用于管理目的的电子健康记录元数据的趋势

IF 2.6 Q2 HEALTH POLICY & SERVICES
Nuo Xu, Ishwar Badwaik, Gunwoo Lee, Eric W. Ford
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引用次数: 0

摘要

目的分析医院电子病历元数据在管理流程中的应用和集成情况。该研究比较了不同医院的EHR元数据利用率。医院自我报告的EHR元数据使用情况来自2018年至2020年的AHA-IT补充报告。本文还分析了EHR供应商对元数据的利用情况。方法采用Bass扩散模型,拟合2018 - 2020年的电子病历采用率数据,利用Excel Solver最小化预测误差,估计电子病历采用率参数。估计的内部和外部影响系数揭示了主要驱动采用的因素,而扩散模型能够预测未来的临界点和采用水平。结果对2018 - 2020年EHR元数据利用率的分析发现,将这些数据整合到医院管理实践中有明显的趋势。在对相关项目作出回应的卫生系统中,69%的卫生系统已经在使用电子病历元数据,预计到2035年,几乎所有卫生系统都将这样做。此外,元数据的使用因供应商而异。该研究强调,医院管理者的内在动机,而不是外部需求,正在推动电子病历元数据。随着具有更大内在吸引力的创新更快地传播并具有更大的持久力,EHR元数据的使用将继续增长。这些趋势表明EHR元数据在管理决策、临床质量改进和优化劳动力效率方面的重要性日益增加。结论电子病历元数据作为管理和卫生服务研究资源具有广阔的应用前景。如果EHR供应商创建统一的度量标准,这些工具的实用程序将得到增强。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Trends in electronic health record metadata use for management purposes

Objective

This study aims to analyze hospitals' adoption and integration of electronic health record (EHR) metadata into their management processes.

Design

The study compares the rates of EHR metadata utilization across various hospitals over time. Hospitals' self-reported use of EHR metadata is drawn from the AHA-IT Supplements from 2018 to 2020. An analysis of metadata utilization by EHR vendors is also provided.

Method

The study uses Bass diffusion modeling to estimate EHR adoption parameters by fitting adoption rate data from 2018 to 2020, using Excel Solver to minimize prediction errors. The estimated internal and external influence coefficients reveal which factor primarily drives adoption, while the diffusion model enables future projection of tipping point and adoption level.

Results

Analysis of EHR metadata utilization rates from 2018 to 2020 find a significant trend towards the integration of this data into hospital management practices. Among health systems responding to the items of interest, 69% of them are already using EHR metadata, and it is projected that nearly all will do so by 2035. Further, metadata use varied significantly depending on the vendor.

Discussion

The study underscores that hospital managers' intrinsic motivations, rather than external demands, are driving EHR metadata. As innovations with greater intrinsic appeal spread more rapidly and have greater staying power, EHR metadata use will continue to grow. These trends are indicative of the growing importance of EHR metadata in management decision-making, clinical quality improvement, and optimizing workforce efficiency.

Conclusions

EHR metadata holds great promise as a managerial and health service research source. The tools' utilities would be enhanced if EHR vendors created uniform metrics.

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来源期刊
Learning Health Systems
Learning Health Systems HEALTH POLICY & SERVICES-
CiteScore
5.60
自引率
22.60%
发文量
55
审稿时长
20 weeks
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