Structural Analysis of Inpatient Medical Care for Breast Cancer Cases Based on Evaluation of Applying Statistical Clinical Groups

Introduction: Specialized inpatient care leads in treatment of cancer cases. Its financing is based on the model of  statistical clinical groups, the analysis of which helps assess service effectiveness, enhance care quality and accessibility, and optimize resources.

Objective: To conduct a structural analysis of specialized medical care provided to breast cancer patients at the Tomsk Regional Oncology Dispensary in 2020–2024 by statistical clinical groups.

Materials and methods: The study was conducted using depersonalized data on breast cancer patients treated at the regional oncology dispensary. We analyzed the number of hospitalized patients, their distribution by age, department, and statistical clinical group code, and the dynamics of the cost-intensity coefficient within groups.

Results: During the study period, the majority of hospitalized cases were women aged 55–64 (32.5 ± 3.5 %) and 65–74 (27.5 ± 1.1 %). Most patients (76.8 % in 2024) were treated in the Oncology Department, with the highest number of completed cases (14,083; 80.7 %) involving drug therapy. In day hospitals, Level 4 Drug Therapy prevailed. In the round-the-clock inpatient department, Level 1 Mastectomy was most common among patients aged 55 years and older (1,294 cases; 24.8 %), while Level 1 Drug Therapy dominated in those under 54 years of age (958 cases; 23.5 %). The relative cost-intensity coefficient declined for most drug therapy statistical clinical groups by 2024, except for those of Levels 10–11 in day hospitals and Levels 11–13 in 24-hour hospitals, demonstrating an increase.

Conclusion: The study results highlight the importance of optimizing age- and cost-aware resource planning to improve clinical economic standards, develop differentiated approaches to funding, forecast departmental workloads, and support data-driven healthcare management.

1. Sahoo H, Govil D, James KS, Prasad RD. Health issues, health care utilization and health care expenditure among elderly in India: Thematic review of literature. Aging Health Res. 2021;1(2):100012. doi: 10.1016/j.ahr.2021.100012

2. Bosque-Mercader L, Siciliani L. The association between bed occupancy rates and hospital quality in the English National Health Service. Eur J Health Econ. 2023;24(2):209-236. doi: 10.1007/s10198-022-01464-8

3. Wu SW, Pan Q, Chen T. Research on diagnosis-related group grouping of inpatient medical expenditure in colorectal cancer patients based on a decision tree model. World J Clin Cases. 2020;8(12):2484-2493. doi: 10.12998/wjcc.v8.i12.2484

4. Kudelina OV, Kaneva МA. The health capital and efficiency of regional health care systems: The conformances and contradictions. Problemy Sotsial’noy Gigieny, Zdravookhraneniya i Istorii Meditsiny. 2022;30(1):24-32. (In Russ.) doi: 10.32687/0869-866X-2022-30-1-24-32

5. Jakovljevic M, Lamnisos D, Westerman R, Chattu VK, Cerda A. Future health spending forecast in leading emerging BRICS markets in 2030: Health policy implications. Health Res Policy Syst. 2022;20(1):23. doi: 10.1186/s12961-022-00822-5

6. Omelyanovskiy VV, Zheleznyakova IA, Bezdenezhnykh TP, Lazareva ML, Fedyaev DV. The review of the foreign experience on the financing of innovative medical technologies. Farmakoekonomika. Sovremennaya Farmakoekonomika i Farmakoepidemiologiya. 2020;13(3):316-323. (In Russ.) doi: 10.17749/2070-4909/farmakoekonomika.2020.055

7. Rumyantseva EI, Zheleznyakova IA, Plakhotnik OS, et al. Changes in diagnosis-related group payment model in the Russian Federation in 2024. Meditsinskie Tekhnologii. Otsenka i Vybor. 2024;(2(46)):10-21. (In Russ.) doi: 10.17116/medtech20244602110

8. Son IM, Evdakov VA, Manoshkina EM, Bantyeva MN, Melnikov YuYu. Current state of the cardiology bed fund in the Russian Federation and its dynamics during 2010–2018. Kubanskiy Nauchnyy Meditsinskiy Vestnik. 2020;27(4):105-118. (In Russ.) doi: 10.25207/1608-6228-2020-27-4-105-118

9. Gordeev SS, Avxentyeva MV, Ledovskikh YuA, et al. Inpatient care: The evolution of payment methods and their impact on quality. Prakticheskaya Onkologiya. 2020;21(2):91-100. (In Russ.). doi: 10.31917/2102091

10. Avxentyeva MV, Petrovskiy AV, Zheleznyakova IA, Zuev AV, Seryapina YuV, Sura MV. Development of diagnosis-related groups for malignant neoplasms diagnostics and treatment in the Russian Federation. Meditsinskie Tekhnologii. Otsenka i Vybor. 2021;(3(43)):12-20. (In Russ.) doi: 10.17116/medtech20214303112

