The Universal Zero Markup Drug Policy and Gastric Cancer Hospitalization Expenses: An Analysis of Trends and Influencing Factors in Shanghai from 2014 to 2021

The Universal Zero Markup Drug Policy and Gastric Cancer Hospitalization Expenses: An Analysis of Trends and Influencing Factors in Shanghai from 2014 to 2021 | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Universal Zero Markup Drug Policy and Gastric Cancer Hospitalization Expenses: An Analysis of Trends and Influencing Factors in Shanghai from 2014 to 2021 Yichun Gu, Jiajun Hao, Da He, Hui Sun, Xin Cui, Wenqi Tian, Yulin Zhang, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3781711/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 22 Apr, 2025 Read the published version in BMC Health Services Research → Version 1 posted 4 You are reading this latest preprint version Abstract Background The increasing hospitalization expenses for Gastric Cancer (GC) cause a serious economic burden on society. Although the Chinese government has implemented the Universal Zero Markup Drug Policy (UZMDP) to control the growth of hospitalization expenditures, they remain a rising trend. It’s crucial to identify the factors influencing the hospitalization expenses of GC patients. This study aimed to analyze the trends and factors influencing hospitalization expenses of GC patients in Shanghai from 2014 to 2021. Methods Study data were sourced from the Health Network of Shanghai Economic Information Center. We employed interrupted time series analysis (ITSA) to analyze the trends in various medical expenditures before and after the implementation of UZMDP. The degree of association between various medical expenditures and hospitalization expenditures of GC patients was calculated by using the new gray relational analysis (GRA). Furthermore, we used multiple linear regression to identify the influencing factors of hospitalization expenses for GC patients. Results Our study included a total of 23,335 participants. The ITSA results showed an increasing trend in hospitalization expenses following the implementation of UZMDP. Drug expenses decreased instantaneously with the implementation of UZMDP, but subsequently began to trend upwards. After UZMDP, the expenses of medical consumables, examinations, and healthcare services all showed an upward trend. The new GRA indicated that the influencing factors of hospitalization expenses were drug expenses, consumable expenses, healthcare service expenses, and examination expenses in sequence. Multiple linear regression analysis showed that GC patients aged 60 or below had lower hospitalization expenses (Coefficient=-780.06, P = 0.0398). However, factors influencing increased hospitalization expenses included longer length of stay (Coefficient = 1753.01, P < 0.001), surgeries (Coefficient = 29047.26, P < 0.001), and hospitalization in the tertiary hospitals (Coefficient = 25485.19, P < 0.001) or secondary hospitals (Coefficient = 17755.12, P < 0.001). Conclusions Hospitalization expenses of GC patients in Shanghai have been rising annually from 2014 to 2021. Despite the implementation of the UZMDP policy, drug expenses remain a major factor in escalating hospitalization expenses. The hospitalization expenses of GC patients are significantly influenced by several factors, including the demographic characteristics of patients, the severity of diseases, and the levels of hospitals. These findings provide a scientific basis for effectively managing the hospitalization expenses of GC. gastric cancer expenditures hospitalization interrupted time series analysis new gray relational analysis universal zero markup drug policy Figures Figure 1 Figure 2 Background Gastric cancer (GC) represents a prevalent malignancy within the gastrointestinal tract, characterized by elevated morbidity, substantial mortality, and an unfavorable prognosis 1 , 2 . According to GLOBOCAN 2020, GC ranks fifth globally among prevalent cancers and stands as the fourth leading cause of cancer-related mortality 3 . The year 2020 witnessed an incidence of approximately 1.1 million new GC cases and an estimated 770,000 fatalities 3 . Regional heterogeneity is discernible, with East Asia contributing substantially to the global incidence, encompassing 60%. Notably, China emerges as the primary contributor, documenting 478,000 cases and 373,000 associated deaths in 2020 4 . Despite recent declines in GC morbidity and mortality within the Chinese population, challenges persist, propelled by the expansive demographic and suboptimal survival rates. Sustained multidisciplinary initiatives are imperative for the efficacious prevention and treatment of GC within this intricate epidemiological landscape 4 . GC ranks second in incidence rate and third in mortality rate of malignant tumors in China 5 . The annual treatment expense for GC in China was approximately 23.5 billion yuan in 2018, ranking third among all tumors and significantly impacting the medical insurance fund 6 . GC imposes a substantial disease and economic burden on society, placing a considerable financial strain on families and individuals. Due to the insidious nature of early symptoms, most patients receive a diagnosis at an advanced stage, resulting in high treatment costs 7 , 8 . A U.S. study found that the 10-month treatment cost for GC patients was 96 times higher than that for non-cancer patients, with hospitalization expenses being the primary contributor 9 . In China, the average per capita medical cost for GC patients in 2018 was nearly 22,000 yuan, ranking second only to lung cancer and primarily attributed to hospitalization expenses 6 . Therefore, monitoring hospitalization expenses for GC patients and associated influencing factors is necessary to control unreasonable increases in medical costs and reduce the economic burden on society, families, and individuals. GC is a disease with high morbidity in the elderly 10 . In Shanghai, a pioneer in China's aging population, GC stands as one of the most prevalent malignant tumors 11 , 12 . In 2016, GC ranked fourth in the standardized incidence rate at 15.85 per 100,000 individuals within the city's cancer incidence spectrum 11 . Despite its prevalence, research on GC patient hospitalization expenses and influencing factors in Shanghai remains scarce. Moreover, Shanghai implemented comprehensive healthcare system reforms in 2017, including the introduction of the universal zero markup drug policy (UZMDP) to alleviate financial burdens on patients 13 . However, there is limited investigation into the impact of these reforms on GC patient hospitalization expenses in Shanghai. Hence, this study aims to explore the trends in hospitalization expenses for GC patients in Shanghai from 2014 to 2021. Utilizing interrupted time series analysis (ITSA) and a novel gray relational analysis model (GRA), the investigation specifically concentrates on delineating changes in GC patient hospitalization expenses pre- and post-comprehensive healthcare reforms. Emphasis is placed on identifying the primary factors associated with these variations. The objective is to provide a scientific foundation for judiciously controlling hospitalization expenses among GC patients, thus alleviating the medical-economic burden on individuals and substantively contributing to the advancement of healthcare system reform within the medical and pharmaceutical sectors. Methods Data source The study data were acquired from the Health Network of the Shanghai Economic Information Center, encompassing the Health Data Reporting System, Hospital Information System (HIS), and Laboratory Information Management System (LIS). Patient case data from the initial page were extracted from the Health Data Reporting System, while information regarding examination and testing expenses originated from the LIS. Other relevant data were retrieved from the HIS. This comprehensive dataset forms the basis for our analytical framework, facilitating a nuanced exploration of factors influencing hospitalization expenses for gastric cancer patients in Shanghai from 2014 to 2021. Study participants The study enrolled individuals diagnosed with gastric cancer (GC) in Shanghai from 2014 to 2021. Following a rigorous screening process to eliminate missing values, outliers, and duplicate entries, a total of 23,335 study subjects were ultimately included in the analysis. Measures of independent variables The main independent variables included in this study were sex (man; women), age (0–45 years; 45–60 years; >60 years), length of hospitalization stay(0–7 days; 8–15 days; 16–30 days; >30 days), surgery, medical insurance, and the level of the hospital attended (unclassified hospital; community healthcare center; primary hospital; secondary hospital; tertiary hospital). Measures of dependent variables Hospitalization expenses were the outcome variable of interest for the study, which mainly include the expenses of drugs, medical consumables, examinations (testing, radiology, and laboratory testing), medical services (beds, consultation, surgery, blood transfusion, oxygen, nursing, and other costs) and other medical costs. Statistical analysis The study initially utilized frequencies and percentages to outline the basic characteristics of the study subjects. Subsequently, ITSA was employed to analyze hospitalization expense trends before and after the UZMDP implementation. ITSA recognized for its ability to discern instantaneous and trend changes in interventions, facilitated assessing intervention effects by examining data at multiple time points 14 . In this study, the full enactment of the UZMDP in Shanghai in January 2017 served as the intervention point (Inter-UZMDP). The period before January 2017 was termed the Pre-UZMDP phase, and after January 2017 was the Post-UZMDP phase. A new GRA gauged the association strength between healthcare expenditures and hospitalization expenses for gastric cancer (GC) patients. This GRA analysis computed correlation coefficients and the degree of correlation by directly assessing the absolute difference between individual comparison and reference series 15 . Total hospitalization expenses were the reference series, and different healthcare costs were the comparison series. Influencing factors on hospitalization expenses were determined through Multiple Linear Regression Analysis. Non-statistically significant variables were gradually eliminated using backward regression to construct the final model. Microsoft Office Excel 2016 was used for database establishment and data cleaning, while R 4.3.1 software performed the analyses. Statistical significance was set at a two-sided P-value less than 0.05. Results A total of 16,109 male and 7,226 female patients with GC in Shanghai from 2014 to 2021 were included in this study. The findings indicated that over 68% of GC patients were aged 60 or older, with almost 50% having a hospital stay of 8 to 15 days. Additionally, more than half of the patients had undergone surgery and held health insurance, while the majority sought treatment at tertiary care hospitals. Detailed participant characteristics are presented in Table 1 , and specific information for each study year is available in Supplement Table 1. Table 1 Baseline characteristics of the study participants Characteristic Numbers Percent Sex Male 16109 69.03% Female 7226 30.97% Age group 0~45 1314 5.63% 45~60 5941 25.46% >60 16080 68.91% Length of Stay (days) 0~7 4507 19.31% 8~15 10847 46.48% 16~30 6553 28.08% >30 1424 6.10% Surgery Yes 18507 79.31% No 4828 20.69% Medical Insurance Yes 15707 67.31% No 7628 32.69% Hospital Level Tertiary 18073 77.45% Secondary 4825 20.68% Primary 23 0.10% Community 118 0.51% Others 296 1.27% Total 23335 As shown in Table 2, spanning 2014 to 2021, the overall hospitalization expenses for gastric cancer (GC) patients exhibited an upward trend. This encompassed costs for medical consumables, examinations, and healthcare services, while a contrasting downward trajectory was noted for pharmaceutical expenses. Particularly post the Universal Zero-Markup Drug Policy (UZMDP), there was a marked 9.03% reduction in total drug expenses. Specific details are available in Supplement Table 2. Table 2 Total hospitalization and principal medical expenses for gastric cancer patients in Shanghai from 2014 to 2021 Year Source of Expenses Total Hospitalization Expenses Total Drug Expenses Total Consumable Expenses Total Examination Expenses Total Healthcare Service Expenses Expenses YoY Growth, % Expenses (%) a YoY Growth, % Expenses (%) a YoY Growth, % Expenses (%) a YoY Growth, % Expenses (%) a YoY Growth, % 2014 61986.76 27111.69 (43.74%) 14780.9 (23.85%) 1453.36 (2.34%) 6608.86 (10.66%) 2015 41977.47 -32.28 15486.17 (36.89%) -42.88 11682.12 (27.83%) -20.96 1367.27 (3.26%) -5.92 5150.29 (12.27%) -22.07 2016 44378.73 5.72 14559.33 (32.81%) -5.98 12960.18 (29.20%) 10.94 2763.79 (6.23%) 102.14 6394.14 (14.41%) 24.15 2017 42636.68 -3.93 12017.91 (28.19%) -17.46 13241.05 (31.06%) 2.17 2539.87 (5.96%) -8.10 6807.71 (15.97%) 6.47 2018 46703.57 9.54 12744.82 (27.29%) 6.05 15075.2 (32.28%) 13.85 3116.86 (6.67%) 22.72 7267.1 (15.56%) 6.75 2019 49572.90 6.14 12623.47 (25.46%) -0.95 16526.41 (33.34%) 9.63 3962.06 (7.99%) 27.12 7842.49 (15.82%) 7.92 2020 52744.66 6.40 14457.64 (27.41%) 14.53 16080.86 (30.49%) -2.70 4140.1 (7.85%) 4.49 8191.78 (15.53%) 4.45 2021 56378.11 6.89 13235.34 (23.48%) -8.45 19205.21 (34.07%) 19.43 4966.58 (8.81%) 19.96 9355.9 (16.59%) 14.21 Notes: YoY: Year over Year; a refers to the proportion of the specific expenses within the Total Hospitalization Expenses. Table 3 displays the segmented regression outcomes from ITSA. The instantaneous shift in total hospitalization expenses lacked statistical significance post the UZMDP implementation. However, the average total hospitalization expenses exhibited a significant upward trend over time (P<0.01), manifesting a monthly increase of approximately 271.73 yuan, as illustrated in Figure 1 . Conversely, drug expenses underwent an immediate and marked reduction post-UZMDP, followed by a sustained increase. Consumables expenses showed no significant transitory alteration but demonstrated a monthly rise of about 106.41 yuan post-UZMDP. Meanwhile, expenses