Structural changes in nursing charges under diagnosis-related group (DRG) payment: A retrospective observational study in a tertiary general hospital in China

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Abstract

Background: In the context of diagnosis-related group (DRG) payment, evidence on structural changes in nursing charge composition in general wards remains limited.
Objective: This study aimed to examine the nursing charge structures and their changes in priority departments within a DRG environment, and to identify whether nursing care is financially undervalued.
Study design: Retrospective observational study. Methods: This retrospective observational study analyzed 215,961 DRG-paid inpatient records (2022-2024) from a large general hospital in Shandong Province. Patients were stratified by relative weight (RW). The analysis was conducted using logistic regression, the entropy weight method, and structural change analysis.
Results: Surgery (OR=46.78, 95%CI 43.76-50.01) and age≥ 60 (OR=4.27, 95%CI 3.99-4.57) were the strongest factors associated with high RW. From 2022-2024, nursing charges in the cardiology department cumulatively decreased by 2.16%, with a contribution rate of 4.63% to the structural changes. Graded nursing care consistently accounted for over 93% each year, while specialized nursing care was consistently maintained at a low level. In the cardiovascular surgery department, nursing charges decreased cumulatively by 0.05% during this period, with a contribution rate of 0.22% to structural changes. Graded nursing care constituted the predominant share, accounting for 79.49%-82.54%. Specialized nursing care represented a key component, consistently exceeding 17%.
Conclusion: This study analyzed nursing charge structure changes in internal medicine and surgery departments. The observed shifts in nursing charge patterns may indicate that the value of nursing care is not fully captured under DRG-based payment. However, this interpretation is based solely on billing data and should therefore be made cautiously. Further research incorporating more granular, nursing-sensitive measures is needed to validate these findings. Integrating nursing workload into DRG may be important for stabilizing valuation and workforce.

Keywords

Diagnosis-Related Group / Charge Structure Analysis / Nursing Administration Research / Retrospective Study

CHANGE HISTORY

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References

[1] Milstein R, Schreyögg J. The end of an era? Activity-based funding based on diag-nosis-related groups: a review of payment reforms in the inpatient sector in 10 high-income countries. Health Policy. 2024; 141:104990. https://doi.org/10.1016/j.healthpol.2023.104990

[2] Goldfield N. The evolution of diagnosis-related groups (DRGs): from its beginnings in case-mix and resource use theory, to its implementation for payment and now for its current utilization for quality within and outside the hospital. Qual Manag Health Care. 2010; 19(1):3-16. https://doi.org/10.1097/QMH.0b013e3181ccbcc3

[3] Chen YJ, Zhang XY, Yan JQ, Xue-Tang, Qian MC, Ying XH. Impact of diagnosis-related groups on inpatient quality of health care: a systematic review and meta-analysis. Inquiry. 2023; 60. https://doi.org/10.1177/00469580231167011469580231167011

[4] Yu XY, Zhang H, Shen LL, et al. Interrupted time series study on the service efficiency and cost structure of DRG payments in the GE 1 group. Front Public Health. 2025; 13:1649042. https://doi.org/10.3389/fpubh.2025.1649042

[5] Griffiths P, Saville C, Ball JE, Monks T. Safer Nursing Care Tool study team. Beyond ratios -flexible and resilient nurse staffing options to deliver cost-effective hospital care and address staff shortages: a simulation and economic modelling study. Int J Nurs Stud. 2021; 117:103901. https://doi.org/10.1016/j.ijnurstu.2021.103901

[6] Bagnasco A, Di Nitto M, Marcomini I, et al. Enlightening nursing care: a protocol for a multicenter observational study measuring nursing work in hospital settings. Healthcare (Basel). 2025; 13(2):167. https://doi.org/10.3390/healthcare13020167

[7] Di Nitto M, Napolitano F, Calzolari M, et al. Billing models for measuring nursing care in inpatient and outpatient settings: a scoping review. BMC Health Serv Res. 2025; 25(1):95. https://doi.org/10.1186/s12913-024-12116-3

[8] Mao HZ, Chen Z, Li W, et al. Nursing cost analysis for acute exacerbation of chronic obstructive pulmonary disease in the intensive care unit. J Clin Nurs. 2025; 34(9):3870-3879. https://doi.org/10.1111/jocn.17603

[9] Jackson J, Anderson JE, Maben J. What is nursing work? A meta-narrative review and integrated framework. Int J Nurs Stud. 2021; 122:103944. https://doi.org/10.1016/j.ijnurstu.2021.103944

