Do Non-local Hospitalized Patients Cost More? A Comparative Study Based on the Implementation of the DRG Payment

Do Non-local Hospitalized Patients Cost More? 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A Comparative Study Based on the Implementation of the DRG Payment Wenbo Du, Xuxian Ren, Yaxin Liu, Hui Yu, Yuying Luo, Xin Yao, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6743500/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Aims: This study investigates whether non-local patients—those hospitalized outside their registered insurance region—incur higher medical expenditures than local patients under China’s Diagnosis-Related Groups (DRG) payment reform. Total hip arthroplasty (THA) was used as a standardized clinical model to evaluate cost disparities and potential cost-shifting behaviors post-reform. Methods: We analyzed 55,532 THA inpatient records from Sichuan Province (2015–2023), classifying patients as local or non-local. Descriptive statistics and univariate tests were conducted using R and SPSS. A multi-period difference-in-differences (DID) model was employed to estimate the reform’s impact, adjusting for individual, institutional, and temporal variables. Results: Non-local patients consistently incurred higher hospitalization costs, despite being younger and having fewer comorbidities. Prior to DRG implementation, the average cost gap was CNY 2,730, mainly from treatment and examination fees. Post-DRG, the gap widened to CNY 2,869 (p < 0.01), with significant increases across all categories—especially consumables and treatment. DID analysis showed significant cost reductions for local patients, while treatment costs for non-local patients rose (β = 0.11, p < 0.01), indicating potential cost-shifting. Conclusions: DRG payment reform effectively reduced costs for local patients but was linked to selective cost increases for non-local patients, particularly in treatment-related spending. These findings suggest that mixed reimbursement models may incentivize differential billing. Ongoing monitoring of expenditure structures is crucial to ensure equitable policy outcomes. DRG Payment Non-local Patients Cost-shifting Total Hip Arthroplasty (THA) Figures Figure 1 Background Diagnosis-Related Groups (DRG) payment systems have been widely adopted globally, especially in high-income countries, as an important mechanism to enhance hospital efficiency, optimize resource allocation, and control healthcare expenditures 1 . With growing health spending and health insurance payment system reforms, controlling medical costs has become a critical issue within public health and healthcare policies 2 , 3 . Currently, China is implementing the DRG-based reimbursement system gradually for local insured patients, aiming at optimizing healthcare spending and improving hospital productivity 4 , 5 . With the implementation of the DRG payment policy, the question of whether health care costs and health care services for groups outside of Medicare coverage are also affected has been widely explored 6 , 7 . In particular, China is currently experiencing an uneven development of healthcare resources. Due to the uneven distribution of healthcare resources, non-local patients refer to individuals receiving medical services outside their registered insurance locations, mainly characterized by those who travel across cities for medical care. However, non-local insured patients typically follow a Fee-For-Service (FFS) payment model, which raises concerns about potential disparities in costs and treatment effects 8 . While the DRG system has been proven effective in reducing the length of hospital stays (LOS) and enhancing efficiency, some studies also explored cost-shifting for FFS patients after DRG implementation 9 , 10 . Impacts on non-local patient costs and received healthcare reremain inadequately studied 11 . Total hip arthroplasty (THA) is a relatively mature surgical method for the treatment of hip joint diseases in orthopedics. With the increasing aging of the population and the continuous progress of hip replacement technology, the number of THA cases is also increasing continuously 12 . Some studies based on national data have shown that hip replacement bundled payment led by doctors is more efficient 13 . This paper takes THA as the research object to explore the changes in the costs of local and non-local patients after the implementation of the DRG payment and whether there is any cost-shifting behavior by physicians .By exploring the changes in medical costs and cost structure among local patients after the implementation of DRG and possible cost-shifting among non-local patients, can validate the effectiveness of the DRG payment and provide suggestions for further adjustments to the DRG payment to promote the balance of quality, efficiency, and fairness. Methods Data Source and Processing Data analyzed in this study were sourced from medical records of patients undergoing total hip arthroplasty (THA) in Sichuan Province from 2015 to 2023. Patients who underwent THA surgery classified under ICD-9 procedure code 81.51 were included. The exclusion criteria were as follows: Missing data: Medical records lacking critical data (e.g., identification number, residence information, or medical payment method). Outlier removal: Records with continuous outcome measures (total hospitalization costs, length of stay) outside the 1st to 99th percentile range. Logical errors: Data with internal inconsistencies, such as discrepancies between patient age and date of birth, mismatches between diseases and patient age, or abnormal admission-discharge counts. A total of 65,126 patient records were initially enrolled in this study. Following exclusion criteria, 31 duplicates were excluded, and 8,030 records with missing values in clinically critical variables were removed. Additionally, 690 records exhibiting logical inconsistencies were discarded. To address extreme values, we applied 1% winsorization