related to examinations and healthcare services consistently ascended post-UZMDP, as depicted in Figure 2 . Table 3 The impact of the universal zero mark-up drug policy on changes in medical costs for gastric cancer patients Source of Expenses Effect of Pre-UZMDP Immediate effect of Inter-UZMDP Sustained effect of Post-UZMDP Coefficient P value Coefficient P value Coefficient P value Hospitalization Expenses 72.69 0.040 -2900.01 0.059 199.04 0.029 Drug Expenses -113.21 0.007 -1610.64 0.028 143.37 0.001 Consumable Expenses 64.76 0.058 -394.20 0.051 41.65 0.0236 Examination Expenses 101.3 <0.001 -1051.07 <0.001 -52.01 <0.001 Healthcare Service Expenses 70.74 <0.001 -328.9 0.222 -21.83 0.171 Table 4 presents the outcomes of the new GRA, illustrating the correlation degree and relational order of average expense levels for each item. The study underscores that drug and consumable expenditures are paramount determinants significantly influencing hospitalization expenses for GC patients in Shanghai from 2014 to 2021. Their correlation is notably higher than other variables, with healthcare services expenses and examination-related expenditures subsequently following, albeit to a lesser degree. Table 4 The results of the new grey relational analysis Source of Expenses Grey relational grade Ranking results of GRA Total Drug Expenses 0.9695 1 Total Consumable Expenses 0.9669 2 Total Healthcare Service Expenses 0.8517 3 Total Examination Expenses 0.8005 4 After verification, total hospitalization expenses demonstrated a normal distribution. Univariate analysis identified significant differences in expenses based on gender, age, hospitalization duration, surgery presence, health insurance, and hospital level ( Supplement Table 3 ). All variables were incorporated into a multiple linear regression model, with a backward elimination process refining the included variables, as detailed in Table 5 . Findings indicated a positive correlation between length of hospitalization and incurred expenses. Additionally, GC patients undergoing surgery experienced higher expenses than their non-surgical counterparts. Tertiary and secondary care hospitalizations for GC incurred higher expenses compared to community health service centers and primary care hospitals. Notably, hospitalization costs were lower for those aged ≤60 than those aged >60. Table 5 Multivariable analyses of hospitalization expenses for gastric cancer patients in Shanghai from 2014 to 2021 Variables Coefficient Std.Error t value P value Constant -19117.69 1394.83 -13.706 <0.001 Sex (Female) Male -3411.83 376.87 -9.053 60) ≤60 -780.06 379.39 -2.056 0.0398 Length of Stay 1753.01 12.18 143.904 <0.001 Surgery (No) Yes 29047.26 479.02 60.639 <0.001 Hospital Level (Community and Primary) Tertiary 25485.19 1340.57 13.244 <0.001 Secondary 17755.12 1331.9 19.134 <0.001 Discussion This study is the first to retrospectively analyze the trends and influencing factors on hospitalization expenses for GC patients in Shanghai using ITSA and the new GRA. It unveils an increasing trend in GC patient hospitalization expenses from 2014 to 2021, primarily driven by rising costs in drugs and consumables. Additionally, demographic characteristics, disease severity, and hospital-specific attributes collectively affect hospitalization expenses for GC patients. The rapid escalation of healthcare expenditures represents a ubiquitous challenge encountered by a majority of nations and stands as one of the formidable challenges necessitating attention in the context of healthcare system reforms in China 17 . To alleviate patient burdens, the Chinese government introduced the UZMDP policy, mandating non-markup drug sales, and selling them to patients at the purchase price 18 . Some studies have shown that the implementation of UZMDP has reduced the drug expenses borne by patients, but the increase in other medical expenses, such as the expense of healthcare services, has weakened the effectiveness of controlling medical expenses and reducing the burden on patients, which is consistent with the results of our study 17 , 19 . After full UZMDP implementation in Shanghai, drug expenses declined, yet costs for medical consumables, healthcare services, and examinations continued to rise, contributing to an overall increase in hospitalization expenses. At present, the challenge of rising hospitalization expenses has not yet been adequately addressed. The study underscores that despite a decline in drug expenses, hospitalization costs following the UZMDP policy were still primarily shaped by drug-related expenses. The ITSA revealed an immediate reduction in drug costs, followed by a gradual resurgence over time. This phenomenon may be attributed to a potential decrease in drug prices, coupled with patients potentially acquiring a greater quantity or opting for pricier medications within the confines of a fixed budget 20 . In addition, the average early diagnosis rate of GC in China is only about 10%, mostly in patients with advanced GC 21 . Molecular targeted therapy is an important treatment option for patients with advanced GC, aiming to inhibit tumor proliferation and improve survival rates 7 . However, targeted therapies are expensive, and the widespread use of targeted therapies can result in higher treatment expenses for patients 22 . Although some common targeted therapies for GC, such as Trastuzumab and Apatinib, have been included in China's National Reimbursement Drug List (NRDL), which has alleviated the financial burden on patients 23 . Nevertheless, Extended treatment durations and elevated drug costs, despite some alleviation through reimbursement, contribute to elevated personal out-of-pocket (OOP) expenses 24 . The advent of new and costly targeted antitumor drugs, initially uncovered by medical insurance, further amplifies the economic strain on patients 23 . In 2021, the Chinese Society of Clinical Oncology (CSCO) recommended that Nivolumab in combination with chemotherapy can be used as first-line treatment for advanced or metastatic GC 21 . Nivolumab, as the premier PD-1 inhibitor approved for first-line advanced GC treatment in China, brings forth substantial costs, with a study citing approximately $ 88,190.33 compared to $ 9,563.80 for conventional chemotherapy 21 . The anticipated widespread adoption of Nivolumab portends a sustained escalation of financial burdens on patients, suggesting that we need to continue to focus on targeted drugs for the treatment of GC in the future and control the costs associated with targeted drugs. On the other hand, in order to receive rebates from pharmaceutical companies, doctors are still incentivized to overprescribe drugs 20 . In the future, there is still a need to further regulate medication practices so as to reduce the burden of medication on patients. The study suggests that consumables, healthcare services, and examinations sequentially play a pivotal role in influencing hospitalization expenses. Specifically, consumables' impact on the hospitalization costs of gastric cancer (GC) patients closely mirrors that of drug expenses. On the one hand, this may be due to the fact that consumables expenses account for a relatively large portion of hospitalization expenses for GC patients 25 . On the other hand, hospitals offset the decrease in drug revenues by increasing the provision of other services or products after the implementation of the UZMDP 26 . Corroborating this finding, a study from Changde, China, reveals an observable rise in annual expenditures for inpatient diagnosis, laboratory examinations, and medical consumables following the UZMDP 27 . Despite China's complete abolition of the medical consumables markup in 2019 28 , this study notes only a marginal 2.7% decrease in consumables expenses for GC patients in 2020 compared to 2019, followed by a resumption of an upward trajectory. The main reason may be that there were more elderly GC patients who used more high-value consumable items in this study, which made the change in consumables expenses not obvious 25 . Medical consumables are crucial in healthcare. Only by establishing and improving the medical consumables management system and regulating the consumables use behavior of medical personnel, can the patient's consumables expenditure be reduced 25 . Initiated in 2015, China's public hospital reform aimed to increase the remuneration for professional services provided by healthcare workers, augment performance-based pay for medical staff, and establish a contemporary hospital management system 29 . The study noted a significant surge in healthcare services expenses from 2014 to 2021, underscoring the current emphasis on the labor value of medical workers in China. Since the full implementation of the UZMDP in 2017, the cost of consultation and treatment in public hospitals has continued to rise due to insufficient subsidies and cost-effectiveness motives 29 . This contributes significantly to the upward trajectory of healthcare services and examination expenses. Despite the government's policies to control the rising expenses of drugs and consumables through the UZMDP or the abolition of mark-ups on consumables, the rapid rise in medical expenditure has not been curbed 29 . A survey based on 15 tertiary hospitals in Shanxi Province revealed that the increase in total hospitalization expenses, driven by heightened miscellaneous expenses, predominantly affected lower-cost patients, potentially exacerbating health inequalities among populations 18 . This highlights the ongoing imperative for healthcare system reform. Rather than relying solely on individual measures to control hospitalization expenses for gastric cancer (GC) patients, a multifaceted approach is recommended. This involves a range of complementary measures to collectively regulate the irrational growth of medical expenses and establish a fair pricing system for medical services to protect the health rights of patients. Consistent with previous studies, we found that the demographic characteristics of GC patients(e.g., gender and age), the severity of their condition(length of hospitalization stay and whether or not they were operated on), and the characteristics of the hospitals(hospital class) all affected the hospitalization expenses of GC patients. Regarding the demographic characteristics of patients, this study found that elderly GC patients incurred more total hospitalization expenses, which is consistent with previous studies. On the one hand, this is due to the higher incidence of GC among the elderly 10 . elderly GC patients undergo complex treatments, leading to increased use of high-value consumables and adjuvant items, thereby amplifying their hospitalization expenses 25 . Through univariate analysis, we found that male GC patients would incur more treatment costs than female GC patients. In multiple regression analysis, however, we found that male GC patients would incur fewer costs, which is less consistent with previous studies 30 . This may be due to Simpson's Paradox in statistics, and further tests with large sample data are still needed in the future 31 . Regarding illness severity, our study indicates that patients with more severe conditions incur higher hospitalization expenses than those with milder illnesses. Specifically, patients diagnosed with gastric cancer (GC) undergoing prolonged hospital stays and surgical interventions tend to accumulate elevated hospitalization expenses due to increased healthcare resource utilization, resulting in heightened medical costs 30 . However, it has been found that inpatients have invalid hospitalization days, that is, patients need to stay in the hospital for observation even if they do not receive any treatment, which leads to an increase in their costs 16 . This not only increases the financial burden of patients but also leads to the waste of healthcare resources, which suggests that we need to improve the efficiency of technical services on the basis of ensuring the quality of healthcare services in the future 16 . In terms of hospital characteristics as another influencing factor, in line with prior research, our study indicates that patients incur the highest hospitalization expenses when seeking care at tertiary hospitals. This association is likely due to the heightened concentration of patients with severe gastric cancer in tertiary care settings 20 . The study has certain limitations. Firstly, the unavailability of additional variables, such as patients' income and history of other diseases, introduces a potential confounding effect on the study results. Secondly, the absence of specific gastric cancer (GC) classifications hinders a detailed analysis of the influencing factors of hospitalization expenses among patients with diverse GC classifications. Thirdly, the intricate policy environment, marked by the concurrent implementation of multiple healthcare reform measures, complicates the measurement of the net effect of the Universal Zero-Markup Drug Policy (UZMDP). The results of the Interrupted Time Series Analysis (ITSA) may be influenced by various policies 17 . In addition, it is important to consider the potential impact of a large-scale outbreak of COVID-19 in 2020 on the hospitalization expenses of GC patients, which could lead to an increase in their various medical expenses. Conclusions The hospitalization expenses for GC patients in Shanghai have shown an upward trend from 2014 to 2021. Our study indicates a reduction in drug expenses following the implementation of the UZMDP. Despite this, drug expenses remain the primary determinant influencing GC patients' hospitalization expenses. Additionally, since the full implementation of the UZMDP, there has been a consistent annual increase in costs related to consumables, healthcare services, and examinations. Notably, consumables expenses have emerged as the second-largest factor impacting the hospitalization expenses of GC patients. In the future, it is still necessary to deepen a variety of healthcare reform measures to control the rise of drugs and consumables expenses. Furthermore, the study identifies advanced age, extended hospitalization duration, surgical interventions, and seeking medical care