[10] Lee SY, Park CG, Boyd AD, et al. Patient‑level nursing cost analysis and cost drivers in acute care: A retrospective longitudinal study. Nurs Outlook. 2026; 74(2):102684. https://doi.org/10.1016/j.outlook.2026.102684

[11] Campling J, Wright HF, Hall GC, et al. Hospitalization costs of adult community-acquired pneumonia in England. J Med Econ. 2022; 25(1):912-918. https://doi.org/10.1080/13696998.2022.2090734

[12] Von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP. The strengthening the reporting of observational studies in epidemiology (STROBE) statement: guidelines for reporting observational studies. Lancet. 2007; 370(9596):1453-1457. https://doi.org/10.1016/S0140-6736(07)61602-X

[13] National Health Commission of the People’s Republic of China. Directory of Medical Institution Diagnostic and Treatment Services. Updated August 31, 2018. Accessed June 2, 2026. https://www.nhc.gov.cn/fzs/c100048/201808/afa9a6d10b9c4ed3ac36358fc20243ff.shtml.

[14] Fernández-Castro M, Rivas-González N, Martín-Gil B, et al. Costs attributable to falls based on Diagnosis-Related Groups (DRGs) analysis of hospitalised patients: a case-control study. Nurs Rep. 2025; 15(9):323. https://doi.org/10.3390/nursrep15090323

[15] Yu QJ, Li YL, Yin Q, et al. Evaluation of inpatient services of tertiary comprehensive hospitals based on DRG payment. Front Public Health. 2024; 12:1300765. https://doi.org/10.3389/fpubh.2024.1300765

[16] Yang S, Huang LH, Li Y, Wang P, Yu YD, Chen X. Comparative study on nursing workload based on the Related Weight of different disease Diagnosis Related Groups. Chinese Nursing Management. 2023; 23(8):1203-1207. https://doi.org/10.3969/j.issn.1672-1756.2023.08.017

[17] Meng ZL, Zou K, Song SH, Wu HZ, Han YL. Associations of Chinese diagnosis-related group systems with inpatient expenditures for older people with hip fracture. BMC Geriatr. 2022; 22(1):169. https://doi.org/10.1186/s12877-022-02865-3

[18] Zhang ZY, Yao XL, Li Y, Dong RY, Jin W, Li YH. DRG payment for male reproductive system malignant tumor surgery: analysis and recommendations on resource con-sumption in a tertiary hospital in China. BMC Surg. 2025; 25(1):207. https://doi.org/10.1186/s12893-025-02940-7

[19] Fan R, Yan ZY, Wang AS, Gao S, Wang LL, Mao SQ. The influence of adverse events on inpatient outcomes in a tertiary hospital using a diagnosis-related group database. Sci Rep. 2024; 14(1):18114. https://doi.org/10.1038/s41598-024-69283-w

[20] Liu Y, Wang G, Qin TG, Kobayashi S, Karako T, Song PP. Comparison of diagnosis-related groups (DRG)-based hospital payment system design and implementation strategies in different countries: the case of ischemic stroke. Biosci Trends. 2024; 18(1):1-10. https://doi.org/10.5582/bst.2023.01027

[21] Zou T, Jin YJ, Chuang YC, Chien CW, Tung TH. The DEMATEL method explores the interdependent relationship structure and weights for diagnosis-related groups system. Front Public Health. 2022; 10:872434. https://doi.org/10.3389/fpubh.2022.872434

[22] Ma XJ, Wang Y. Application of grey relational entropy weight method in DRG per-formance evaluation of inpatient departments. Contrast Media Mol Imaging. 2022; 2022:7348985. https://doi.org/10.1155/2022/7348985

[23] Fetz K, Längler A, Schwermer M, et al. Comparative analysis of resource utilization in integrative anthroposophic and all German pediatric inpatient departments. BMC Health Serv Res. 2020; 20(1):939. https://doi.org/10.1186/s12913-020-05782-6

[24] Welton JM, Longyear R. Emerging nurse billing and reimbursement Models. J Nurs Adm. 2024; 54(9):465-472. https://doi.org/10.1097/NNA.0000000000001456

[25] Racy S, Davidson PM, Peeler A, Hager DN, Street L, Koirala B. A review of inpatient nursing workload measures. J Clin Nurs. 2021; 30(13-14):1799-1809. https://doi.org/10.1111/jocn.15676

[26] Spiva L, McCollum M, Thurman S, et al. A pilot study of a virtual discharge nurse program. J Nurs Care Qual. 2026; 41(2):185-192. https://doi.org/10.1097/NCQ.0000000000000919

[27] National Health Commission of the People's Republic of China. Notice on the Issuance of the National Technical Specifications for Medical Services (2023 Edition). Updated September 28, 2023. Accessed June 2, 2026. https://www.nhc.gov.cn/caiwusi/c100043/202309/b22604883d9a4ca58e82bc61b57cd4fd.shtml.