11. Liu X, Liu F, Wang L, Wu M, Yang L, Wei L. Performance evaluation of medical service for breast cancer patients based on diagnosis related groups. BMC Health Serv Res. 2021;21(1):496. doi: 10.1186/s12913-021-06439-8

12. Ermolitskaya MZ, Kiku PF, Abakumov AI. Breast cancer mortality in the Primorsky Region: Data analysis and modeling. Zdorov’e Naseleniya i Sreda Obitaniya. 2021;29(11):16-22. (In Russ.) doi: 10.35627/2219-5238/2021-29-11-16-22

13. Ratri DMN, Fitriyah AA, Mawaddah MHF, Suprapti B, Romadhon PZ, Samirah. Analysis of cost of illness and diagnosis-related group payment system in breast cancer patients with chemotherapy in Indonesia. Pharm Ed. 2024;24(3):147-152. doi: 10.46542/pe.2024.243.147152

14. Fedyaev DV, Omelyanovskiy VV, LazarevaML, Seryapina YuV, Ledovskikh YuA. Diagnosis-related groups and payments for the treatment of malignant neoplasms in the model of 2019. Farmakoekonomika. Sovremennaya Farmakoekonomika i Farmakoepidemiologiya. 2019;12(3):169-177. (In Russ.) doi: 10.17749/2070-4909.2019.12.3.169-177

15. Knyazeva VA, Mamchik NP, Gabbasova NV, Moshurov IP, Sereda AA. Epidemiological characteristics of breast cancer in the Voronezh Region in 2015–2019. Zdorov’e Naseleniya i Sreda Obitaniya. 2023;31(4):40-46. (In Russ.) doi: 10.35627/2219-5238/2023-31-4-40-46

16. Andreev DA, Zavyalov AA, Ermolaeva TN. Methodological outlines for assessing the costs of cancer patients care. Zdravookhranenie Rossiyskoy Federatsii. 2021;65(2):125-134. (In Russ.) doi: 10.47470/0044-197X-2021-65-2-125-134

17. Russkikh SV, Lindenbraten AL, Moskvicheva LI, Vasilieva TP, Smbatyan SM, Gorbacheva NA. Organizational and economic aspects of standardization of processes in the healthcare system. Zdravookhranenie Rossiyskoy Federatsii. 2023;67(5):367-373. (In Russ.) doi: 10.47470/0044-197X-2023-67-5-367-373

18. Löfgren A, Åkesson O, Johansson J, Persson J. Hospital costs and health-related quality of life from complications after esophagectomy. Eur J Surg Oncol. 2021;47(5):1042-1047. doi: 10.1016/j.ejso.2020.09.032

19. Basu P, Zhang L, Hariprasad R, Carvalho AL, Barchuk A. A pragmatic approach to tackle the rising burden of breast cancer through prevention & early detection in countries ‘in transition.’ Indian J Med Res. 2020;152(4):343-355. doi: 10.4103/ijmr.ijmr_1868_19

20. Arnold M, Morgan E, Rumgay H, et al. Current and future burden of breast cancer: Global statistics for 2020 and 2040. Breast. 2022;66:15-23. doi: 10.1016/j.breast.2022.08.010

21. Kudelina OV, Gamirova KA, Sheryazdanova DN. Optimization of cancer care costs: A systematic review of international publications. Zdorov’e Naseleniya i Sreda Obitaniya. 2025;33(4):7-18. (In Russ.) doi: 10.35627/2219-5238/2025-33-4-7-18

22. Tishkina SN, Matskevich VE, Ledovskikh YuA, Semakova EV, Omelyanovskiy VV. Regulatory framework of the on cological medical care provision. Farmakoekonomika. Sovremennaya Farmakoekonomika i Farmakoepidemiologiya. 2020;13(3):304-315. (In Russ.) doi: 10.17749/2070-4909/farmakoekonomika.2020.052

23. Omelyanovskiy VV, Avxentyeva MV, Zheleznyakova IA, et al. Main changes in the model of diagnosis-related groups in 2022. Meditsinskie Tekhnologii. Otsenka i Vybor. 2022;(2(44)):8-21. (In Russ.) doi: 10.17116/medtech2022440218

24. Murashko RA, Alekseenko SN, Koshkarov AA, Teslenko LG, Korogod MA, Rubtsova IT. Patient routing and process approach implementation for regional oncology service. Kubanskiy Nauchnyy Meditsinskiy Vestnik. 2021;28(1):84-102. (In Russ.) doi: 10.25207/1608-6228-2021-28-1-84-102

25. 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. doi: 10.34172/ijhpm.2022.6536

26. Kudelina OV, Gamirova KA, Grishenko MYu. Efficiency assessment of hospital bed capacity in a regional oncology center: A observational retrospective study. Kubanskiy Nauchnyy Meditsinskiy Vestnik. 2025;32(3):94-106. (In Russ.) doi: 10.25207/1608-6228-2025-32-3-94-106