at secondary and tertiary hospitals as the predominant factors contributing to higher hospitalization expenses for gastric cancer (GC) patients. The study suggests that in the future, further attention should be paid to the disease characteristics of GC patients. Efforts should be directed towards enhancing the utilization rate of medical resources, with the overarching goal of mitigating the economic burden on both GC patients and society. Abbreviations GC Gastric cancer UZMDP Universal Zero Markup Drug Policy ITSA Interrupted time series analysis GRA New gray relational analysis HIS Hospital Information System LIS Laboratory Information Management System NRDL China's National Reimbursement Drug List OOP Personal out-of-pocket CSCO Chinese Society of Clinical Oncology Declarations Ethics approval and consent to participate The experimental protocol was established, according to the ethical guidelines of the Helsinki Declaration and was approved by the Human Ethics Committee of Shanghai Health Development Research Center Ethical Review Board. Written informed consent was obtained from individual or guardian participants. Consent for publication Not applicable. Availability of data and materials All data generated or analysed during this study are included in this published article. Competing interests The authors declare that they have no competing interests. Funding Not applicable. Authors' contributions Chunlin Jin and Haiyin Wang conceived and planned the study; Yichun GU conducted the statistical analysis and wrote the manuscript draft; Jiajun Hao wrote the manuscript draft; Xin Cui and Wenqi Tian conducted data cleaning and other data work; Da HE and Hui Sun provided methodological and material advice; Yulin Zhang translated the manuscript. All authors provided constructive feedback regarding the interpretation of the results and the writing of the manuscript. All authors reviewed the manuscript. Acknowledgements We owe a special debt of gratitude to all the professors and editors, whose hard work benefited us a lot and academically reviewed the paper. References Morgan E, Arnold M, Camargo MC, et al. The current and future incidence and mortality of gastric cancer in 185 countries, 2020–40: A population-based modelling study. eClinicalMedicine. 2022;47. doi:10.1016/j.eclinm.2022.101404 Qu WM, Zhang N. 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In China, these cancer-targeted drugs have been included in the medical insurance!_Medical Insurance News_News & Events_ Yunnan Medical Security Bureau. Accessed November 15, 2023. https://ylbz.yn.gov.cn/index.php?c=show&id=2376 Xia Y, Pan Y, Qian XY, Zhang N, Bai ZA. Analysis of influence factors of trastuzumab inclued in drug directory of Shanghai medical insurance on targeted therapy for breast cancer patients. Chin J New Drugs Clin Rem. 2021;40(12):826-829. doi:10.14109/j.cnki.xyylc.2021.12.06 Li H, Gu FH, Wang W, Wang N, Wu AW. Study on Effect of Medical Consumption Reform on Hospitalization Expenses of Gastric Cancer Patients Undergoing Operation. Hospital Management Forum. 2022;39(5):12-15. Yan K, Yang C, Zhang H, et al. Impact of the zero-mark-up drug policy on drug-related expenditures and use in public hospitals, 2016–2018: an interrupted time series study in Shaanxi. BMJ Open. 2020;10(11):e037034. doi:10.1136/bmjopen-2020-037034 Peng Z, Zhan C, Ma X, et al. Did the universal zero-markup drug policy lower healthcare expenditures? Evidence from Changde, China. BMC Health Services Research. 2021;21(1):1205. doi:10.1186/s12913-021-07211-8 Ma J. Notice of the General Office of the State Council on the Issuance of the Reform Program for the Governance of High-Value Medical Consumables_Health_ The State Council of the People's Republic of China. Accessed November 15, 2023. https://www.gov.cn/zhengce/content/2019-07/31/content_5417518.htm Huang J, Dai T. Public hospital reforms in China: the perspective of hospital directors. BMC Health Services Research. 2019;19(1):142. doi:10.1186/s12913-019-3954-z Yusefi AR, Lankarani KB, Bastani P, Radinmanesh M, Kavosi Z. Risk Factors for Gastric Cancer: A Systematic Review. Asian Pac J Cancer Prev. 2018;19(3):591-603. doi:10.22034/APJCP.2018.19.3.591 Sprenger J, Weinberger N. Simpson’s Paradox. In: Zalta EN, ed. The Stanford Encyclopedia of Philosophy. Summer 2021. Metaphysics Research Lab, Stanford University; 2021. Accessed October 23, 2023. https://plato.stanford.edu/archives/sum2021/entries/paradox-simpson/ Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 22 Apr, 2025 Read the published version in BMC Health Services Research → Version 1 posted Editorial decision: Revision requested 09 Jan, 2024 Submission checks completed at journal 09 Jan, 2024 Editor assigned by journal 09 Jan, 2024 First submitted to journal 20 Dec, 2023 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3781711","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":266180562,"identity":"539b6f51-6b2c-4d77-9026-6ffc6d4f8479","order_by":0,"name":"Yichun Gu","email":"","orcid":"","institution":"Shanghai Health Development Research Center","correspondingAuthor":false,"prefix":"","firstName":"Yichun","middleName":"","lastName":"Gu","suffix":""},{"id":266180563,"identity":"e9095f98-9657-492b-bb1b-91188c6c66ac","order_by":1,"name":"Jiajun Hao","email":"","orcid":"","institution":"Zhejiang University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Jiajun","middleName":"","lastName":"Hao","suffix":""},{"id":266180564,"identity":"d8a49474-b6d6-453c-85c1-9f0264d7f061","order_by":2,"name":"Da He","email":"","orcid":"","institution":"Shanghai Health Development Research Center","correspondingAuthor":false,"prefix":"","firstName":"Da","middleName":"","lastName":"He","suffix":""},{"id":266180565,"identity":"f33b3ff1-eeea-48aa-abca-0597068c8c1f","order_by":3,"name":"Hui Sun","email":"","orcid":"","institution":"Shanghai Health Development Research Center","correspondingAuthor":false,"prefix":"","firstName":"Hui","middleName":"","lastName":"Sun","suffix":""},{"id":266180566,"identity":"04cc295a-43d1-452c-80fc-42c4c6323621","order_by":4,"name":"Xin Cui","email":"","orcid":"","institution":"Shanghai Health Statistics Center","correspondingAuthor":false,"prefix":"","firstName":"Xin","middleName":"","lastName":"Cui","suffix":""},{"id":266180567,"identity":"20126935-0c02-477b-9415-4100c0784d99","order_by":5,"name":"Wenqi Tian","email":"","orcid":"","institution":"Shanghai Health Statistics Center","correspondingAuthor":false,"prefix":"","firstName":"Wenqi","middleName":"","lastName":"Tian","suffix":""},{"id":266180568,"identity":"8c8c205f-c414-432f-b3f3-34e3748d3428","order_by":6,"name":"Yulin Zhang","email":"","orcid":"","institution":"China Pharmaceutical University","correspondingAuthor":false,"prefix":"","firstName":"Yulin","middleName":"","lastName":"Zhang","suffix":""},{"id":266180569,"identity":"7e63298e-4cb3-4d77-99e8-ec0a86780053","order_by":7,"name":"Chunlin Jin","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyUlEQVRIiWNgGAWjYBACxmYGBmYgLcPGwHyAmYGNBC08bAxsCcRpAQGwFiAyIE4Lczvvwc+FbXd4+KR7Pn8uKLsnz8De+/gFfofxJUvPbHvGwyZzdpv0jHPFhg08x80s8GvhMWPmbTvMwyaRuw3ISEhgkEhjMyBSS87jzyRrYZCGamF+QECLsTTPOZCWNDMgI8GwjecY/nAz7D9j+Jmn7LCc/Izkx0BGgjw/exvzB7xaGtBFgFawSeDTIo9NEL8to2AUjIJRMOIAAI2JObD/Lh/aAAAAAElFTkSuQmCC","orcid":"","institution":"Shanghai Health Development Research Center","correspondingAuthor":true,"prefix":"","firstName":"Chunlin","middleName":"","lastName":"Jin","suffix":""},{"id":266180570,"identity":"dd9e977a-7c55-4fa3-bd1d-648527827dea","order_by":8,"name":"Haiyin Wang","email":"","orcid":"","institution":"Shanghai Health Development Research Center","correspondingAuthor":false,"prefix":"","firstName":"Haiyin","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2023-12-20 12:15:06","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3781711/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3781711/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12913-025-12422-4","type":"published","date":"2025-04-22T15:57:41+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":49485273,"identity":"b3ea12dd-73fd-420f-b2ee-989429fe0630","added_by":"auto","created_at":"2024-01-11 16:11:03","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":43228,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTrend of the hospitalization expenses from 2014 to 2021\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-3781711/v1/fd1fd0c1269a6c6a81f2a6ba.png"},{"id":49485272,"identity":"a66c37b4-3548-409a-99bc-15502adf0968","added_by":"auto","created_at":"2024-01-11 16:11:02","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":147109,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTrend of the different medical expenses from 2014 to 2021\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-3781711/v1/88c49400269605c9dfd64ef3.png"},{"id":81569691,"identity":"3d460a9f-d411-40ca-ae76-fa45ad8fb3c0","added_by":"auto","created_at":"2025-04-28 16:10:11","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1436336,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3781711/v1/801c097f-d9c5-404e-abbe-60e5fdc9b297.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Universal Zero Markup Drug Policy and Gastric Cancer Hospitalization Expenses: An Analysis of Trends and Influencing Factors in Shanghai from 2014 to 2021","fulltext":[{"header":"Background","content":"\u003cp\u003eGastric cancer (GC) represents a prevalent malignancy within the gastrointestinal tract, characterized by elevated morbidity, substantial mortality, and an unfavorable prognosis\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. According to GLOBOCAN 2020, GC ranks fifth globally among prevalent cancers and stands as the fourth leading cause of cancer-related mortality\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. The year 2020 witnessed an incidence of approximately 1.1\u0026nbsp;million new GC cases and an estimated 770,000 fatalities\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Regional heterogeneity is discernible, with East Asia contributing substantially to the global incidence, encompassing 60%. Notably, China emerges as the primary contributor, documenting 478,000 cases and 373,000 associated deaths in 2020\u003csup\u003e4\u003c/sup\u003e. Despite recent declines in GC morbidity and mortality within the Chinese population, challenges persist, propelled by the expansive demographic and suboptimal survival rates. Sustained multidisciplinary initiatives are imperative for the efficacious prevention and treatment of GC within this intricate epidemiological landscape\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eGC ranks second in incidence rate and third in mortality rate of malignant tumors in China\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. The annual treatment expense for GC in China was approximately 23.5\u0026nbsp;billion yuan in 2018, ranking third among all tumors and significantly impacting the medical insurance fund\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. GC imposes a substantial disease and economic burden on society, placing a considerable financial strain on families and individuals. Due to the insidious nature of early symptoms, most patients receive a diagnosis at an advanced stage, resulting in high treatment costs\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. A U.S. study found that the 10-month treatment cost for GC patients was 96 times higher than that for non-cancer patients, with hospitalization expenses being the primary contributor\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. In China, the average per capita medical cost for GC patients in 2018 was nearly 22,000 yuan, ranking second only to lung cancer and primarily attributed to hospitalization expenses\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Therefore, monitoring hospitalization expenses for GC patients and associated influencing factors is necessary to control unreasonable increases in medical costs and reduce the economic burden on society, families, and individuals.\u003c/p\u003e \u003cp\u003eGC is a disease with high morbidity in the elderly\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. In Shanghai, a pioneer in China's aging population, GC stands as one of the most prevalent malignant tumors\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. In 2016, GC ranked fourth in the standardized incidence rate at 15.85 per 100,000 individuals within the city's cancer incidence spectrum\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Despite its prevalence, research on GC patient hospitalization expenses and influencing factors in Shanghai remains scarce. Moreover, Shanghai implemented comprehensive healthcare system reforms in 2017, including the introduction of the universal zero markup drug policy (UZMDP) to alleviate financial burdens on patients\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. However, there is limited investigation into the impact of these reforms on GC patient hospitalization expenses in Shanghai. Hence, this study aims to explore the trends in hospitalization expenses for GC patients in Shanghai from 2014 to 2021. Utilizing interrupted time series analysis (ITSA) and a novel gray relational analysis model (GRA), the investigation specifically concentrates on delineating changes in GC patient hospitalization expenses pre- and post-comprehensive healthcare reforms. Emphasis is placed on identifying the primary factors associated with these variations. The objective is to provide a scientific foundation for judiciously controlling hospitalization expenses among GC patients, thus alleviating the medical-economic burden on individuals and substantively contributing to the advancement of healthcare system reform within the medical and pharmaceutical sectors.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData source\u003c/h2\u003e \u003cp\u003eThe study data were acquired from the Health Network of the Shanghai Economic Information Center, encompassing the Health Data Reporting System, Hospital Information System (HIS), and Laboratory Information Management System (LIS). Patient case data from the initial page were extracted from the Health Data Reporting System, while information regarding examination and testing expenses originated from the LIS. Other relevant data were retrieved from the HIS. This comprehensive dataset forms the basis for our analytical framework, facilitating a nuanced exploration of factors influencing hospitalization expenses for gastric cancer patients in Shanghai from 2014 to 2021.