The synchronous strengthening of growth trends across all types of resources after 2016 observed in this study is highly aligned with the implementation cycles of the aforementioned policy instruments^37,38.

Policy implications and future prospects under the current scale of medical resources

The findings of this study show that the implementation of the Outline is positively associated with the significant growth in the total scale of medical and health resources in China, with multiple core indicators having met or exceeded the 2030 targets ahead of schedule, which lays a solid resource foundation for the development of China’s medical service system. Combined with the study findings and the practical needs of the development of the health care sector, the following policy implications are proposed: First, continuously consolidate the nationally unified policy framework of target anchoring, and dynamically adjust policy priorities based on the completion of core indicators. For indicators that have exceeded the 2030 targets ahead of schedule, the policy focus can be shifted from “total scale expansion” to “structural optimization and quality improvement”. For indicators that still fall short of the targets, targeted policy support should be continuously strengthened to ensure the smooth completion of the 2030 targets^39–41.

Second, attach high importance to the fiscal sustainability of medical and health resource development, and consolidate the long-term security framework for health investment. The findings of this study show that the average annual growth rate of China’s government health expenditure from 1990 to 2023 reached 15.865%, which was significantly higher than the average annual growth rate of GDP over the same period. China is currently in a critical stage of slowing economic growth and accelerated demographic transition. On the one hand, the deepening population aging will continuously drive up the social demand for medical and health services in the long run, and the rigid pressure on medical insurance funds and public health expenditure will continue to increase. On the other hand, the shrinking size of the working-age population will impose a long-term constraint on the fiscal tax base, posing challenges to the long-term sustainability of the historical trajectory of rapid growth in government health input. This is the core issue that determines whether the resource growth trend identified in this study can be extended to 2030 and beyond. On this basis, it is necessary to scientifically evaluate the medium- and long-term growth space of government health expenditure. While stabilizing the government’s responsibility for health input, priorities should be given to optimizing the structure of health input, focusing targeted investment on core shortfall areas such as primary health care and public health, improving the utilization efficiency and cost-effectiveness of fiscal funds, and establishing a long-term health input mechanism aligned with the level of economic and social development, demographic changes, and residents’ health needs.

Third, improve the long-term security mechanism for the supply of health human resources, and address the long-term constraints on medical talent development. This study confirms that the number of physicians and nurses in China has achieved rapid growth following the implementation of the Outline. However, medical talents are characterized by a long training cycle and high professional entry threshold in the industry, and there is a significant lag effect in the large-scale training of clinical medical and nursing personnel. The rapidly expanding scale of medical talent training may lead to potential downstream issues, including the control of training quality and imbalance in regional distribution. On this basis, it is essential to improve the long-term security mechanism for health human resource supply: on the one hand, scientifically predict the medium- and long-term demand for health human resources, plan the scale and structure of medical talent training in advance based on demographic changes and epidemiological transition, refine the medical talent training system and the Standardized Residency Training System, strictly control training quality while stabilizing the total volume of talent supply, and guarantee the professional competence of the clinical talent team from the source. On the other hand, in response to issues such as the structural imbalance of the physician workforce and insufficient retention of primary care physicians, improve occupational security and incentive mechanisms to guide high-quality talents to flow to primary care settings and less developed regions. Meanwhile, continuously consolidate the growth achievements of the nursing workforce, further optimize the doctor-nurse structure, and strengthen the core role of nursing staff in key areas including primary health care, chronic disease management, and elderly health services, which aligns with the global and national development direction of strengthening primary health care systems.

Fourth, promote the transformation of medical resource development from “total volume expansion” to “structural optimization”. In view of the growth differences across the three categories of human, physical and financial resources identified in this study, differentiated supporting policies should be formulated to avoid one-size-fits-all policy design, and targeted measures should be implemented to address the shortfalls in the resource structure. Meanwhile, a dynamic monitoring mechanism for the effectiveness of policy implementation should be established to timely adjust policy priorities according to changes in resource dynamics, so as to promote the precise matching between medical resources and residents’ health needs. In addition, it is necessary to continuously optimize the health financing structure, steadily increase the share of government health expenditure, give full play to the income redistribution effect of public financing, further reduce the economic burden of disease on residents, and advance the realization of health equity.

Conclusion

This study takes the whole of China as the evaluation scope, and for the first time from a systematic national-level perspective, applies interrupted time series (ITS) analysis based on 34 years of time series data from 1990 to 2023, to systematically examine the association between the Healthy China 2030 Planning Outline and the scale changes of medical and health resources in China at the national level. The study covers a total of 13 core indicators across three dimensions: physical resources, human resources, and financial resources. Based on the ITS analysis of the 34-year longitudinal data, the results show that the implementation of the Outline is strongly and positively associated with the significant positive growth in the total scale and per capita accessibility of medical and health resources in China. It has driven the synchronous expansion of physical, human, and financial resources as well as strengthened investment in these areas, laying a solid resource foundation for advancing universal health coverage. Specifically, the number of licensed (assistant) physicians per 1,000 population in China reached 3.40 in 2023, exceeding the 2030 target of 3.0 set out in the Outline 7 years ahead of schedule. Multiple core indicators, including the number of registered nurses per 1,000 population and the number of hospital beds per 1,000 population, have also approached or met the 2030 expected targets, providing direct empirical evidence for the quantitative evaluation of the implementation effectiveness of the Outline.