[28] People's Government of Shandong Province. Notice of the Shandong Provincial Medical Security Bureau on the Issuance of Shandong Province Medical Service Item Prices for Public Medical Institutions (2023 Edition). Updated March 31, 2023. Accessed June 2, 2026. http://www.shandong.gov.cn/art/2023/3/31/art_100623_ 42382.html.

[29] National Health Commission of the People's Republic of China. Standard for nursing classification. Updated August 29, 2023. Accessed June 2, 2026. https://www.nhc. gov.cn/cms-search/downFiles/c566264366804318839addc5aa2d2efd.pdf.

[30] Kim JH. Multicollinearity and misleading statistical results. Korean J Anesthesiol. a)2019; 72(6):558-569. https://doi.org/10.4097/kja.19087

[31] Albahri AS, Hamid RA, Albahri OS, Zaidan AA. Detection-based prioritisation: Framework of multi-laboratory characteristics for asymptomatic COVID-19 carriers based on integrated Entropy-TOPSIS methods. Artif Intell Med. 2021; 111:101983. https://doi.org/10.1016/j.artmed.2020.101983

[32] Hellín Gil MF, Mikla M, Seva Llor AM, Roldán Valcárcel MD, Ibáñez-López FJ, López Montesinos MJ. Multicenter application of a nursing workload measurement scale in adult hospitalization units. Int J Nurs Sci. 2022; 9(4):460-466. https://doi.org/10.1016/j.ijnss.2022.09.011

[33] Ko Y, Park B. Calculating the optimal number of nurses based on nursing intensity by patient classification groups in general units in South Korea: a cross-sectional study. Nurs Open. 2023; 10(6):3982-3991. https://doi.org/10.1002/nop2.1657

[34] Huang YN, Meng GX, Li YX. Analysis of the structural changes of adverse drug re-action reports in China. Herald of Medicine. 2025; 44(6):982-988. https://doi.org/10.3870/j.issn.1004-0781.2025.06.024

[35] Cook CB, Thompson BM, Perrin AJ, Castro JC, McGary AK, Buras MR.Assessing the complexity of inpatient care managed by endocrinologists in a tertiary care teaching hospital. Endocr Pract. 2026; 32(2):188-193. https://doi.org/10.1016/j.eprac.2025.09.200

[36] Hatchimonji JS, Mavroudis CL, Friedman A, et al. National cohort study of resource utilization in older adults with emergency general surgery conditions. J Surg Res. 2023; 290:310-318. https://doi.org/10.1016/j.jss.2023.05.010

[37] Fehr M, Naegele M, Greiling M. Advancement of clinical practice in delivering CAR T-cell therapy: impact on healthcare resource utilization and comparison with au-tologous stem cell transplantation in patients with relapsed/refractory large B-cell lymphomas. Ann Hematol. 2025; 104(9):4779-4790. https://doi.org/10.1007/s00277-025-06564-y

[38] Heckman GA, Gimbel S, Mensink C, et al. The integrated care team: a primary care based-approach to support older adults with complex health needs. Healthc Manag Forum. 2025; 38(3):192-199. https://doi.org/10.1177/08404704241293051

[39] Aljohani KA. Frailty and polypharmacy among geriatric home care patients: an epidemiological analysis and implications for optimised care. BMC Nurs. 2025; 24(1):1206. https://doi.org/10.1186/s12912-025-03850-y

[40] Zhang Q, Lu ZH, Jing SS, Guo D, Wang LJ. Comprehensive evaluation of the im-plementation of close-type county medical alliance in Shandong Province using en-tropy weight TOPSIS method and non-integer rank sum ratio method. BMC Health Serv Res. 2024; 24(1):1193. https://doi.org/10.1186/s12913-024-11659-9

[41] Seligson MT, Lyden SP, Caputo FJ, Kirksey L, Rowse JW, Smolock CJ. Improving clinical documentation of evaluation and management care and patient acuity im-proves reimbursement as well as quality metrics. J Vasc Surg. 2021; 74(6):2055-2062. https://doi.org/10.1016/j.jvs.2021.06.027

