{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T06:13:44Z","timestamp":1788416024666,"version":"build-2803163510"},"reference-count":37,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T00:00:00Z","timestamp":1788393600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Public Health"],"abstract":"\n Background<\/jats:title>\n The nationwide rollout of Diagnosis-Intervention Packet (DIP) payment reform in China aims to enhance inpatient cost efficiency, yet high-magnification cases impose escalating financial burdens on tertiary hospitals. This study characterized the cost profiles and independent determinants of high-magnification cases under DIP to inform precision cost governance and medical insurance policy optimization.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n This retrospective observational study included 191,490 consecutive inpatient admissions from a National Health Commission-administered hospital in southern China (2024\u20132025). High-magnification cases were defined as actual hospitalization costs exceeding 2 times the standard DIP reimbursement benchmark in the present study. We analyzed their clinical features, cost composition, and multi-dimensional distribution. Multi-variable logistic regression adjusted for department-level fixed effects was applied to identify independent determinants.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n A total of 17,929 (9.36%) high-magnification cases were identified. These cases had an average hospitalization cost of 65,366.0 Chinese Yuan (CNY), which was 2.38 times the overall average of 27,444.7 CNY, and a mean length of stay of 9.1 days. 49.42% of high-magnification cases resulted in DIP payment deficits, with a mean deficit of 1,492.1 CNY per case. The Charlson Comorbidity Index (CCI) fluctuated between 1.8 and 2.0 during the study period. Using multivariate logistic regression, the confidence intervals (CI) and odds ratios (OR) of influencing factors were calculated. Independent positive predictors included length of stay (LOS) (OR\u202f=\u202f1.139, 95% CI 1.136\u20131.143), CCI (OR\u202f=\u202f1.068, 95% CI 1.057\u20131.080), consumable cost proportion (OR\u202f=\u202f1.029, 95% CI 1.026\u20131.031), and medication cost proportion (OR\u202f=\u202f1.053, 95% CI 1.051\u20131.055). Subgroup analyses further suggested the highest high-magnification risk (all\n p<\/jats:italic>\n \u202f&lt;\u202f0.001) for\n Secondary comprehensive disease category<\/jats:italic>\n (OR\u202f=\u202f9.474, 95% CI 8.028\u201311.180),\n Pregnancy, childbirth &amp; puerperium<\/jats:italic>\n (OR\u202f=\u202f8.162, 95% CI 4.503\u201314.793),\n Health status &amp; healthcare contact factors<\/jats:italic>\n (OR\u202f=\u202f7.292, 95% CI 5.575\u20139.537) and\n Skin &amp; subcutaneous tissue disorders<\/jats:italic>\n (OR\u202f=\u202f3.695, 95% CI 2.715\u20135.029).\n <\/jats:p>\n <\/jats:sec>\n \n Conclusion<\/jats:title>\n High-magnification DIP cases feature excessive resource consumption and high deficit rates. Prolonged LOS, consumables and medication costs are core drivers. Targeted cost control and optimized reimbursement benchmarks for complex conditions is beneficial for improving the utilization efficiency of medical insurance funds and maintaining the stable operation of hospitals while ensuring medical quality.<\/jats:p>\n <\/jats:sec>","DOI":"10.3389\/fpubh.2026.1915516","type":"journal-article","created":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T05:23:33Z","timestamp":1788413013000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["High-magnification inpatient cases under DIP payment reform: prevalence, cost burden, and risk factors in an NHC-administered hospital in China"],"prefix":"10.3389","volume":"14","author":[{"given":"Jianjun","family":"Lu","sequence":"first","affiliation":[{"name":"Department of Quality Management and Evaluation, The First Affiliated Hospital, Sun Yat-Sen University","place":["Guangzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhuochen","family":"Lin","sequence":"additional","affiliation":[{"name":"Department of Quality Management and Evaluation, The First Affiliated Hospital, Sun Yat-Sen University","place":["Guangzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ziyi","family":"Xin","sequence":"additional","affiliation":[{"name":"Department of Quality Management and Evaluation, The First Affiliated Hospital, Sun Yat-Sen University","place":["Guangzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junfeng","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Quality Management and Evaluation, The First Affiliated Hospital, Sun Yat-Sen University","place":["Guangzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuting","family":"Gu","sequence":"additional","affiliation":[{"name":"Department of Quality Management and Evaluation, The First Affiliated Hospital, Sun Yat-Sen University","place":["Guangzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ying","family":"Xiong","sequence":"additional","affiliation":[{"name":"Department of Quality Management and Evaluation, The First Affiliated Hospital, Sun Yat-Sen University","place":["Guangzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wujun","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Quality Management and Evaluation, The First Affiliated Hospital, Sun Yat-Sen University","place":["Guangzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,9,3]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"100066","DOI":"10.1016\/j.hpopen.2022.100066","article-title":"Development of a novel hospital payment system - big data diagnosis & intervention packet","volume":"3","author":"Xie","year":"2022","journal-title":"Health Policy Open"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"154","DOI":"10.1258\/hsmr.2010.010002","article-title":"Homogeneity of the German diagnosis-related groups","volume":"23","author":"Stausberg","year":"2010","journal-title":"Health Serv Manag Res"},{"key":"ref3","doi-asserted-by":"publisher","first-page":"454","DOI":"10.1002\/hec.3033","article-title":"Do diagnosis-related group-based payments incentivise hospitals to adjust output mix?","volume":"24","author":"Liang","year":"2015","journal-title":"Health Econ"},{"key":"ref4","doi-asserted-by":"publisher","first-page":"2055","DOI":"10.2147\/rmhp.s467471","article-title":"Does the diagnosis-intervention packet payment reform impact medical costs, quality, and medical service capacity in secondary and tertiary hospitals? 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