A Study of DRG Overspending on Hospitalization Costs for Oncology Patients Based on Degree of Structural Variation and New Gray Correlation Analysis

doi:10.19546/j.issn.1674-3830.2023.12.005

China Health Insurance ›› 2023, Vol. 0 ›› Issue (12) : 37-44. DOI: 10.19546/j.issn.1674-3830.2023.12.005

Author information +

History +

Abstract

Objective: The analysis explores the internal composition of inpatient costs and related cost changes of patients in the overspending DRG groups, providing data support for optimizing the cost structure and fine management of hospitals. Methods: The basic hospitalization cost information of the top 20% overspending cases ( a total of 14 DRGs) with malignant tumors from a tertiary oncology hospital from April to June 2022 was collected for degree of structural variation and new gray correlation analysis. Results: The three groups with the highest overspending ratios are RB21, RU11, and ES33, showing that drug costs and image and laboratory costs constituted the most important component of hospitalization costs. There were varying degrees of differences in the structural composition between the overspending cases and normal revenue cases in each DRG, and the drug cost ratios of overspending cases in RB21, XJ13, and ER15 groups increased by more than 20% compared with the normal group. The treatment cost ratio increased by 53.52% in the RC15 group. There were differences in the contribution rate of various types of costs to the structural change of the average hospitalization cost in different DRG groups. The highest degree of association between each cost and hospitalization cost was drug costs (0.790), followed by treatment costs (0.750) and consumables costs (0.736). Conclusion: It is necessary to explore the re-optimization of disease groups through clinical validation, and actively adjust the weights of different disease to further refine the composition of DRG.

Key words

malignant tumors / inpatient costs / new gray correlation analysis / degree of structural variation analysis

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations

A Study of DRG Overspending on Hospitalization Costs for Oncology Patients Based on Degree of Structural Variation and New Gray Correlation Analysis[J]. China Health Insurance. 2023, 0(12): 37-44 https://doi.org/10.19546/j.issn.1674-3830.2023.12.005

References

[1] 张钰婉,卢亚娟,谈在祥,等.DRG结付下住院费用超支原因及管控建议——基于模糊集定性比较分析法[J].卫生经济研究,2023,40(04):80-83.
[2] 葛梦妍,曾智,王璐瑶.我国公立医院医疗费用结构变动及预测研究[J].现代医院管理,2023,21(02):9-14.
[3] 司洪强,张红艳,张东峰,等.DIP付费下急性上呼吸道感染患者住院费用灰色关联分析[J].中国医疗保险,2023(09):94-99.
[4] 严敬琴,彭小冬,刘慧铭,等.基于新灰色关联与结构变动度的精神障碍患者住院费用结构分析[J].四川精神卫生,2019,32(05):437-441.
[5] 吴奕,厉胜群,徐凌云.医院卫生材料消耗分析与管控建议[J].医院管理论坛,2020,37(03):17-19.
[6] 赵威,覃双凌.基于DRG的恶性肿瘤患者住院费用新灰色关联分析[J].卫生经济研究,2022,39(04):50-52.
[7] 铁海龙,张光辉,孙菲,等.新疆某肿瘤专科医院肺恶性肿瘤患者住院费用灰色关联及结构变动度分析[J].中国病案,2021,22(09):63-66.
[8] 周传坤,刘青青,杨川,等.基于DRG的某医院患者费用分析及医用耗材成本管控策略探讨[J].中国医院管理,2021,41(02):55-58.
[9] 程希,沈爱宗.2017—2020年中国科学技术大学附属第一医院新型抗肿瘤药使用情况分析[J].中国医院用药评价与分析,2021,21(09):1109-1113.
[10] 陈群,杨晓鹏,闫园园,等.北京某三级医院2018—2021年新型抗肿瘤药使用情况分析[J].中国医药科学,2023,13(13):112-116.
[11] 曹然,汪国玉,陈美玲,等.2018—2022年中国科学院合肥肿瘤医院新型抗肿瘤药应用分析[J].现代药物与临床,2023,38(09):2342-2350.
[12] PETRONI G, BUQUE A, COUSSENS L M, et al.Targeting oncogene and non-oncogene addiction to inflame the tumour microenvironment[J].Nature reviews drug discovery, 2022,21(6):440-462.
[13] 张翠翠,让莹子,王雪莲,等.1128张免疫抑制剂处方超说明书用药情况及其不良反应风险分析[J].中国医院用药评价与分析,2019,19(06):742-744.
[14] 田云,尤海生,曹舫.两家住院患者抗肿瘤药物超说明书使用分析[J].中国药师,2019,22(06):1102-1105.
[15] 魏安华,贡雪芃,王璐,等.临床药师基于结构变动度对DRG超支病例用药合理性分析与研究[J].药物流行病学杂志,2022,31(02):93-96.
[16] 任旭,丁锦希,李佳明,等.DRG亏损病组的精细化管理研究[J].中国医疗保险,2023(06):53-59.
[17] 刘玥,赵凯,魏明丽.DRG支付下公立医院精细化成本管控的实证研究[J].卫生经济研究,2022,39(03):83-87.
[18] 严玲,王晓冬,王东川,等.基于RBRVS的绩效考核模式优化:“价值医疗”中的管理探索[J].中国普外基础与临床杂志,2021,28(12):1554-1558.
[19] 龚小宝.CT/MRI图像融合技术在鼻咽癌放疗靶区勾画中的应用价值[J].当代医学, 2021,27(36):40-42.
[20] HUANG B, YANG F, YIN M, et al.A review of multimodal medical image fusion techniques[J].Computational and mathematical methods in medicine 2020:8279342.
[21] SONG L, LI Y, DONG G, et al.Artificial intelligence-based bone-enhanced magnetic resonance image-a computed tomography/magnetic resonance image composite image modality in nasopharyngeal carcinoma radiotherapy[J].Quantitative imaging in medicine and surgery, 2021,11(12):4709-4720.
[22] KEARNEY M, COFFEY M, LEONG A.A review of image guided radiation therapy in head and neck cancer from 2009-2019 best practice recommendations for RTTs in the clinic[J].Technical innovations and patient support in radiation oncology, 2020,14:43-50.
[23] 余震,杨军.DRG病组结构变动度分析在病案监管中的应用[J].中国医疗保险, 2022(12):38-41.
[24] 胡曼,王锦毓,缪艳瑶.DRG评价方法在肿瘤专科医院应用及问题探讨[J].医院管理论坛,2021,38(01):32-34.
[25] 梁锌,李丽,尹世全.北京某肿瘤医院初治食管癌的住院费用及影响因素分析[J].中国病案,2022,23(08):51-54.
[26] 王文君,贾晓倩,周道平,等.DRG高倍率病例与正常倍率病例差异及住院费用灰色关联分析[J].中国医院,2023,27(05):55-58.