to 843 outlier records for key expenditure variables. The final analytical cohort comprised 55,532 cases. All expenditure metrics were inflation-adjusted using the Consumer Price Index (CPI) and log-transformed to approximate normality, thereby ensuring the validity of parametric statistical analyses. All data cleaning procedures were performed using R software Statistical Analysis For data description, normality of variables was assessed via the Shapiro-Wilk test (α = 0.05) using both R and SPSS. Continuous variables conforming to normal distribution were summarized as mean ± standard deviation, while non-normally distributed variables were expressed as median with interquartile range (IQR). Univariate analyses were conducted in SPSS to explore preliminary associations between costs and DRG payment. Independent two-sample t-tests were applied for normally distributed variables, with Mann-Whitney U tests employed as non-parametric alternatives where normality assumptions were violated. For empirical analysis section, considering the phased, city-specific introduction of the DRG payment, this study employed a multi-period difference-in-differences (DID) model 14 . Since the DRG payment was not withdrawn or reversed once implemented, the multi-period DID method was selected to better capture the dynamic implementation effects.The multi-period DID model constructs multiple separate treatment and control datasets for each policy pilot period, stacking them into one integrated dataset, upon which standard DID regression analyses were performed. The model controlled for space(city) and time(year) fixed effects, as well as individual characteristics such as gender, age, Charlson Comorbidity Index (CCI), payment methods, and hospital types. The multi-period DID model is specified as follows: $$\:{Y}_{ict}=\sigma\:+{\alpha\:}_{c}+{\lambda\:}_{t}+{{\beta\:}}_{0}({\text{D}}_{\text{c}\text{t}}\times\:{\text{T}}_{\text{c}\text{t}})+{{\beta\:}}_{1}{\text{X}}_{\text{i}\text{c}\text{t}}{+{\epsilon\:}}_{\text{i}\text{c}\text{t}}$$ In the above equation, the subscripts i,c,t represent patient, city (region of treatment), and year respectively. The terms \(\:{\alpha\:}_{c}\:\) and \(\:{\lambda\:}_{t}\:\) denote city fixed effects and year fixed effects, respectively, controlling for city-level characteristics that are either time-invariant or vary only over time. The key explanatory variable in this multi-period setting is \(\:{\text{D}}_{\text{c}\text{t}}\times\:{\text{T}}_{\text{c}\text{t}}\) , indicating whether city c implemented the DRG pilot payment in year i . Individual-level characteristics \(\:{\text{X}}_{\text{i}\text{c}\text{t}}\) , such as gender, age, Charlson Comorbidity Index (CCI), and medical payment methods, were included as control variables. Finally, \(\:{{\epsilon\:}}_{\text{i}\text{c}\text{t}}\) represents the random error term. Results Basic information [Insert Table 1 here] Table 1 displays patient demographic and clinical characteristics. Gender differences between local and non-local patients were insignificant (p = 0.06), while significant differences existed in age distribution, payment methods, length of stay(LOS), hospital types, CCI, and clinical pathway management (all p < 0.01). Non-local patients were significantly younger, preferred specialty hospitals, and generally presented fewer comorbidities compared to local patients. [Insert Fig. 1 here] Figure 1 illustrates the longitudinal trends in total hospitalization costs for local and non-local patients undergoing THA between 2015 and 2023. Over the nine-year period, non-local patients consistently incurred higher total hospitalization costs compared to local patients. This disparity persists despite baseline characteristics (Table 1) indicating that non-local patients were younger, had fewer comorbidities, and shorter average hospital stays—factors typically associated with reduced expenditures. Such a divergence may suggest systemic cost-shifting practices, wherein hospitals disproportionately allocate expenses to non-local patients reimbursed under fee-for-service (FFS) models rather than DRG-capped local patients.A notable inflection point occurred in 2021, with a sharp decline in costs for both cohorts. This temporal alignment coincides with the province-wide implementation of the DRG policy in Sichuan Province. Changes in Medical Costs Pre- and Post-DRG [Insert Table 2 here] For Pre-DRG period, non-local patients incurred significantly higher total hospitalization costs compared to local patients (50,525 CNY vs. 47,795 CNY, p < 0.01), driven primarily by elevated examination costs (4,388 CNY vs. 3,949 CNY, p < 0.01) and treatment costs (8,863 CNY vs. 6,379 CNY, p 0.10), while medication costs showed no statistically significant disparity. After the DRG payment policy was implemented, the cost gap widened substantially, with non-local patients exhibiting CNY 2,868.82 (p < 0.01) higher total hospitalization costs. All subcategories demonstrated significant disparities: medication (Δ = CNY 371.31, p < 0.01), examination (Δ = CNY 136.81, p < 0.01), treatment (Δ = CNY1,306.01, p < 0.01), and consumables (Δ = CNY 1,065.54, p < 0.01). Strikingly, the post-policy consumables costs reversed their pre-policy trend, becoming significantly higher for non-local patients, which may indicate significant cost-shifting behaviors by healthcare institutions. Multi-Period DID Regression Analysis [Insert Table 3 here] The multi-period DID analysis demonstrates distinct policy-driven behavioral shifts across cost categories (Table 3). For local patients, the DRG policy significantly reduced total hospitalization costs (β = -0.01, p = 0.03), primarily through declines in medication (β =-0.04, p = 0.01), examination (β =-0.07, p < 0.01), and treatment expenditures (β =-0.03, p < 0.01). However, consumables costs exhibited a paradoxical increase (β = 0.10, p = 0.03), likely reflecting hospitals’ strategic substitution toward higher-cost materials to