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStudy participants\u003c/h2\u003e \u003cp\u003eThe study enrolled individuals diagnosed with gastric cancer (GC) in Shanghai from 2014 to 2021. Following a rigorous screening process to eliminate missing values, outliers, and duplicate entries, a total of 23,335 study subjects were ultimately included in the analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eMeasures of independent variables\u003c/h2\u003e \u003cp\u003eThe main independent variables included in this study were sex (man; women), age (0\u0026ndash;45 years; 45\u0026ndash;60 years; \u0026gt;60 years), length of hospitalization stay(0\u0026ndash;7 days; 8\u0026ndash;15 days; 16\u0026ndash;30 days; \u0026gt;30 days), surgery, medical insurance, and the level of the hospital attended (unclassified hospital; community healthcare center; primary hospital; secondary hospital; tertiary hospital).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eMeasures of dependent variables\u003c/h2\u003e \u003cp\u003eHospitalization expenses were the outcome variable of interest for the study, which mainly include the expenses of drugs, medical consumables, examinations (testing, radiology, and laboratory testing), medical services (beds, consultation, surgery, blood transfusion, oxygen, nursing, and other costs) and other medical costs.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe study initially utilized frequencies and percentages to outline the basic characteristics of the study subjects.\u003c/p\u003e \u003cp\u003eSubsequently, ITSA was employed to analyze hospitalization expense trends before and after the UZMDP implementation. ITSA recognized for its ability to discern instantaneous and trend changes in interventions, facilitated assessing intervention effects by examining data at multiple time points\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. In this study, the full enactment of the UZMDP in Shanghai in January 2017 served as the intervention point (Inter-UZMDP). The period before January 2017 was termed the Pre-UZMDP phase, and after January 2017 was the Post-UZMDP phase.\u003c/p\u003e \u003cp\u003eA new GRA gauged the association strength between healthcare expenditures and hospitalization expenses for gastric cancer (GC) patients. This GRA analysis computed correlation coefficients and the degree of correlation by directly assessing the absolute difference between individual comparison and reference series\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Total hospitalization expenses were the reference series, and different healthcare costs were the comparison series.\u003c/p\u003e \u003cp\u003eInfluencing factors on hospitalization expenses were determined through Multiple Linear Regression Analysis. Non-statistically significant variables were gradually eliminated using backward regression to construct the final model.\u003c/p\u003e \u003cp\u003eMicrosoft Office Excel 2016 was used for database establishment and data cleaning, while R 4.3.1 software performed the analyses. Statistical significance was set at a two-sided P-value less than 0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 16,109 male and 7,226 female patients with GC in Shanghai from 2014 to 2021 were included in this study. The findings indicated that over 68% of GC patients were aged 60 or older, with almost 50% having a hospital stay of 8 to 15 days. Additionally, more than half of the patients had undergone surgery and held health insurance, while the majority sought treatment at tertiary care hospitals. Detailed participant characteristics are presented in \u003cstrong\u003eTable 1\u003c/strong\u003e, and specific information for each study year is available in \u003cstrong\u003eSupplement Table 1.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1 Baseline characteristics of the study participants\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"332\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.493975903614455%\" style=\"width: 52.6144%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.89156626506024%\" style=\"width: 24.8366%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumbers\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.6144578313253%\" style=\"width: 22.549%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePercent\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.493975903614455%\" valign=\"bottom\" style=\"width: 52.6144%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.89156626506024%\" valign=\"bottom\" style=\"width: 24.8366%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.6144578313253%\" style=\"width: 22.549%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.493975903614455%\" valign=\"bottom\" style=\"width: 52.6144%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.89156626506024%\" valign=\"bottom\" style=\"width: 24.8366%;\"\u003e\n \u003cp\u003e16109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.6144578313253%\" valign=\"bottom\" style=\"width: 22.549%;\"\u003e\n \u003cp\u003e69.03%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.493975903614455%\" valign=\"bottom\" style=\"width: 52.6144%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.89156626506024%\" valign=\"bottom\" style=\"width: 24.8366%;\"\u003e\n \u003cp\u003e7226\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.6144578313253%\" valign=\"bottom\" style=\"width: 22.549%;\"\u003e\n \u003cp\u003e30.97%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.493975903614455%\" valign=\"bottom\" style=\"width: 52.6144%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge group\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.89156626506024%\" valign=\"bottom\" style=\"width: 24.8366%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.6144578313253%\" valign=\"bottom\" style=\"width: 22.549%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.493975903614455%\" valign=\"bottom\" style=\"width: 52.6144%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;0~45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.89156626506024%\" valign=\"bottom\" style=\"width: 24.8366%;\"\u003e\n \u003cp\u003e1314\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.6144578313253%\" valign=\"bottom\" style=\"width: 22.549%;\"\u003e\n \u003cp\u003e5.63%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.493975903614455%\" valign=\"bottom\" style=\"width: 52.6144%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;45~60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.89156626506024%\" valign=\"bottom\" style=\"width: 24.8366%;\"\u003e\n \u003cp\u003e5941\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.6144578313253%\" valign=\"bottom\" style=\"width: 22.549%;\"\u003e\n \u003cp\u003e25.46%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.493975903614455%\" valign=\"bottom\" style=\"width: 52.6144%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026gt;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.89156626506024%\" valign=\"bottom\" style=\"width: 24.8366%;\"\u003e\n \u003cp\u003e16080\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.6144578313253%\" valign=\"bottom\" style=\"width: 22.549%;\"\u003e\n \u003cp\u003e68.91%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.493975903614455%\" valign=\"bottom\" style=\"width: 52.6144%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLength of Stay (days)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.89156626506024%\" valign=\"bottom\" style=\"width: 24.8366%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.6144578313253%\" valign=\"bottom\" style=\"width: 22.549%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.493975903614455%\" valign=\"bottom\" style=\"width: 52.6144%;\"\u003e\n \u003cp\u003e\u0026nbsp; 0~7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.89156626506024%\" valign=\"bottom\" style=\"width: 24.8366%;\"\u003e\n \u003cp\u003e4507\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.6144578313253%\" valign=\"bottom\" style=\"width: 22.549%;\"\u003e\n \u003cp\u003e19.31%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.493975903614455%\" valign=\"bottom\" style=\"width: 52.6144%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;8~15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.89156626506024%\" valign=\"bottom\" style=\"width: 24.8366%;\"\u003e\n \u003cp\u003e10847\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.6144578313253%\" valign=\"bottom\" style=\"width: 22.549%;\"\u003e\n \u003cp\u003e46.48%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.493975903614455%\" valign=\"bottom\" style=\"width: 52.6144%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;16~30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.89156626506024%\" valign=\"bottom\" style=\"width: 24.8366%;\"\u003e\n \u003cp\u003e6553\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.6144578313253%\" valign=\"bottom\" style=\"width: 22.549%;\"\u003e\n \u003cp\u003e28.08%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.493975903614455%\" valign=\"bottom\" style=\"width: 52.6144%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026gt;30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.89156626506024%\" valign=\"bottom\" style=\"width: 24.8366%;\"\u003e\n \u003cp\u003e1424\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.6144578313253%\" valign=\"bottom\" style=\"width: 22.549%;\"\u003e\n \u003cp\u003e6.10%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.493975903614455%\" valign=\"bottom\" style=\"width: 52.6144%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSurgery\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.89156626506024%\" valign=\"bottom\" style=\"width: 24.8366%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.6144578313253%\" valign=\"bottom\" style=\"width: 22.549%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.493975903614455%\" valign=\"bottom\" style=\"width: 52.6144%;\"\u003e\n \u003cp\u003e\u0026nbsp; Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.89156626506024%\" valign=\"bottom\" style=\"width: 24.8366%;\"\u003e\n \u003cp\u003e18507\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.6144578313253%\" valign=\"bottom\" style=\"width: 22.549%;\"\u003e\n \u003cp\u003e79.31%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.493975903614455%\" valign=\"bottom\" style=\"width: 52.6144%;\"\u003e\n \u003cp\u003e\u0026nbsp; No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.89156626506024%\" valign=\"bottom\" style=\"width: 24.8366%;\"\u003e\n \u003cp\u003e4828\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.6144578313253%\" valign=\"bottom\" style=\"width: 22.549%;\"\u003e\n \u003cp\u003e20.69%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.493975903614455%\" valign=\"bottom\" style=\"width: 52.6144%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedical Insurance\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.89156626506024%\" valign=\"bottom\" style=\"width: 24.8366%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.6144578313253%\" valign=\"bottom\" style=\"width: 22.549%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.493975903614455%\" valign=\"bottom\" style=\"width: 52.6144%;\"\u003e\n \u003cp\u003e\u0026nbsp; Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.89156626506024%\" valign=\"bottom\" style=\"width: 24.8366%;\"\u003e\n \u003cp\u003e15707\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.6144578313253%\" valign=\"bottom\" style=\"width: 22.549%;\"\u003e\n \u003cp\u003e67.31%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.493975903614455%\" valign=\"bottom\" style=\"width: 52.6144%;\"\u003e\n \u003cp\u003e\u0026nbsp; No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.89156626506024%\" valign=\"bottom\" style=\"width: 24.8366%;\"\u003e\n \u003cp\u003e7628\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.6144578313253%\" valign=\"bottom\" style=\"width: 22.549%;\"\u003e\n \u003cp\u003e32.69%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.493975903614455%\" valign=\"bottom\" style=\"width: 52.6144%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHospital Level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.89156626506024%\" valign=\"bottom\" style=\"width: 24.8366%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.6144578313253%\" valign=\"bottom\" style=\"width: 22.549%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.493975903614455%\" valign=\"bottom\" style=\"width: 52.6144%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Tertiary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.89156626506024%\" valign=\"bottom\" style=\"width: 24.8366%;\"\u003e\n \u003cp\u003e18073\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.6144578313253%\" valign=\"bottom\" style=\"width: 22.549%;\"\u003e\n \u003cp\u003e77.45%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.493975903614455%\" valign=\"bottom\" style=\"width: 52.6144%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Secondary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.89156626506024%\" valign=\"bottom\" style=\"width: 24.8366%;\"\u003e\n \u003cp\u003e4825\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.6144578313253%\" valign=\"bottom\" style=\"width: 22.549%;\"\u003e\n \u003cp\u003e20.68%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.493975903614455%\" valign=\"bottom\" style=\"width: 52.6144%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Primary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.89156626506024%\" valign=\"bottom\" style=\"width: 24.8366%;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.6144578313253%\" valign=\"bottom\" style=\"width: 22.549%;\"\u003e\n \u003cp\u003e0.10%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.493975903614455%\" valign=\"bottom\" style=\"width: 52.6144%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Community\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.89156626506024%\" valign=\"bottom\" style=\"width: 24.8366%;\"\u003e\n \u003cp\u003e118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.6144578313253%\" valign=\"bottom\" style=\"width: 22.549%;\"\u003e\n \u003cp\u003e0.51%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.493975903614455%\" valign=\"bottom\" style=\"width: 52.6144%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Others\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.89156626506024%\" valign=\"bottom\" style=\"width: 24.8366%;\"\u003e\n \u003cp\u003e296\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.6144578313253%\" valign=\"bottom\" style=\"width: 22.549%;\"\u003e\n \u003cp\u003e1.27%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.493975903614455%\" valign=\"bottom\" style=\"width: 52.6144%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.89156626506024%\" valign=\"bottom\" style=\"width: 24.8366%;\"\u003e\n \u003cp\u003e23335\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.6144578313253%\" style=\"width: 22.549%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAs shown in Table 2, spanning 2014 to 2021, the overall hospitalization expenses for gastric cancer (GC) patients exhibited an upward trend. This encompassed costs for medical consumables, examinations, and healthcare services, while a contrasting downward trajectory was noted for pharmaceutical expenses. Particularly post the Universal Zero-Markup Drug Policy (UZMDP), there was a marked 9.03% reduction in total drug expenses. Specific details are available in \u003cstrong\u003eSupplement Table 2.