The national-scale, long-cycle dynamic analysis perspective adopted in this study addresses key limitations of existing relevant research. Most existing studies rely on cross-sectional data, which can only capture the static characteristics of resources at a specific time point and fail to reflect the long-term dynamic trend of national medical and health resources before and after policy implementation. Most studies are limited to descriptive statistical analysis, lacking a systematic dissection of the logical association between national top-level health strategies and changes in the scale of national resources. Furthermore, most focus on partial analyses at the provincial level and below, making it difficult to form systematic nationwide conclusions due to sample scope constraints. By integrating the research dimensions of long-cycle dynamic tracking, policy effect correlation analysis, and nationwide overall scale, this study provides a more comprehensive analytical framework for accurately capturing the actual impact of the national health strategy on the total scale of China’s medical resources, and also offers a useful complementary approach for evaluating the effectiveness of health resource policies at the national strategic level.

Although the implementation of the Outline is positively associated with the significant growth in the scale of medical and health resources in China, there are still urgent shortfalls to be optimized in the current development of medical resources. The expansion of total resource volume is not equivalent to structural optimization, efficiency improvement, and equitable distribution, and there is still room for improvement to meet the systematic development goals of the Healthy China strategy. Looking ahead, it is necessary to further strengthen the target-oriented role of the Outline, dynamically adjust policy priorities based on the completion of core indicators, and promote the transformation of medical resource development from “total scale expansion” to “structural optimization, quality improvement, and equitable distribution”.

Limitations

Several limitations of this study should be acknowledged. First, constrained by the availability of long-term continuous data, this study only focuses on the overall changes in the total volume and per capita scale of medical and health resources at the national level. It cannot conduct sub-regional interrupted time series (ITS) analysis for eastern, central, and western China, nor can it reflect the disparities in the equity of inter-regional resource distribution, the impact of the policy on coordinated regional development, and the regional heterogeneity characteristics of resource growth. This is the primary limitation of this study. Second, the single-group ITS design adopted in this study did not set a parallel control group. Therefore, it cannot completely rule out the possibility that the accelerated growth of medical and health resource indicators after 2016 was driven by the combined shocks of inherent growth momentum, demographic transition, and concurrent medical and health policies, which may lead to confounding bias¹⁸. Concurrent policies focusing on medical resources and hospital reform, including the expansion of the comprehensive reform of urban public hospitals in April 2016 and the 13th Five-Year Plan for Deepening the Medical and Health Care System Reform issued in December 2016, may have affected the growth trend of health resources, leading to a risk of overestimating the policy intervention effect in this study⁴². Third, this study only evaluated the effects of approximately 7 years after the implementation of the Outline. The long-term effects of the policy need to be verified with a longer observation period, and there are limitations in the long-term stability of the results. Fourth, the policy intervention period largely overlapped with the COVID-19 pandemic period, and emergency medical investment may have introduced confounding effects. Although the robustness of the results was verified through sensitivity analysis, the interpretation of trends after 2020 should be made with caution. Fifth, this study only focuses on the supply scale of medical resources, and does not include indicators such as medical service output, operational efficiency, and population health outcomes. Thus, it cannot confirm the actual impact of resource expansion on residents’ health. Sixth, the Newey-West adjustment applied in this study can only correct the standard errors of regression coefficients, but cannot change the point estimates. If the model’s specification of the autocorrelation structure of the time series is inappropriate, it may still lead to bias in statistical inference.

To address the above limitations, future studies should be deepened and improved in the following directions: overcome data limitations to conduct supplementary analysis of the heterogeneity of policy effects at the provincial and sub-regional levels, extend the evaluation period and isolate the short-term shock of the COVID-19 pandemic to verify the long-term stability of the results; combine authoritative micro-survey data to address the limitation of ecological fallacy, and link macro-level resource supply with individual healthcare-seeking behavior; optimize the quasi-experimental study design by incorporating a control group to isolate the confounding interference from concurrent policies, so as to improve the rigor of causal identification; expand the analytical dimensions by including indicators of resource utilization efficiency and population health outcomes to complete the research and analysis framework; optimize the time series statistical analysis strategy and conduct multi-method robustness tests to address the inherent limitations of existing statistical methods, with a view to providing empirical evidence for the in-depth implementation of the Healthy China 2030 Planning Outline.

Electronic Supplementary Material

Below is the link to the electronic supplementary material.

Author contributions

N.D.D.A., B.H.G.Y., D.M.H., and Y.S. participated in the research design. N.D.D.A. and B.H.G.Y. were responsible for data collection and organization. N.D.D.A. and B.H.G.Y. prepared and analyzed the data. N.D.D.A. and B.H.G.Y. jointly wrote the initial draft of the paper. N.D.D.A., B.H.G.Y., D.P.L., X.Y.W., M.Y.L., H.G., J.T.Z., D.M.H., and Y.S. revised the manuscript and provided crucial academic content. D.M.H. and Y.S.

Funding

This work was supported by a grant from the 2025 Major Science and Technology Special Project Fund of Autonomous Region (2025A03015)), National Natural Science Foundation of China No. This work was supported by a grant from the 2025 Major Science and Technology Special Project Fund of Autonomous Region (2025A03015), National Natural Science Foundation of China No. 82430035, National Key Research and Development Program of China. Nos.2021YFF0702303.2024YFC2511101.2023YFE0203200, Foundation for Innovative Research Groups of Hubei Province No. 2023AFA038, Fundamental Research Funds for the Central Universities No.2024BRA019.

Data availability

The datasets used and/or analysed during the current study available from the corresponding author on reasonable request.

Declarations

Competing interests

The authors declare no competing interests.

Ethics approval and consent to participate

This study is an observational study based on secondary analysis of publicly available aggregated administrative data obtained from official and authoritative statistical yearbooks, including the China Health Statistical Yearbook and the China Statistical Yearbook. No ethical committee approval or individual informed consent was required for this study.

Data integrity statement

Within the 1990–2023 study period of this research, there were no missing data for all 13 analytical indicators. The dataset has sound integrity, and fully meets the methodological requirements of the time series analysis in this study.