offset DRG-imposed revenue constraints. Among non-local patients, total costs and most subcategories showed no statistically significant post-policy changes. Notably, treatment costs surged disproportionately (β = 0.11, p < 0.01), suggesting targeted cost-shifting to this FFS-reimbursed cohort. This anomaly aligns with hospitals’ potential exploitation of payment model differentials: while DRG has reduced the economic burden of local patients, non-local patients faced intensified billing for treatment services. Discussion This study systematically evaluated the impact of Diagnosis-Related Groups (DRG) payment policies on medical expenditures among local and non-local patients undergoing total hip arthroplasty (THA), with particular emphasis on the potential phenomenon of cost-shifting. This study revealed that the DRG payment policy effectively decreased overall hospitalization expenditures for local patients, particularly evident in pharmaceuticals, diagnostic tests, and treatment costs, which is consistent with international evidence supporting DRG's efficacy in improving cost control 15 , 16 .However, the significant increase in consumables costs suggests preferential selection of higher-cost surgical implants, consistent with international evidence linking DRG adoption to increased use of premium-priced joint replacement components despite clinical equivalence 17 . Total expenditures for non-local patients did not significantly decline, which indicates the cost adjustment across different payment systems is not evident. Further, analysis demonstrated significant increases in treatment expenses for non-local patients, likely reflecting strategic cost-shifting behaviors by hospitals 18 . Given that non-local patients have restricted access to alternative healthcare institutions and limited knowledge of local hospital pricing structures, hospitals may be incentivized to increase costs selectively in these components 19 , 20 . Overall, the analysis indicates that despite its theoretical aims of cost control, the DRG payment model in practice may inadvertently encourage selective institutional behavior detrimental to certain patient populations 21 .Notably, despite being younger and having fewer comorbidities, non-local patients still incurred higher hospitalization costs. Moreover, considering the abnormal increase in treatment costs for non-local patients after the implementation of the DRG policy, non-local patients are more likely to become the targets of cost-shifting There may be some possible limitations in this study. As a retrospective observational study, it lacked longitudinal follow-up of patient health outcomes, potentially overlooking long-term health implications and subsequent healthcare needs following DRG implementation. And, this study mainly relies on objective data to reflect changes in results and does not delve deeply into the theoretical aspects. Despite these limitations, the findings provide valuable insights for DRG payment implementation in other regions and healthcare institutions. Based on the outcomes of this study, future research should explore targeted policy adjustments and institutional interventions aimed at mitigating cost-shifting issues associated with DRG implementation. Specifically, strategies such as refining insurance reimbursement standards, increasing transparency in inter-regional medical billing and strengthening regulation of medical practices are critical 22 . Based on the outcomes of this study, future research should explore targeted policy adjustments and institutional interventions aimed at mitigating cost-shifting issues associated with DRG implementation. Abbreviations Abbreviation Full Term DRG Diagnosis-Related Groups THA Total Hip Arthroplasty DID Difference-in-Differences FFS Fee-for-Service CNY Chinese Yuan CPI Consumer Price Index LOS Length of Stay CCI Charlson Comorbidity Index IQR Interquartile Range ICD International Classification of Diseases SPSS Statistical Package for the Social Sciences Declarations Author Contributions: W.D. led the manuscript drafting and contributed to the overall study coordination. J.W. was responsible for the study concept and design. Y.L. (Yaxin Liu) performed data acquisition and conducted preliminary statistical analyses. X.R. contributed to data interpretation and literature review. H.Y., Y.L. (Yuying Luo), and X.Y. provided access to and support for the original data sources used in this study. All authors critically revised the manuscript for important intellectual content and approved the final version. Availability of data and materials The datasets analyzed during the current study are not publicly available due to data protection regulations, but are available from the corresponding author on reasonable request. Ethics approval and consent to participate This study was approved by the Ethics Committee of West China Hospital, Sichuan University. The study involved a secondary analysis of anonymized hospital administrative data without any personally identifiable information. All necessary administrative permissions to access and use the data were obtained from Sichuan Health Information Center. Given the nature of the data, the requirement for informed consent was waived by the ethics committee. This study was conducted in accordance with the principles of the Declaration of Helsinki. Conflict of Interest Disclosures: All authors declare that they have no conflicts of interest relevant to the content of this article. Funding/Support: This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Role of the Funder/Sponsor: Not applicable. Consent for publication Not applicable. Data Sharing Statement: The data analyzed in this study are derived from anonymized administrative health records and are not publicly available due to data protection regulations. Requests for data access may be considered on reasonable academic grounds and with permission from the data-holding institution. References Mihailovic N, Kocic S, Jakovljevic M. Review of Diagnosis-Related Group-Based Financing of Hospital Care. Health Serv Res Manag Epidemiol. 