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使用新型医疗保健软件技术的放射肿瘤学替代支付模式提案的自动化大数据分析

Automated Big Data Analytics for the Radiation Oncology Alternative Payment Model Proposal Using a Novel Health Care Software Technology.

作者信息

Thaker Nikhil G, Holloway Joshua, Hodapp Chas, Mellen Michael, Fryefield David, Meghani Rehman, Tong Kathryn, Rose Christopher M

机构信息

Arizona Oncology, The US Oncology Network, and Bayta Systems, Tucson, AZ.

The US Oncology Network, and McKesson Corporation, The Woodlands, TX.

出版信息

JCO Oncol Pract. 2020 Apr;16(4):e333-e340. doi: 10.1200/JOP.19.00692. Epub 2020 Mar 10.

Abstract

INTRODUCTION

The proposed Radiation Oncology Alternative Payment Model (RO-APM) aims to test prospective episode-based payments for radiotherapy episodes. Practices will need a tool that can calculate historical episode reimbursements to succeed in this new model. An automated software-based technology was created to calculate historical episode reimbursements within a large Network of community oncology practices.

MATERIALS AND METHODS

Claims data between January 1, 2017, and July 31, 2019, were cleaned, organized into episodes, and analyzed with a series of Python computer programs per proposed RO-APM methodology. Averaged Winsorized historical episode reimbursements were first calculated over the entire Network, then over 24 of the largest Practices, and then rerun after application of Clinical Rules to remove misattributed episodes.

RESULTS

A total of 79,418 RO-APM-defined episodes were generated from 6,512,375 claims lines. A total of 7,086 episodes (8.9%) were removed because of no treatment delivery code within 28 days of treatment planning. The Network of practices had more bone metastases, and breast, cervical, and uterine cancers but less lung and prostate cancer than the RO-APM dataset. Combination-modality episodes were more costly and required more providers than single-modality episodes. Clinical Rules reattributed 2,495 episodes (3.4%) and increased episode reimbursement by +5.8% over all disease sites (+3.7% using volume weighting; = .001).

CONCLUSION

As payment models continue to shift from volume to value, practices will need an automated analytics technology to measure historical costs and prepare for operational and financial transformation. This automated approach can be adapted to future versions of the RO-APM. Our analysis suggests that future iterations of the RO-APM could incorporate Clinical Rules to remove misattributed palliative care episodes and could implement a separate payment for episodes with multiple radiation therapy modalities.

摘要

引言

拟议的放射肿瘤学替代支付模式(RO - APM)旨在测试针对放射治疗疗程的前瞻性基于疗程的支付方式。医疗机构需要一种能够计算历史疗程报销金额的工具,以便在这种新模式中取得成功。为此创建了一种基于软件的自动化技术,用于在大型社区肿瘤医疗网络中计算历史疗程报销金额。

材料与方法

根据拟议的RO - APM方法,对2017年1月1日至2019年7月31日期间的理赔数据进行清理、整理成疗程,并使用一系列Python计算机程序进行分析。首先计算整个网络的平均缩尾历史疗程报销金额,然后计算24家最大医疗机构的报销金额,之后在应用临床规则以去除归因错误的疗程后重新运行计算。

结果

从6,512,375条理赔记录中总共生成了79,418个RO - APM定义的疗程。由于在治疗计划后28天内没有治疗实施代码,总共7,086个疗程(8.9%)被剔除。与RO - APM数据集相比,该医疗网络中的骨转移瘤、乳腺癌、宫颈癌和子宫癌更多,但肺癌和前列腺癌更少。联合治疗模式的疗程比单一治疗模式的疗程成本更高,且需要更多的医疗服务提供者。临床规则重新归因了2,495个疗程(3.4%),并使所有疾病部位的疗程报销金额增加了5.8%(使用量加权为3.7%;P = 0.001)。

结论

随着支付模式继续从按数量转向按价值,医疗机构将需要自动化分析技术来衡量历史成本,并为运营和财务转型做好准备。这种自动化方法可适用于RO - APM的未来版本。我们的分析表明,RO - APM的未来迭代版本可以纳入临床规则以去除归因错误的姑息治疗疗程,并可以对采用多种放射治疗模式的疗程实施单独支付。

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