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开发一个标准化的医疗成本数据仓库。

Developing a standardized healthcare cost data warehouse.

作者信息

Visscher Sue L, Naessens James M, Yawn Barbara P, Reinalda Megan S, Anderson Stephanie S, Borah Bijan J

机构信息

Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA.

Division of Health Care Policy and Research, Mayo Clinic, 200 First St SW, Rochester, MN, 55905, USA.

出版信息

BMC Health Serv Res. 2017 Jun 12;17(1):396. doi: 10.1186/s12913-017-2327-8.

Abstract

BACKGROUND

Research addressing value in healthcare requires a measure of cost. While there are many sources and types of cost data, each has strengths and weaknesses. Many researchers appear to create study-specific cost datasets, but the explanations of their costing methodologies are not always clear, causing their results to be difficult to interpret. Our solution, described in this paper, was to use widely accepted costing methodologies to create a service-level, standardized healthcare cost data warehouse from an institutional perspective that includes all professional and hospital-billed services for our patients.

METHODS

The warehouse is based on a National Institutes of Research-funded research infrastructure containing the linked health records and medical care administrative data of two healthcare providers and their affiliated hospitals. Since all patients are identified in the data warehouse, their costs can be linked to other systems and databases, such as electronic health records, tumor registries, and disease or treatment registries.

RESULTS

We describe the two institutions' administrative source data; the reference files, which include Medicare fee schedules and cost reports; the process of creating standardized costs; and the warehouse structure. The costing algorithm can create inflation-adjusted standardized costs at the service line level for defined study cohorts on request.

CONCLUSION

The resulting standardized costs contained in the data warehouse can be used to create detailed, bottom-up analyses of professional and facility costs of procedures, medical conditions, and patient care cycles without revealing business-sensitive information. After its creation, a standardized cost data warehouse is relatively easy to maintain and can be expanded to include data from other providers. Individual investigators who may not have sufficient knowledge about administrative data do not have to try to create their own standardized costs on a project-by-project basis because our data warehouse generates standardized costs for defined cohorts upon request.

摘要

背景

针对医疗保健价值的研究需要对成本进行衡量。虽然成本数据有许多来源和类型,但每种都有其优缺点。许多研究人员似乎创建了针对特定研究的成本数据集,但其成本核算方法的解释并不总是清晰明了,导致其结果难以解读。我们在本文中描述的解决方案是使用广泛接受的成本核算方法,从机构角度创建一个服务层面的标准化医疗保健成本数据仓库,其中包括我们患者的所有专业服务和医院计费服务。

方法

该数据仓库基于美国国立卫生研究院资助的研究基础设施,包含两家医疗保健提供商及其附属医院的关联健康记录和医疗管理数据。由于所有患者都在数据仓库中被识别,他们的成本可以与其他系统和数据库相关联,如电子健康记录、肿瘤登记处以及疾病或治疗登记处。

结果

我们描述了这两家机构的行政源数据、参考文件(包括医疗保险费用表和成本报告)、创建标准化成本的过程以及数据仓库结构。成本核算算法可根据要求为定义的研究队列在服务项目层面创建经通胀调整的标准化成本。

结论

数据仓库中生成的标准化成本可用于对手术、医疗状况和患者护理周期的专业和设施成本进行详细的自下而上分析,而不会泄露商业敏感信息。创建后,标准化成本数据仓库相对易于维护,并且可以扩展以纳入其他提供商的数据。对于那些可能对行政数据没有足够了解的个体研究人员来说,不必逐个项目地尝试创建自己的标准化成本,因为我们的数据仓库可根据要求为定义的队列生成标准化成本。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6f4/5469019/e54dc7b4bb7c/12913_2017_2327_Fig1_HTML.jpg

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