2016;3:2333392816647892. 10.1177/2333392816647892 . Zou K, Li HY, Zhou D, et al. 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Knee replacement and diagnosis-related groups (DRGs): patient classification and hospital reimbursement in 11 European countries. Knee Surg Sports Traumatol Arthrosc. 2013;21(11):2548–56. 10.1007/s00167-013-2374-6 . Tables Tables 1 to 3 are available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Table1.png Table 1. Baseline characteristics for local and non-local patients (n/%) Table2.png Table 2. Changes in Costs for Local and Non-local Patients Before and After the mplementation of the DRG Policy Table3.png Table 3: Multi-period Difference-in-Differences Regression Results of DRG Policy on Hospitalization Costs for Local and Non-local Patients Cite Share Download PDF Status: Posted Version 1 posted 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. 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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-6743500","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":483361163,"identity":"6efc7b5d-f85c-4ab4-9c57-7c97562df512","order_by":0,"name":"Wenbo Du","email":"","orcid":"","institution":"Chongqing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Wenbo","middleName":"","lastName":"Du","suffix":""},{"id":483361164,"identity":"28782f07-cc73-40b3-a1ac-5692a15478b8","order_by":1,"name":"Xuxian Ren","email":"","orcid":"","institution":"Chongqing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xuxian","middleName":"","lastName":"Ren","suffix":""},{"id":483361165,"identity":"59518e75-307f-4466-89d8-55f6c7001b49","order_by":2,"name":"Yaxin Liu","email":"","orcid":"","institution":"West China Hospital of Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Yaxin","middleName":"","lastName":"Liu","suffix":""},{"id":483361166,"identity":"5146f8b1-6557-4270-8d99-fea32f939239","order_by":3,"name":"Hui Yu","email":"","orcid":"","institution":"Sichuan Health Information Center","correspondingAuthor":false,"prefix":"","firstName":"Hui","middleName":"","lastName":"Yu","suffix":""},{"id":483361167,"identity":"0e6ae03d-41fb-44af-bb40-114e6e1109b1","order_by":4,"name":"Yuying Luo","email":"","orcid":"","institution":"Sichuan Health Information Center","correspondingAuthor":false,"prefix":"","firstName":"Yuying","middleName":"","lastName":"Luo","suffix":""},{"id":483361168,"identity":"77483fd3-5457-4a9d-92c9-7c1108cdb3c2","order_by":5,"name":"Xin Yao","email":"","orcid":"","institution":"Sichuan Health Information Center","correspondingAuthor":false,"prefix":"","firstName":"Xin","middleName":"","lastName":"Yao","suffix":""},{"id":483361169,"identity":"31b31bee-a1d2-4d66-84b4-b941ae9a9efb","order_by":6,"name":"Jin Wen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0ElEQVRIiWNgGAWjYBACAxCRAMSMzQyMDxIqakjTwmzw4MwxIrVAAZvkwxZmwlrMJZKfSTxss8ljbuc9VpHYwMbA396dgFeL5Yw0Y4PEtrRixma+tBuJO2QYJM6c3YDfYTcSDB8kbjuc2NjMY3Yj8Qwbg4FELiEt6R8OJG77D9ZSkNjGTIyWHJAtB8BaGIjTcuZNsUHiv2SQFmOJhDPHeAj75Xj6NskfZ+wSN/afMfz4o6JGjr+9F78WODBsgNA8xCkHAXnilY6CUTAKRsFIAwCUGUuuBmT7sgAAAABJRU5ErkJggg==","orcid":"","institution":"West China Hospital of Sichuan University","correspondingAuthor":true,"prefix":"","firstName":"Jin","middleName":"","lastName":"Wen","suffix":""}],"badges":[],"createdAt":"2025-05-25 11:53:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6743500/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6743500/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":86673569,"identity":"e0a8b6a2-afb5-4dad-830c-bebef41c0863","added_by":"auto","created_at":"2025-07-14 11:48:20","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":224115,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTotal Hospitalization Costs for Local and Non-local Patients from 2015 to 2023\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-6743500/v1/965e361f95750e5ddc564b5b.png"},{"id":105892922,"identity":"23330562-8af1-4ecc-8cbf-29ce298b19d7","added_by":"auto","created_at":"2026-04-01 08:15:01","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":762380,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6743500/v1/22f4d126-5543-4e20-b006-b90d49e800d1.pdf"},{"id":86673567,"identity":"e67c54a4-6861-46be-8fa0-c3167100797d","added_by":"auto","created_at":"2025-07-14 11:48:20","extension":"png","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":51369,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTable 1. Baseline characteristics for local and non-local patients (n/%)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Table1.png","url":"https://assets-eu.researchsquare.com/files/rs-6743500/v1/d50caf20a3e0364b1a9fd4c9.png"},{"id":86672435,"identity":"f0910a34-233f-4e83-a196-64da787db240","added_by":"auto","created_at":"2025-07-14 11:40:20","extension":"png","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":45178,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTable 2. Changes in Costs for Local and Non-local Patients Before and After the mplementation of the DRG Policy\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Table2.png","url":"https://assets-eu.researchsquare.com/files/rs-6743500/v1/667db1cef1b84d5b1b41fc66.png"},{"id":86672438,"identity":"53970b57-d6a9-48af-96d4-b054d857fc4e","added_by":"auto","created_at":"2025-07-14 11:40:20","extension":"png","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":28783,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTable 3: Multi-period Difference-in-Differences Regression Results of DRG Policy on Hospitalization Costs for Local and Non-local Patients\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Table3.png","url":"https://assets-eu.researchsquare.com/files/rs-6743500/v1/ce001a365c2fd4ba1c363910.png"}],"financialInterests":"No competing interests reported.","formattedTitle":"Do Non-local Hospitalized Patients Cost More? A Comparative