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eTotal hospitalization and principal medical expenses for gastric cancer patients in Shanghai from 2014 to 2021\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"728\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.065934065934066%\" rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eYear\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"90.93406593406593%\" colspan=\"10\"\u003e\n \u003cp\u003e\u003cstrong\u003eSource of Expenses\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\" colspan=\"2\"\u003e\n \u003cp\u003eTotal Hospitalization Expenses\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" colspan=\"2\"\u003e\n \u003cp\u003eTotal Drug \u0026nbsp; \u0026nbsp; Expenses\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" colspan=\"2\"\u003e\n \u003cp\u003eTotal Consumable \u0026nbsp;Expenses\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" colspan=\"2\"\u003e\n \u003cp\u003eTotal Examination Expenses\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" colspan=\"2\"\u003e\n \u003cp\u003eTotal Healthcare Service Expenses\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.428571428571429%\"\u003e\n \u003cp\u003eExpenses\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.571428571428571%\"\u003e\n \u003cp\u003eYoY Growth, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.428571428571429%\"\u003e\n \u003cp\u003eExpenses (%)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.571428571428571%\"\u003e\n \u003cp\u003eYoY Growth, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.428571428571429%\"\u003e\n \u003cp\u003eExpenses (%)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.571428571428571%\"\u003e\n \u003cp\u003eYoY Growth, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.428571428571429%\"\u003e\n \u003cp\u003eExpenses (%)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.571428571428571%\"\u003e\n \u003cp\u003eYoY Growth, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.428571428571429%\"\u003e\n \u003cp\u003eExpenses (%)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.571428571428571%\"\u003e\n \u003cp\u003eYoY Growth, %\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.028727770177838%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2014\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.39671682626539%\"\u003e\n \u003cp\u003e61986.76\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7975376196990425%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.39671682626539%\" valign=\"top\"\u003e\n \u003cp\u003e27111.69\u003c/p\u003e\n \u003cp\u003e(43.74%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7975376196990425%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.39671682626539%\" valign=\"top\"\u003e\n \u003cp\u003e14780.9 (23.85%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7975376196990425%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.39671682626539%\"\u003e\n \u003cp\u003e1453.36 (2.34%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7975376196990425%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.39671682626539%\"\u003e\n \u003cp\u003e6608.86 (10.66%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7975376196990425%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.028727770177838%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2015\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.39671682626539%\"\u003e\n \u003cp\u003e41977.47\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7975376196990425%\"\u003e\n \u003cp\u003e-32.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.39671682626539%\" valign=\"top\"\u003e\n \u003cp\u003e15486.17 (36.89%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7975376196990425%\"\u003e\n \u003cp\u003e-42.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.39671682626539%\" valign=\"top\"\u003e\n \u003cp\u003e11682.12 (27.83%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7975376196990425%\"\u003e\n \u003cp\u003e-20.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.39671682626539%\"\u003e\n \u003cp\u003e1367.27 (3.26%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7975376196990425%\"\u003e\n \u003cp\u003e-5.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.39671682626539%\"\u003e\n \u003cp\u003e5150.29 (12.27%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7975376196990425%\"\u003e\n \u003cp\u003e-22.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.028727770177838%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2016\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.39671682626539%\"\u003e\n \u003cp\u003e44378.73\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7975376196990425%\"\u003e\n \u003cp\u003e5.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.39671682626539%\" valign=\"top\"\u003e\n \u003cp\u003e14559.33 (32.81%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7975376196990425%\"\u003e\n \u003cp\u003e-5.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.39671682626539%\" valign=\"top\"\u003e\n \u003cp\u003e12960.18 (29.20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7975376196990425%\"\u003e\n \u003cp\u003e10.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.39671682626539%\"\u003e\n \u003cp\u003e2763.79 (6.23%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7975376196990425%\"\u003e\n \u003cp\u003e102.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.39671682626539%\"\u003e\n \u003cp\u003e6394.14 (14.41%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7975376196990425%\"\u003e\n \u003cp\u003e24.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.028727770177838%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2017\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.39671682626539%\"\u003e\n \u003cp\u003e42636.68\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7975376196990425%\"\u003e\n \u003cp\u003e-3.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.39671682626539%\" valign=\"top\"\u003e\n \u003cp\u003e12017.91 (28.19%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7975376196990425%\"\u003e\n \u003cp\u003e-17.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.39671682626539%\" valign=\"top\"\u003e\n \u003cp\u003e13241.05 (31.06%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7975376196990425%\"\u003e\n \u003cp\u003e2.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.39671682626539%\"\u003e\n \u003cp\u003e2539.87 (5.96%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7975376196990425%\"\u003e\n \u003cp\u003e-8.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.39671682626539%\"\u003e\n \u003cp\u003e6807.71 (15.97%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7975376196990425%\"\u003e\n \u003cp\u003e6.47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.028727770177838%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2018\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.39671682626539%\"\u003e\n \u003cp\u003e46703.57\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7975376196990425%\"\u003e\n \u003cp\u003e9.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.39671682626539%\" valign=\"top\"\u003e\n \u003cp\u003e12744.82 (27.29%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7975376196990425%\"\u003e\n \u003cp\u003e6.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.39671682626539%\" valign=\"top\"\u003e\n \u003cp\u003e15075.2 (32.28%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7975376196990425%\"\u003e\n \u003cp\u003e13.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.39671682626539%\"\u003e\n \u003cp\u003e3116.86 (6.67%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7975376196990425%\"\u003e\n \u003cp\u003e22.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.39671682626539%\"\u003e\n \u003cp\u003e7267.1 (15.56%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7975376196990425%\"\u003e\n \u003cp\u003e6.75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.028727770177838%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2019\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.39671682626539%\"\u003e\n \u003cp\u003e49572.90\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7975376196990425%\"\u003e\n \u003cp\u003e6.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.39671682626539%\" valign=\"top\"\u003e\n \u003cp\u003e12623.47 (25.46%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7975376196990425%\"\u003e\n \u003cp\u003e-0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.39671682626539%\" valign=\"top\"\u003e\n \u003cp\u003e16526.41 (33.34%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7975376196990425%\"\u003e\n \u003cp\u003e9.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.39671682626539%\"\u003e\n \u003cp\u003e3962.06 (7.99%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7975376196990425%\"\u003e\n \u003cp\u003e27.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.39671682626539%\"\u003e\n \u003cp\u003e7842.49 (15.82%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7975376196990425%\"\u003e\n \u003cp\u003e7.92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.028727770177838%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2020\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.39671682626539%\"\u003e\n \u003cp\u003e52744.66\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7975376196990425%\"\u003e\n \u003cp\u003e6.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.39671682626539%\" valign=\"top\"\u003e\n \u003cp\u003e14457.64 (27.41%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7975376196990425%\"\u003e\n \u003cp\u003e14.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.39671682626539%\" valign=\"top\"\u003e\n \u003cp\u003e16080.86 (30.49%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7975376196990425%\"\u003e\n \u003cp\u003e-2.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.39671682626539%\"\u003e\n \u003cp\u003e4140.1 (7.85%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7975376196990425%\"\u003e\n \u003cp\u003e4.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.39671682626539%\"\u003e\n \u003cp\u003e8191.78 (15.53%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7975376196990425%\"\u003e\n \u003cp\u003e4.45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.028727770177838%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2021\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.39671682626539%\"\u003e\n \u003cp\u003e56378.11\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7975376196990425%\"\u003e\n \u003cp\u003e6.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.39671682626539%\" valign=\"top\"\u003e\n \u003cp\u003e13235.34 (23.48%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7975376196990425%\"\u003e\n \u003cp\u003e-8.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.39671682626539%\" valign=\"top\"\u003e\n \u003cp\u003e19205.21 (34.07%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7975376196990425%\"\u003e\n \u003cp\u003e19.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.39671682626539%\"\u003e\n \u003cp\u003e4966.58 (8.81%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7975376196990425%\"\u003e\n \u003cp\u003e19.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.39671682626539%\"\u003e\n \u003cp\u003e9355.9 (16.59%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7975376196990425%\"\u003e\n \u003cp\u003e14.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cem\u003eNotes: YoY: Year over Year; \u003csup\u003ea\u003c/sup\u003e refers to the proportion of the specific expenses within the Total Hospitalization Expenses.\u003c/em\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u003c/strong\u003e displays the segmented regression outcomes from ITSA. The instantaneous shift in total hospitalization expenses lacked statistical significance post the UZMDP implementation. However, the average total hospitalization expenses exhibited a significant upward trend over time (P\u0026lt;0.01), manifesting a monthly increase of approximately 271.73 yuan, as illustrated in \u003cstrong\u003eFigure 1\u003c/strong\u003e. Conversely, drug expenses underwent an immediate and marked reduction post-UZMDP, followed by a sustained increase. Consumables expenses showed no significant transitory alteration but demonstrated a monthly rise of about 106.41 yuan post-UZMDP. Meanwhile, expenses related to examinations and healthcare services consistently ascended post-UZMDP, as depicted in \u003cstrong\u003eFigure 2\u003c/strong\u003e.