[42] Wu ST, Chen YZ, Wu YX, Wu XW. A study on performance evaluation of surgical departments in tertiary public hospitals based on the fuzzy combination-DEA method. Front Public Health. 2026; 14:1801363. https://doi.org/10.3389/fpubh.2026.1801363

[43] Lv C, Gong YH, Wang XH, et al. Correlation between diagnosis-related group weights and nursing time in the cardiology department: cross-sectional study. JMIR Med Inform. 2025; 13:e65549. https://doi.org/10.2196/65549

[44] Quentin W, Stephani V, Berenson RA, et al. How denmark, england, estonia, france, germany, and the usa pay for variable, specialized and low volume care: a cross-country comparison of in-patient payment systems. Int J Health Policy Manag. 2022; 11(12):2940-2950. https://doi.org/10.34172/ijhpm.2022.6536

[45] Hatefimoadab N, Jaghargh MT, Abbaszadeh A, et al. Reforming nursing reimburse-ment: direct payment models under Iran's Nursing Service Act in a global context. Cost Eff Resour Alloc. 2025; 24(1):8. https://doi.org/10.1186/s12962-025-00690-0

[46] Newland JA. Are nurses an invisible and inexhaustible resource? Nurse Pract. a)2024; 49(5):6. https://doi.org/10.1097/01.Npr.0000000000000176

[47] Winkels R, Schad S, Schöffski O, Seelig MH. Auswirkungen des Pflegepersonalstärkungsgesetzes auf die minimal-invasive Chirurgie am Beispiel der Hemikolektomie rechts aus ökonomischer Perspektive [Impact of the Nursing Personnel Strengthening Act on minimally invasive surgery exemplified by right-sided hemicolectomy from an economic perspective]. Chirurg. 2022; 93(5):490-498. https://doi.org/10.1007/s00104-021-01523-5

[48] Cesare M, D’agostino F, Sebastiani E, Nursing And Public Health Group, Damiani G, Cocchieri A. Deciphering the link between diagnosis-related group weight and nur-sing care complexity in hospitalized children: an observational study. Children (Basel). 2025; 12(1):103. https://doi.org/10.3390/children12010103

[49] Cesare M, D'agostino F, Nurchis MC, et al. Determinants of prolonged hospitalization in children and adolescents: a retrospective observational study. J Nurs Scholarsh. 2025; 57(3):412-430. https://doi.org/10.1111/jnu.13045

[50] Cesare M, Zega M. Clinical nursing information systems based on standardized nursing terminologies: How are we doing? J Nurs Scholarsh. 2024; 56(5):625-627. https://doi.org/10.1111/jnu.13023

[51] Cesare M, Nurchis MC, Nursing And Public Health Group, Damiani G, Cocchieri A. Ranking nursing diagnoses by predictive relevance for intensive care unit transfer risk in adult and pediatric patients: a machine learning approach with random forest. Healthcare (Basel). 2025; 13(11):1339. https://doi.org/10.3390/healthcare13111339

[52] Cesare M, Gray R, Cocchieri A. Stop silencing nursing complexity: why standardized nursing terminologies must be heard. Nurs Rep. 2026; 16(1):28. https://doi.org/10.3390/nursrep16010028

[53] Fabrizi D, Bernasconi DP, Locatelli G, et al. How are diagnosis-related groups and staffing allocation systems associated with the complexity of nursing care? An ob-servational study. Healthcare (Basel). 2024; 12(19):1988. https://doi.org/10.3390/healthcare12191988

[54] Griffiths P, Saville C, Ball J, et al. Nursing workload, nurse staffing methodologies and tools: a systematic scoping review and discussion. Int J Nurs Stud. 2020; 103:103487. https://doi.org/10.1016/j.ijnurstu.2019.103487

[55] Borges ML, Caruso P, Nassar Júnior AP. Nursing workload associated with the fre-quency of multidisciplinary rounds: a cross-sectional study. Revista Brasileira De Terapia Intensiva. 2021; 33(1):82-87. https://doi.org/10.5935/0103-507X.20210008

[56] Fore A, Islim F, Shever L. Data collected by the electronic health record is insufficient for estimating nursing costs: an observational study on acute care inpatient nursing units. Int J Nurs Stud. 2019; 91:101-107. https://doi.org/10.1016/j.ijnurstu.2018.11.004