Study Based on the Implementation of the DRG Payment","fulltext":[{"header":"Background","content":"\u003cp\u003eDiagnosis-Related Groups (DRG) payment systems have been widely adopted globally, especially in high-income countries, as an important mechanism to enhance hospital efficiency, optimize resource allocation, and control healthcare expenditures\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. With growing health spending and health insurance payment system reforms, controlling medical costs has become a critical issue within public health and healthcare policies\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Currently, China is implementing the DRG-based reimbursement system gradually for local insured patients, aiming at optimizing healthcare spending and improving hospital productivity \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eWith the implementation of the DRG payment policy, the question of whether health care costs and health care services for groups outside of Medicare coverage are also affected has been widely explored\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. In particular, China is currently experiencing an uneven development of healthcare resources. Due to the uneven distribution of healthcare resources, non-local patients refer to individuals receiving medical services outside their registered insurance locations, mainly characterized by those who travel across cities for medical care. However, non-local insured patients typically follow a Fee-For-Service (FFS) payment model, which raises concerns about potential disparities in costs and treatment effects \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eWhile the DRG system has been proven effective in reducing the length of hospital stays (LOS) and enhancing efficiency, some studies also explored cost-shifting for FFS patients after DRG implementation\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Impacts on non-local patient costs and received healthcare reremain inadequately studied\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eTotal hip arthroplasty (THA) is a relatively mature surgical method for the treatment of hip joint diseases in orthopedics. With the increasing aging of the population and the continuous progress of hip replacement technology, the number of THA cases is also increasing continuously\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Some studies based on national data have shown that hip replacement bundled payment led by doctors is more efficient\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. This paper takes THA as the research object to explore the changes in the costs of local and non-local patients after the implementation of the DRG payment and whether there is any cost-shifting behavior by physicians .By exploring the changes in medical costs and cost structure among local patients after the implementation of DRG and possible cost-shifting among non-local patients, can validate the effectiveness of the DRG payment and provide suggestions for further adjustments to the DRG payment to promote the balance of quality, efficiency, and fairness.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eData Source and Processing\u003c/h2\u003e\u003cp\u003eData analyzed in this study were sourced from medical records of patients undergoing total hip arthroplasty (THA) in Sichuan Province from 2015 to 2023. Patients who underwent THA surgery classified under ICD-9 procedure code 81.51 were included.\u003c/p\u003e\u003cp\u003eThe exclusion criteria were as follows:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eMissing data: Medical records lacking critical data (e.g., identification number, residence information, or medical payment method).\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eOutlier removal: Records with continuous outcome measures (total hospitalization costs, length of stay) outside the 1st to 99th percentile range.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eLogical errors: Data with internal inconsistencies, such as discrepancies between patient age and date of birth, mismatches between diseases and patient age, or abnormal admission-discharge counts.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eA total of 65,126 patient records were initially enrolled in this study. Following exclusion criteria, 31 duplicates were excluded, and 8,030 records with missing values in clinically critical variables were removed. Additionally, 690 records exhibiting logical inconsistencies were discarded. To address extreme values, we applied 1% winsorization to 843 outlier records for key expenditure variables. The final analytical cohort comprised 55,532 cases. All expenditure metrics were inflation-adjusted using the Consumer Price Index (CPI) and log-transformed to approximate normality, thereby ensuring the validity of parametric statistical analyses. All data cleaning procedures were performed using R software\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eFor data description, normality of variables was assessed via the Shapiro-Wilk test (α\u0026thinsp;=\u0026thinsp;0.05) using both R and SPSS. Continuous variables conforming to normal distribution were summarized as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation, while non-normally distributed variables were expressed as median with interquartile range (IQR). Univariate analyses were conducted in SPSS to explore preliminary associations between costs and DRG payment. Independent two-sample t-tests were applied for normally distributed variables, with Mann-Whitney U tests employed as non-parametric alternatives where normality assumptions were violated.