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3 The impact of the universal zero mark-up drug policy on changes in medical costs for gastric cancer patients\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"126%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.208333333333332%\" rowspan=\"2\" style=\"width: 26.3518%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSource of Expenses\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.833333333333332%\" colspan=\"2\" style=\"width: 25.0742%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEffect of\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ePre-UZMDP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.916666666666668%\" colspan=\"2\" style=\"width: 28.8273%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eImmediate effect of Inter-UZMDP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.875%\" colspan=\"2\" style=\"width: 10.5407%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSustained effect of Post-UZMDP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.151515151515152%\" style=\"width: 13.3356%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCoefficient\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.636363636363637%\" style=\"width: 11.7385%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP value\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.696969696969695%\" style=\"width: 17.0888%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCoefficient\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.636363636363637%\" style=\"width: 11.7385%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP value\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.181818181818183%\" style=\"width: 6.548%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCoefficient\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.636363636363637%\" style=\"width: 3.9927%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP value\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.526315789473685%\" style=\"width: 26.3518%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHospitalization Expenses\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.526315789473685%\" valign=\"bottom\" style=\"width: 13.3356%;\"\u003e\n \u003cp\u003e72.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"bottom\" style=\"width: 11.7385%;\"\u003e\n \u003cp\u003e0.040\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.68421052631579%\" valign=\"bottom\" style=\"width: 17.0888%;\"\u003e\n \u003cp\u003e-2900.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"bottom\" style=\"width: 11.7385%;\"\u003e\n \u003cp\u003e0.059\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.631578947368421%\" valign=\"bottom\" style=\"width: 6.548%;\"\u003e\n \u003cp\u003e199.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"bottom\" style=\"width: 3.9927%;\"\u003e\n \u003cp\u003e0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.526315789473685%\" style=\"width: 26.3518%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDrug Expenses\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.526315789473685%\" valign=\"bottom\" style=\"width: 13.3356%;\"\u003e\n \u003cp\u003e-113.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"bottom\" style=\"width: 11.7385%;\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.68421052631579%\" valign=\"bottom\" style=\"width: 17.0888%;\"\u003e\n \u003cp\u003e-1610.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"bottom\" style=\"width: 11.7385%;\"\u003e\n \u003cp\u003e0.028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.631578947368421%\" valign=\"bottom\" style=\"width: 6.548%;\"\u003e\n \u003cp\u003e143.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"bottom\" style=\"width: 3.9927%;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.526315789473685%\" style=\"width: 26.3518%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eConsumable Expenses\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.526315789473685%\" valign=\"bottom\" style=\"width: 13.3356%;\"\u003e\n \u003cp\u003e64.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"bottom\" style=\"width: 11.7385%;\"\u003e\n \u003cp\u003e0.058\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.68421052631579%\" valign=\"bottom\" style=\"width: 17.0888%;\"\u003e\n \u003cp\u003e-394.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"bottom\" style=\"width: 11.7385%;\"\u003e\n \u003cp\u003e0.051\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.631578947368421%\" valign=\"bottom\" style=\"width: 6.548%;\"\u003e\n \u003cp\u003e41.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"bottom\" style=\"width: 3.9927%;\"\u003e\n \u003cp\u003e0.0236\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.526315789473685%\" style=\"width: 26.3518%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eExamination Expenses\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.526315789473685%\" valign=\"bottom\" style=\"width: 13.3356%;\"\u003e\n \u003cp\u003e101.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"bottom\" style=\"width: 11.7385%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.68421052631579%\" valign=\"bottom\" style=\"width: 17.0888%;\"\u003e\n \u003cp\u003e-1051.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"bottom\" style=\"width: 11.7385%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.631578947368421%\" valign=\"bottom\" style=\"width: 6.548%;\"\u003e\n \u003cp\u003e-52.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"bottom\" style=\"width: 3.9927%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.526315789473685%\" style=\"width: 26.3518%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHealthcare Service Expenses\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.526315789473685%\" valign=\"bottom\" style=\"width: 13.3356%;\"\u003e\n \u003cp\u003e70.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"bottom\" style=\"width: 11.7385%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.68421052631579%\" valign=\"bottom\" style=\"width: 17.0888%;\"\u003e\n \u003cp\u003e-328.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"bottom\" style=\"width: 11.7385%;\"\u003e\n \u003cp\u003e0.222\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.631578947368421%\" valign=\"bottom\" style=\"width: 6.548%;\"\u003e\n \u003cp\u003e-21.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.473684210526315%\" valign=\"bottom\" style=\"width: 3.9927%;\"\u003e\n \u003cp\u003e0.171\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4\u003c/strong\u003e presents the outcomes of the new GRA, illustrating the correlation degree and relational order of average expense levels for each item. The study underscores that drug and consumable expenditures are paramount determinants significantly influencing hospitalization expenses for GC patients in Shanghai from 2014 to 2021. Their correlation is notably higher than other variables, with healthcare services expenses and examination-related expenditures subsequently following, albeit to a lesser degree.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4 The results of the new grey relational analysis\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"586\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.27303754266212%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSource of Expenses\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.01023890784983%\"\u003e\n \u003cp\u003e\u003cstrong\u003eGrey relational grade\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.716723549488055%\"\u003e\n \u003cp\u003e\u003cstrong\u003eRanking results of GRA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.27303754266212%\"\u003e\n \u003cp\u003eTotal Drug Expenses\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.01023890784983%\"\u003e\n \u003cp\u003e0.9695\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.716723549488055%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.27303754266212%\"\u003e\n \u003cp\u003eTotal Consumable Expenses\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.01023890784983%\"\u003e\n \u003cp\u003e0.9669\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.716723549488055%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.27303754266212%\"\u003e\n \u003cp\u003eTotal Healthcare Service Expenses\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.01023890784983%\"\u003e\n \u003cp\u003e0.8517\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.716723549488055%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.27303754266212%\"\u003e\n \u003cp\u003eTotal Examination Expenses\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.01023890784983%\"\u003e\n \u003cp\u003e0.8005\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.716723549488055%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAfter verification, total hospitalization expenses demonstrated a normal distribution. Univariate analysis identified significant differences in expenses based on gender, age, hospitalization duration, surgery presence, health insurance, and hospital level (\u003cstrong\u003eSupplement Table 3\u003c/strong\u003e). All variables were incorporated into a multiple linear regression model, with a backward elimination process refining the included variables, as detailed in \u003cstrong\u003eTable 5\u003c/strong\u003e. Findings indicated a positive correlation between length of hospitalization and incurred expenses. Additionally, GC patients undergoing surgery experienced higher expenses than their non-surgical counterparts. Tertiary and secondary care hospitalizations for GC incurred higher expenses compared to community health service centers and primary care hospitals. Notably, hospitalization costs were lower for those aged \u0026le;60 than those aged \u0026gt;60.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5 Multivariable analyses of hospitalization expenses for gastric cancer patients in Shanghai from 2014 to 2021\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.978873239436616%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.781690140845072%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCoefficient\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.6056338028169%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eStd.Error\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.845070422535212%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003et value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.788732394366198%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.978873239436616%\"\u003e\n \u003cp\u003e\u003cstrong\u003eConstant\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.781690140845072%\"\u003e\n \u003cp\u003e-19117.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.6056338028169%\"\u003e\n \u003cp\u003e1394.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.845070422535212%\"\u003e\n \u003cp\u003e-13.706\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.788732394366198%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.978873239436616%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex (Female)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.781690140845072%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.6056338028169%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.845070422535212%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.788732394366198%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.978873239436616%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Male\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.781690140845072%\"\u003e\n \u003cp\u003e-3411.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.6056338028169%\"\u003e\n \u003cp\u003e376.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.845070422535212%\"\u003e\n \u003cp\u003e-9.053\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.788732394366198%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.978873239436616%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge group (\u0026gt;60)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.781690140845072%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.6056338028169%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.845070422535212%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.788732394366198%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.978873239436616%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026le;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.781690140845072%\" valign=\"bottom\"\u003e\n \u003cp\u003e-780.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.6056338028169%\" valign=\"bottom\"\u003e\n \u003cp\u003e379.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.845070422535212%\" valign=\"bottom\"\u003e\n \u003cp\u003e-2.056\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.788732394366198%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.0398\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.978873239436616%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eLength of Stay\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.781690140845072%\" valign=\"bottom\"\u003e\n \u003cp\u003e1753.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.6056338028169%\" valign=\"bottom\"\u003e\n \u003cp\u003e12.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.845070422535212%\" valign=\"bottom\"\u003e\n \u003cp\u003e143.904\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.788732394366198%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.978873239436616%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eSurgery (No)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.781690140845072%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.6056338028169%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.845070422535212%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.788732394366198%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.978873239436616%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.781690140845072%\" valign=\"bottom\"\u003e\n \u003cp\u003e29047.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.6056338028169%\" valign=\"bottom\"\u003e\n \u003cp\u003e479.