\u003c/p\u003e\u003cp\u003eFor empirical analysis section, considering the phased, city-specific introduction of the DRG payment, this study employed a multi-period difference-in-differences (DID) model\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Since the DRG payment was not withdrawn or reversed once implemented, the multi-period DID method was selected to better capture the dynamic implementation effects.The multi-period DID model constructs multiple separate treatment and control datasets for each policy pilot period, stacking them into one integrated dataset, upon which standard DID regression analyses were performed. The model controlled for space(city) and time(year) fixed effects, as well as individual characteristics such as gender, age, Charlson Comorbidity Index (CCI), payment methods, and hospital types.\u003c/p\u003e\u003cp\u003eThe multi-period DID model is specified as follows:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:{Y}_{ict}=\\sigma\\:+{\\alpha\\:}_{c}+{\\lambda\\:}_{t}+{{\\beta\\:}}_{0}({\\text{D}}_{\\text{c}\\text{t}}\\times\\:{\\text{T}}_{\\text{c}\\text{t}})+{{\\beta\\:}}_{1}{\\text{X}}_{\\text{i}\\text{c}\\text{t}}{+{\\epsilon\\:}}_{\\text{i}\\text{c}\\text{t}}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eIn the above equation, the subscripts i,c,t represent patient, city (region of treatment), and year respectively. The terms \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\alpha\\:}_{c}\\:\\)\u003c/span\u003e\u003c/span\u003eand \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\lambda\\:}_{t}\\:\\)\u003c/span\u003e\u003c/span\u003edenote city fixed effects and year fixed effects, respectively, controlling for city-level characteristics that are either time-invariant or vary only over time. The key explanatory variable in this multi-period setting is \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{D}}_{\\text{c}\\text{t}}\\times\\:{\\text{T}}_{\\text{c}\\text{t}}\\)\u003c/span\u003e\u003c/span\u003e, indicating whether city \u003cem\u003ec\u003c/em\u003e implemented the DRG pilot payment in year \u003cem\u003ei\u003c/em\u003e. Individual-level characteristics \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{X}}_{\\text{i}\\text{c}\\text{t}}\\)\u003c/span\u003e\u003c/span\u003e, such as gender, age, Charlson Comorbidity Index (CCI), and medical payment methods, were included as control variables. Finally,\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\epsilon\\:}}_{\\text{i}\\text{c}\\text{t}}\\)\u003c/span\u003e\u003c/span\u003e represents the random error term.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n \u003ch2\u003eBasic information\u003c/h2\u003e\n \u003cp\u003e[Insert Table\u0026nbsp;1 here]\u003c/p\u003e\n \u003cp\u003eTable 1 displays patient demographic and clinical characteristics. Gender differences between local and non-local patients were insignificant (p\u0026thinsp;=\u0026thinsp;0.06), while significant differences existed in age distribution, payment methods, length of stay(LOS), hospital types, CCI, and clinical pathway management (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Non-local patients were significantly younger, preferred specialty hospitals, and generally presented fewer comorbidities compared to local patients.\u003c/p\u003e\n \u003cp\u003e[Insert Fig.\u0026nbsp;1 here]\u003c/p\u003e\n \u003cp\u003eFigure 1 illustrates the longitudinal trends in total hospitalization costs for local and non-local patients undergoing THA between 2015 and 2023. Over the nine-year period, non-local patients consistently incurred higher total hospitalization costs compared to local patients. This disparity persists despite baseline characteristics (Table\u0026nbsp;1) indicating that non-local patients were younger, had fewer comorbidities, and shorter average hospital stays\u0026mdash;factors typically associated with reduced expenditures. Such a divergence may suggest systemic cost-shifting practices, wherein hospitals disproportionately allocate expenses to non-local patients reimbursed under fee-for-service (FFS) models rather than DRG-capped local patients.A notable inflection point occurred in 2021, with a sharp decline in costs for both cohorts. This temporal alignment coincides with the province-wide implementation of the DRG policy in Sichuan Province.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eChanges in Medical Costs Pre- and Post-DRG\u003c/h3\u003e\n\u003cp\u003e[Insert Table\u0026nbsp;2 here]\u003c/p\u003e\n\u003cp\u003eFor Pre-DRG period, non-local patients incurred significantly higher total hospitalization costs compared to local patients (50,525 CNY vs. 47,795 CNY, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), driven primarily by elevated examination costs (4,388 CNY vs. 3,949 CNY, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and treatment costs (8,863 CNY vs. 6,379 CNY, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Notably, consumables costs for non-local patients were marginally lower (\u0026Delta; = -218.98, p\u0026thinsp;\u0026gt;\u0026thinsp;0.10), while medication costs showed no statistically significant disparity.\u003c/p\u003e\n\u003cp\u003eAfter the DRG payment policy was implemented, the cost gap widened substantially, with non-local patients exhibiting CNY 2,868.82 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) higher total hospitalization costs. All subcategories demonstrated significant disparities: medication (\u0026Delta;\u0026thinsp;=\u0026thinsp;CNY 371.31, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), examination (\u0026Delta;\u0026thinsp;=\u0026thinsp;CNY 136.81, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), treatment (\u0026Delta;\u0026thinsp;=\u0026thinsp;CNY1,306.01, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and consumables (\u0026Delta;\u0026thinsp;=\u0026thinsp;CNY 1,065.54, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Strikingly, the post-policy consumables costs reversed their pre-policy trend, becoming significantly higher for non-local patients, which may indicate significant cost-shifting behaviors by healthcare institutions.\u003c/p\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003eMulti-Period DID Regression Analysis\u003c/h2\u003e\n \u003cp\u003e[Insert Table\u0026nbsp;3 here]\u003c/p\u003e\n \u003cp\u003eThe multi-period DID analysis demonstrates distinct policy-driven behavioral shifts across cost categories (Table\u0026nbsp;3). For local patients, the DRG policy significantly reduced total hospitalization costs (\u0026beta; = -0.01, p\u0026thinsp;=\u0026thinsp;0.03), primarily through declines in medication (\u0026beta; =-0.04, p\u0026thinsp;=\u0026thinsp;0.01), examination (\u0026beta; =-0.07, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), and treatment expenditures (\u0026beta; =-0.03, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). However, consumables costs exhibited a paradoxical increase (\u0026beta;\u0026thinsp;=\u0026thinsp;0.10, p\u0026thinsp;=\u0026thinsp;0.03), likely reflecting hospitals\u0026rsquo; strategic substitution toward higher-cost materials to offset DRG-imposed revenue constraints.\u003c/p\u003e\n \u003cp\u003eAmong non-local patients, total costs and most subcategories showed no statistically significant post-policy changes. Notably, treatment costs surged disproportionately (\u0026beta;\u0026thinsp;=\u0026thinsp;0.11, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), suggesting targeted cost-shifting to this FFS-reimbursed cohort. This anomaly aligns with hospitals\u0026rsquo; potential exploitation of payment model differentials: while DRG has reduced the economic burden of local patients, non-local patients faced intensified billing for treatment services.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study systematically evaluated the impact of Diagnosis-Related Groups (DRG) payment policies on medical expenditures among local and non-local patients undergoing total hip arthroplasty (THA), with particular emphasis on the potential phenomenon of cost-shifting.\u003c/p\u003e\u003cp\u003eThis study revealed that the DRG payment policy effectively decreased overall hospitalization expenditures for local patients, particularly evident in pharmaceuticals, diagnostic tests, and treatment costs, which is consistent with international evidence supporting DRG's efficacy in improving cost control\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e.However, the significant increase in consumables costs suggests preferential selection of higher-cost surgical implants, consistent with international evidence linking DRG adoption to increased use of premium-priced joint replacement components despite clinical equivalence \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eTotal expenditures for non-local patients did not significantly decline, which indicates the cost adjustment across different payment systems is not evident. Further, analysis demonstrated significant increases in treatment expenses for non-local patients, likely reflecting strategic cost-shifting behaviors by hospitals\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Given that non-local patients have restricted access to alternative healthcare institutions and limited knowledge of local hospital pricing structures, hospitals may be incentivized to increase costs selectively in these components\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eOverall, the analysis indicates that despite its theoretical aims of cost control, the DRG payment model in practice may inadvertently encourage selective institutional behavior detrimental to certain patient populations\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e.Notably, despite being younger and having fewer comorbidities, non-local patients still incurred higher hospitalization costs. Moreover, considering the abnormal increase in treatment costs for non-local patients after the implementation of the DRG policy, non-local patients are more likely to become the targets of cost-shifting\u003c/p\u003e\u003cp\u003eThere may be some possible limitations in this study. As a retrospective observational study, it lacked longitudinal follow-up of patient health outcomes, potentially overlooking long-term health implications and subsequent healthcare needs following DRG implementation. And, this study mainly relies on objective data to reflect changes in results and does not delve deeply into the theoretical aspects.\u003c/p\u003e\u003cp\u003eDespite these limitations, the findings provide valuable insights for DRG payment implementation in other regions and healthcare institutions. Based on the outcomes of this study, future research should explore targeted policy adjustments and institutional interventions aimed at mitigating cost-shifting issues associated with DRG implementation. Specifically, strategies such as refining insurance reimbursement standards, increasing transparency in inter-regional medical billing and strengthening regulation of medical practices are critical\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Based on the outcomes of this study, future research should explore targeted policy adjustments and institutional interventions aimed at mitigating cost-shifting issues associated with DRG implementation.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eAbbreviation\u003c/div\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003eFull Term\u003c/div\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eDRG\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003eDiagnosis-Related Groups\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eTHA\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003eTotal Hip Arthroplasty\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eDID\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003eDifference-in-Differences\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eFFS\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003eFee-for-Service\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eCNY\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003eChinese Yuan\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eCPI\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003eConsumer Price