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.845070422535212%\" valign=\"bottom\"\u003e\n \u003cp\u003e60.639\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.788732394366198%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.978873239436616%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eHospital Level (Community and Primary)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.781690140845072%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.6056338028169%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.845070422535212%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.788732394366198%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.978873239436616%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Tertiary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.781690140845072%\"\u003e\n \u003cp\u003e25485.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.6056338028169%\" valign=\"bottom\"\u003e\n \u003cp\u003e1340.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.845070422535212%\" valign=\"bottom\"\u003e\n \u003cp\u003e13.244\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.788732394366198%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.978873239436616%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Secondary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.781690140845072%\" valign=\"bottom\"\u003e\n \u003cp\u003e17755.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.6056338028169%\" valign=\"bottom\"\u003e\n \u003cp\u003e1331.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.845070422535212%\" valign=\"bottom\"\u003e\n \u003cp\u003e19.134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.788732394366198%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study is the first to retrospectively analyze the trends and influencing factors on hospitalization expenses for GC patients in Shanghai using ITSA and the new GRA. It unveils an increasing trend in GC patient hospitalization expenses from 2014 to 2021, primarily driven by rising costs in drugs and consumables. Additionally, demographic characteristics, disease severity, and hospital-specific attributes collectively affect hospitalization expenses for GC patients.\u003c/p\u003e \u003cp\u003eThe rapid escalation of healthcare expenditures represents a ubiquitous challenge encountered by a majority of nations and stands as one of the formidable challenges necessitating attention in the context of healthcare system reforms in China\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. To alleviate patient burdens, the Chinese government introduced the UZMDP policy, mandating non-markup drug sales, and selling them to patients at the purchase price\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Some studies have shown that the implementation of UZMDP has reduced the drug expenses borne by patients, but the increase in other medical expenses, such as the expense of healthcare services, has weakened the effectiveness of controlling medical expenses and reducing the burden on patients, which is consistent with the results of our study\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. After full UZMDP implementation in Shanghai, drug expenses declined, yet costs for medical consumables, healthcare services, and examinations continued to rise, contributing to an overall increase in hospitalization expenses. At present, the challenge of rising hospitalization expenses has not yet been adequately addressed.\u003c/p\u003e \u003cp\u003eThe study underscores that despite a decline in drug expenses, hospitalization costs following the UZMDP policy were still primarily shaped by drug-related expenses. The ITSA revealed an immediate reduction in drug costs, followed by a gradual resurgence over time. This phenomenon may be attributed to a potential decrease in drug prices, coupled with patients potentially acquiring a greater quantity or opting for pricier medications within the confines of a fixed budget\u003csup\u003e \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e \u003c/sup\u003e. In addition, the average early diagnosis rate of GC in China is only about 10%, mostly in patients with advanced GC\u003csup\u003e \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e \u003c/sup\u003e. Molecular targeted therapy is an important treatment option for patients with advanced GC, aiming to inhibit tumor proliferation and improve survival rates\u003csup\u003e \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e \u003c/sup\u003e. However, targeted therapies are expensive, and the widespread use of targeted therapies can result in higher treatment expenses for patients\u003csup\u003e \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e \u003c/sup\u003e. Although some common targeted therapies for GC, such as Trastuzumab and Apatinib, have been included in China's National Reimbursement Drug List (NRDL), which has alleviated the financial burden on patients\u003csup\u003e \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e \u003c/sup\u003e. Nevertheless, Extended treatment durations and elevated drug costs, despite some alleviation through reimbursement, contribute to elevated personal out-of-pocket (OOP) expenses\u003csup\u003e \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e \u003c/sup\u003e. The advent of new and costly targeted antitumor drugs, initially uncovered by medical insurance, further amplifies the economic strain on patients\u003csup\u003e \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e \u003c/sup\u003e. In 2021, the Chinese Society of Clinical Oncology (CSCO) recommended that Nivolumab in combination with chemotherapy can be used as first-line treatment for advanced or metastatic GC\u003csup\u003e \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e \u003c/sup\u003e. Nivolumab, as the premier PD-1 inhibitor approved for first-line advanced GC treatment in China, brings forth substantial costs, with a study citing approximately \u003cspan\u003e$\u003c/span\u003e88,190.33 compared to \u003cspan\u003e$\u003c/span\u003e9,563.80 for conventional chemotherapy\u003csup\u003e \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e \u003c/sup\u003e. The anticipated widespread adoption of Nivolumab portends a sustained escalation of financial burdens on patients, suggesting that we need to continue to focus on targeted drugs for the treatment of GC in the future and control the costs associated with targeted drugs. On the other hand, in order to receive rebates from pharmaceutical companies, doctors are still incentivized to overprescribe drugs\u003csup\u003e \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e \u003c/sup\u003e. In the future, there is still a need to further regulate medication practices so as to reduce the burden of medication on patients.\u003c/p\u003e \u003cp\u003eThe study suggests that consumables, healthcare services, and examinations sequentially play a pivotal role in influencing hospitalization expenses. Specifically, consumables' impact on the hospitalization costs of gastric cancer (GC) patients closely mirrors that of drug expenses. On the one hand, this may be due to the fact that consumables expenses account for a relatively large portion of hospitalization expenses for GC patients\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. On the other hand, hospitals offset the decrease in drug revenues by increasing the provision of other services or products after the implementation of the UZMDP\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. Corroborating this finding, a study from Changde, China, reveals an observable rise in annual expenditures for inpatient diagnosis, laboratory examinations, and medical consumables following the UZMDP\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Despite China's complete abolition of the medical consumables markup in 2019\u003csup\u003e28\u003c/sup\u003e, this study notes only a marginal 2.7% decrease in consumables expenses for GC patients in 2020 compared to 2019, followed by a resumption of an upward trajectory. The main reason may be that there were more elderly GC patients who used more high-value consumable items in this study, which made the change in consumables expenses not obvious\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Medical consumables are crucial in healthcare. Only by establishing and improving the medical consumables management system and regulating the consumables use behavior of medical personnel, can the patient's consumables expenditure be reduced\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eInitiated in 2015, China's public hospital reform aimed to increase the remuneration for professional services provided by healthcare workers, augment performance-based pay for medical staff, and establish a contemporary hospital management system\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. The study noted a significant surge in healthcare services expenses from 2014 to 2021, underscoring the current emphasis on the labor value of medical workers in China. Since the full implementation of the UZMDP in 2017, the cost of consultation and treatment in public hospitals has continued to rise due to insufficient subsidies and cost-effectiveness motives\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. This contributes significantly to the upward trajectory of healthcare services and examination expenses.\u003c/p\u003e \u003cp\u003eDespite the government's policies to control the rising expenses of drugs and consumables through the UZMDP or the abolition of mark-ups on consumables, the rapid rise in medical expenditure has not been curbed\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. A survey based on 15 tertiary hospitals in Shanxi Province revealed that the increase in total hospitalization expenses, driven by heightened miscellaneous expenses, predominantly affected lower-cost patients, potentially exacerbating health inequalities among populations\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. This highlights the ongoing imperative for healthcare system reform. Rather than relying solely on individual measures to control hospitalization expenses for gastric cancer (GC) patients, a multifaceted approach is recommended. This involves a range of complementary measures to collectively regulate the irrational growth of medical expenses and establish a fair pricing system for medical services to protect the health rights of patients.\u003c/p\u003e \u003cp\u003eConsistent with previous studies, we found that the demographic characteristics of GC patients(e.g., gender and age), the severity of their condition(length of hospitalization stay and whether or not they were operated on), and the characteristics of the hospitals(hospital class) all affected the hospitalization expenses of GC patients. Regarding the demographic characteristics of patients, this study found that elderly GC patients incurred more total hospitalization expenses, which is consistent with previous studies. On the one hand, this is due to the higher incidence of GC among the elderly\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. elderly GC patients undergo complex treatments, leading to increased use of high-value consumables and adjuvant items, thereby amplifying their hospitalization expenses\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Through univariate analysis, we found that male GC patients would incur more treatment costs than female GC patients. In multiple regression analysis, however, we found that male GC patients would incur fewer costs, which is less consistent with previous studies\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. This may be due to Simpson's Paradox in statistics, and further tests with large sample data are still needed in the future\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eRegarding illness severity, our study indicates that patients with more severe conditions incur higher hospitalization expenses than those with milder illnesses. Specifically, patients diagnosed with gastric cancer (GC) undergoing prolonged hospital stays and surgical interventions tend to accumulate elevated hospitalization expenses due to increased healthcare resource utilization, resulting in heightened medical costs\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. However, it has been found that inpatients have invalid hospitalization days, that is, patients need to stay in the hospital for observation even if they do not receive any treatment, which leads to an increase in their costs\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. This not only increases the financial burden of patients but also leads to the waste of healthcare resources, which suggests that we need to improve the efficiency of technical services on the basis of ensuring the quality of healthcare services in the future\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn terms of hospital characteristics as another influencing factor, in line with prior research, our study indicates that patients incur the highest hospitalization expenses when seeking care at tertiary hospitals. This association is likely due to the heightened concentration of patients with severe gastric cancer in tertiary care settings\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe study has certain limitations. Firstly, the unavailability of additional variables, such as patients' income and history of other diseases, introduces a potential confounding effect on the study results. Secondly, the absence of specific gastric cancer (GC) classifications hinders a detailed analysis of the influencing factors of hospitalization expenses among patients with diverse GC classifications. Thirdly, the intricate policy environment, marked by the concurrent implementation of multiple healthcare reform measures, complicates the measurement of the net effect of the Universal Zero-Markup Drug Policy (UZMDP). The results of the Interrupted Time Series Analysis (ITSA) may be influenced by various policies\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. In addition, it is important to consider the potential impact of a large-scale outbreak of COVID-19 in 2020 on the hospitalization expenses of GC patients, which could lead to an increase in their various medical expenses.