Index\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eLOS\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003eLength of Stay\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eCCI\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003eCharlson Comorbidity Index\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eIQR\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003eInterquartile Range\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eICD\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003eInternational Classification of Diseases\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cdiv class=\"SimplePara\"\u003eSPSS\u003c/div\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cdiv class=\"SimplePara\"\u003eStatistical Package for the Social Sciences\u003c/div\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003cbr/\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eW.D. led the manuscript drafting and contributed to the overall study coordination. J.W. was responsible for the study concept and design. Y.L. (Yaxin Liu) performed data acquisition and conducted preliminary statistical analyses. X.R. contributed to data interpretation and literature review. H.Y., Y.L. (Yuying Luo), and X.Y. provided access to and support for the original data sources used in this study. All authors critically revised the manuscript for important intellectual content and approved the final version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets analyzed during the current study are not publicly available due to data protection regulations, but are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Ethics Committee of West China Hospital, Sichuan University. The study involved a secondary analysis of anonymized hospital administrative data without any personally identifiable information. All necessary administrative permissions to access and use the data were obtained from Sichuan Health Information Center. Given the nature of the data, the requirement for informed consent was waived by the ethics committee. This study was conducted in accordance with the principles of the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest Disclosures:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors declare that they have no conflicts of interest relevant to the content of this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding/Support:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRole of the Funder/Sponsor:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\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\u003eData Sharing Statement:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data analyzed in this study are derived from anonymized administrative health records and are not publicly available due to data protection regulations. 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Knee Surg Sports Traumatol Arthrosc. 2013;21(11):2548\u0026ndash;56. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00167-013-2374-6\u003c/span\u003e\u003cspan address=\"10.1007/s00167-013-2374-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 3 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"DRG Payment, Non-local Patients, Cost-shifting, Total Hip Arthroplasty (THA)","lastPublishedDoi":"10.21203/rs.3.rs-6743500/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6743500/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eAims:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study investigates whether non-local patients—those hospitalized outside their registered insurance region—incur higher medical expenditures than local patients under China’s Diagnosis-Related Groups (DRG) payment reform. Total hip arthroplasty (THA) was used as a standardized clinical model to evaluate cost disparities and potential cost-shifting behaviors post-reform.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe analyzed 55,532 THA inpatient records from Sichuan Province (2015–2023), classifying patients as local or non-local. Descriptive statistics and univariate tests were conducted using R and SPSS. A multi-period difference-in-differences (DID) model was employed to estimate the reform’s impact, adjusting for individual, institutional, and temporal variables.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNon-local patients consistently incurred higher hospitalization costs, despite being younger and having fewer comorbidities. Prior to DRG implementation, the average cost gap was CNY 2,730, mainly from treatment and examination fees. Post-DRG, the gap widened to CNY 2,869 (p \u0026lt; 0.01), with significant increases across all categories—especially consumables and treatment. DID analysis showed significant cost reductions for local patients, while treatment costs for non-local patients rose (β = 0.11, p \u0026lt; 0.01), indicating potential cost-shifting.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDRG payment reform effectively reduced costs for local patients but was linked to selective cost increases for non-local patients, particularly in treatment-related spending. These findings suggest that mixed reimbursement models may incentivize differential billing. Ongoing monitoring of expenditure structures is crucial to ensure equitable policy outcomes.\u003c/p\u003e","manuscriptTitle":"Do Non-local Hospitalized Patients Cost More? A Comparative Study Based on the Implementation of the DRG Payment","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-14 11:40:15","doi":"10.21203/rs.3.rs-6743500/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3cf11c90-201d-495f-9def-039ae0802bc8","owner":[],"postedDate":"July 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-01T08:14:44+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-14 11:40:15","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6743500","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6743500","identity":"rs-6743500","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}