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe hospitalization expenses for GC patients in Shanghai have shown an upward trend from 2014 to 2021. Our study indicates a reduction in drug expenses following the implementation of the UZMDP. Despite this, drug expenses remain the primary determinant influencing GC patients' hospitalization expenses. Additionally, since the full implementation of the UZMDP, there has been a consistent annual increase in costs related to consumables, healthcare services, and examinations. Notably, consumables expenses have emerged as the second-largest factor impacting the hospitalization expenses of GC patients. In the future, it is still necessary to deepen a variety of healthcare reform measures to control the rise of drugs and consumables expenses. Furthermore, the study identifies advanced age, extended hospitalization duration, surgical interventions, and seeking medical care at secondary and tertiary hospitals as the predominant factors contributing to higher hospitalization expenses for gastric cancer (GC) patients. The study suggests that in the future, further attention should be paid to the disease characteristics of GC patients. Efforts should be directed towards enhancing the utilization rate of medical resources, with the overarching goal of mitigating the economic burden on both GC patients and society.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eGC Gastric cancer\u003c/p\u003e\n\u003cp\u003eUZMDP Universal Zero Markup Drug Policy\u003c/p\u003e\n\u003cp\u003eITSA Interrupted time series analysis\u003c/p\u003e\n\u003cp\u003eGRA New gray relational analysis\u003c/p\u003e\n\u003cp\u003eHIS Hospital Information System\u003c/p\u003e\n\u003cp\u003eLIS Laboratory Information Management System\u003c/p\u003e\n\u003cp\u003eNRDL China\u0026apos;s National Reimbursement Drug List\u003c/p\u003e\n\u003cp\u003eOOP Personal out-of-pocket\u003c/p\u003e\n\u003cp\u003eCSCO Chinese Society of Clinical Oncology\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe experimental protocol was established, according to the ethical guidelines of the Helsinki Declaration and was approved by the Human Ethics Committee of Shanghai Health Development Research Center Ethical Review Board. Written informed consent was obtained from individual or guardian participants.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analysed during this study are included in this published article.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eChunlin Jin and Haiyin Wang conceived and planned the study; Yichun GU conducted the statistical analysis and wrote the manuscript draft; Jiajun Hao wrote the manuscript draft; Xin Cui and Wenqi Tian conducted data cleaning and other data work; Da HE and Hui Sun provided methodological and material advice; Yulin Zhang translated the manuscript. All authors provided constructive feedback regarding the interpretation of the results and the writing of the manuscript. All authors reviewed the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe owe a special debt of gratitude to all the professors and editors, whose hard work benefited us a lot and academically reviewed the paper.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eMorgan E, Arnold M, Camargo MC, et al. The current and future incidence and mortality of gastric cancer in 185 countries, 2020\u0026ndash;40: A population-based modelling study. eClinicalMedicine. 2022;47. doi:10.1016/j.eclinm.2022.101404\u003c/li\u003e\n \u003cli\u003eQu WM, Zhang N.\u0026nbsp;Analysis of related influencing factors of psychological distress during chemotherapy in middle-aged and elderly patients with gastric cancer. 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Hospital Utilization in Patients With Gastric Cancer and Factors Affecting In-Hospital Mortality, Length of Stay, and Costs. Journal of Clinical Gastroenterology. 2019;53(4):e157. doi:10.1097/MCG.0000000000001016\u003c/li\u003e\n \u003cli\u003eHaga K, Matsumoto K, Kitazawa T, Seto K, Fujita S, Hasegawa T. Cost of illness of the stomach cancer in Japan - a time trend and future projections. BMC Health Services Research. 2013;13(1):283. doi:10.1186/1472-6963-13-283\u003c/li\u003e\n \u003cli\u003eBao PP, Wu CX, Gu K, et al. Analysis on incidence of stomach cancer in 2016 and trend of incidence during 2002-2016 in Shanghai. Journal of Diagnostics Concepts \u0026amp; Practice. 2022;21(4):462-469. doi:10.16150/j.1671-2870.2022.04.008\u003c/li\u003e\n \u003cli\u003eThe proportion of registered elderly population in Shanghai exceeds 35% and the aging degree is further deepened-XINHUANET. Accessed October 22, 2023. https://www.xinhuanet.com/politics/2020-05/24/c_1126025478.htm\u003c/li\u003e\n \u003cli\u003eWang LH, Tang YK, Qian MC, Jiang HL. A Comparative Study on the Price Adjustment of Medical Services on Hospital Operations and Doctors\u0026apos; Prescription Behavior under the Universal Zero Markup Drug Policy in Shanghai. Chinese Enterprise Accounting of Villages and towns. 2020;(11):156-160.\u003c/li\u003e\n \u003cli\u003eMcDowall D, McCleary R, Bartos BJ. Interrupted Time Series Analysis. Oxford University Press; 2019.\u003c/li\u003e\n \u003cli\u003eGe ZC, Yu HQ, Zhou T, Xu QY. A new grey relational analysis method. Chinese Journal of Health Statistics. 1999;(1):51-52.\u003c/li\u003e\n \u003cli\u003eCui QM, Zhai TM, HuXB, et al. Analysis of Factors Influencing Hospitalization Costs of Gastric Cancer Patients in Gansu Province, 2014-2017. Chinese Journal of Health Statistics. 2022;39(1):64-67.\u003c/li\u003e\n \u003cli\u003eZhu Z, Wang J, Sun Y, Zhang J, Han P, Yang L. The impact of zero markup drug policy on patients\u0026rsquo; healthcare utilization and expense: An interrupted time series study. Frontiers in Medicine. 2022;9. Accessed October 23, 2023. https://www.frontiersin.org/articles/10.3389/fmed.2022.928690\u003c/li\u003e\n \u003cli\u003eNi Z, Jia J, Cui L, Zhou S, Wang X. The Impact of China\u0026rsquo;s Zero Markup Drug Policy on Hospitalization Expenses for Inpatients in Tertiary Public Hospitals: Evidence Based on Quantile Difference-in-Difference Models. Healthcare. 2021;9:908. doi:10.3390/healthcare9070908\u003c/li\u003e\n \u003cli\u003eChen L, Wu C, Guo Y, He J. Impacts of the drug markup reduction policy on hospital expenditures of esophageal cancer surgery inpatients in Shanghai, China. Public Health. 2020;179:118-126. doi:10.1016/j.puhe.2019.09.023\u003c/li\u003e\n \u003cli\u003eZhu D, Shi X, Nicholas S, Bai Q, He P. Impact of China\u0026rsquo;s healthcare price reforms on traditional Chinese medicine public hospitals in Beijing: an interrupted time-series study. BMJ Open. 2019;9(8):e029646. doi:10.1136/bmjopen-2019-029646\u003c/li\u003e\n \u003cli\u003eShu Y, Ding Y, Zhang Q.\u0026nbsp;Cost-Effectiveness of Nivolumab Plus Chemotherapy vs. Chemotherapy as First-Line Treatment for Advanced Gastric Cancer/Gastroesophageal Junction Cancer/Esophagel Adenocarcinoma in China. Front Oncol. 2022;12:851522. doi:10.3389/fonc.2022.851522\u003c/li\u003e\n \u003cli\u003eRui W, Yue S, Jing G, et al. A Retrospective Study and Current Situation Analysis of Medical Insurance Policies for Non-Small Cell Lung Cancer. Service Science and Management. 2023;12:22. doi:10.12677/SSEM.2023.121003\u003c/li\u003e\n \u003cli\u003eWhy are targeted drugs so expensive? 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Impact of the zero-mark-up drug policy on drug-related expenditures and use in public hospitals, 2016\u0026ndash;2018: an interrupted time series study in Shaanxi. BMJ Open. 2020;10(11):e037034. doi:10.1136/bmjopen-2020-037034\u003c/li\u003e\n \u003cli\u003ePeng Z, Zhan C, Ma X, et al. Did the universal zero-markup drug policy lower healthcare expenditures? Evidence from Changde, China. BMC Health Services Research. 2021;21(1):1205. doi:10.1186/s12913-021-07211-8\u003c/li\u003e\n \u003cli\u003eMa J. Notice of the General Office of the State Council on the Issuance of the Reform Program for the Governance of High-Value Medical Consumables_Health_\u0026nbsp;The State Council of the People\u0026apos;s Republic of China. Accessed November 15, 2023. https://www.gov.cn/zhengce/content/2019-07/31/content_5417518.htm\u003c/li\u003e\n \u003cli\u003eHuang J, Dai T. Public hospital reforms in China: the perspective of hospital directors. BMC Health Services Research. 2019;19(1):142. doi:10.1186/s12913-019-3954-z\u003c/li\u003e\n \u003cli\u003eYusefi AR, Lankarani KB, Bastani P, Radinmanesh M, Kavosi Z. Risk Factors for Gastric Cancer: A Systematic Review. Asian Pac J Cancer Prev. 2018;19(3):591-603. doi:10.22034/APJCP.2018.19.3.591\u003c/li\u003e\n \u003cli\u003eSprenger J, Weinberger N. Simpson\u0026rsquo;s Paradox. In: Zalta EN, ed. The Stanford Encyclopedia of Philosophy. Summer 2021. Metaphysics Research Lab, Stanford University; 2021. Accessed October 23, 2023. https://plato.stanford.edu/archives/sum2021/entries/paradox-simpson/\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-health-services-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bhsr","sideBox":"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/BHSR/default.aspx","title":"BMC Health Services Research","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"gastric cancer, expenditures, hospitalization, interrupted time series analysis, new gray relational analysis, universal zero markup drug policy","lastPublishedDoi":"10.21203/rs.3.rs-3781711/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3781711/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe increasing hospitalization expenses for Gastric Cancer (GC) cause a serious economic burden on society. Although the Chinese government has implemented the Universal Zero Markup Drug Policy (UZMDP) to control the growth of hospitalization expenditures, they remain a rising trend. It\u0026rsquo;s crucial to identify the factors influencing the hospitalization expenses of GC patients. This study aimed to analyze the trends and factors influencing hospitalization expenses of GC patients in Shanghai from 2014 to 2021.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eStudy data were sourced from the Health Network of Shanghai Economic Information Center. We employed interrupted time series analysis (ITSA) to analyze the trends in various medical expenditures before and after the implementation of UZMDP. The degree of association between various medical expenditures and hospitalization expenditures of GC patients was calculated by using the new gray relational analysis (GRA). Furthermore, we used multiple linear regression to identify the influencing factors of hospitalization expenses for GC patients.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003e Our study included a total of 23,335 participants. The ITSA results showed an increasing trend in hospitalization expenses following the implementation of UZMDP. Drug expenses decreased instantaneously with the implementation of UZMDP, but subsequently began to trend upwards. After UZMDP, the expenses of medical consumables, examinations, and healthcare services all showed an upward trend. The new GRA indicated that the influencing factors of hospitalization expenses were drug expenses, consumable expenses, healthcare service expenses, and examination expenses in sequence. Multiple linear regression analysis showed that GC patients aged 60 or below had lower hospitalization expenses (Coefficient=-780.06, P\u0026thinsp;=\u0026thinsp;0.0398). However, factors influencing increased hospitalization expenses included longer length of stay (Coefficient\u0026thinsp;=\u0026thinsp;1753.01, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), surgeries (Coefficient\u0026thinsp;=\u0026thinsp;29047.26, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and hospitalization in the tertiary hospitals (Coefficient\u0026thinsp;=\u0026thinsp;25485.19, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) or secondary hospitals (Coefficient\u0026thinsp;=\u0026thinsp;17755.12, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eHospitalization expenses of GC patients in Shanghai have been rising annually from 2014 to 2021. Despite the implementation of the UZMDP policy, drug expenses remain a major factor in escalating hospitalization expenses. The hospitalization expenses of GC patients are significantly influenced by several factors, including the demographic characteristics of patients, the severity of diseases, and the levels of hospitals. These findings provide a scientific basis for effectively managing the hospitalization expenses of GC.\u003c/p\u003e","manuscriptTitle":"The Universal Zero Markup Drug Policy and Gastric Cancer Hospitalization Expenses: An Analysis of Trends and Influencing Factors in Shanghai from 2014 to 2021","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-11 16:10:58","doi":"10.21203/rs.3.rs-3781711/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-01-09T19:43:58+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-01-09T16:00:07+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-01-09T16:00:07+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Health Services Research","date":"2023-12-20T12:03:30+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-health-services-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bhsr","sideBox":"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/BHSR/default.aspx","title":"BMC Health Services Research","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"26031be9-3947-4722-8898-f03c051faf8c","owner":[],"postedDate":"January 11th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-04-28T16:02:14+00:00","versionOfRecord":{"articleIdentity":"rs-3781711","link":"https://doi.org/10.1186/s12913-025-12422-4","journal":{"identity":"bmc-health-services-research","isVorOnly":false,"title":"BMC Health Services Research"},"publishedOn":"2025-04-22 15:57:41","publishedOnDateReadable":"April 22nd, 2025"},"versionCreatedAt":"2024-01-11 16:10:58","video":"","vorDoi":"10.1186/s12913-025-12422-4","vorDoiUrl":"https://doi.org/10.1186/s12913-025-12422-4","workflowStages":[]},"version":"v1","identity":"rs-3781711","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3781711","identity":"rs-3781711","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}