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会诊后表单系统:关于电子健康记录中高效数据收集的观点

The Postencounter Form System: Viewpoint on Efficient Data Collection Within Electronic Health Records.

作者信息

Held Philip, Boley Randy A, Faig Walter G, O'Toole John A, Desai Imran, Zalta Alyson K, Khan Jawad, Sims Shannon, Brennan Michael B, Van Horn Rebecca, Glover Angela C, Hota Bala N, Patty Brian D, Rab S Shafiq, Pollack Mark H, Karnik Niranjan S

机构信息

Department of Psychiatry and Behavioral Sciences, Rush University Medical Center, Chicago, IL, United States.

Research Institute, Children's Hospital of Philadelphia, Philadelphia, PA, United States.

出版信息

JMIR Form Res. 2020 Apr 6;4(4):e17429. doi: 10.2196/17429.

DOI:10.2196/17429
PMID:32250276
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7171586/
Abstract

Electronic health records (EHRs) offer opportunities for research and improvements in patient care. However, challenges exist in using data from EHRs due to the volume of information existing within clinical notes, which can be labor intensive and costly to transform into usable data with existing strategies. This case report details the collaborative development and implementation of the postencounter form (PEF) system into the EHR at the Road Home Program at Rush University Medical Center in Chicago, IL to address these concerns with limited burden to clinical workflows. The PEF system proved to be an effective tool with over 98% of all clinical encounters including a completed PEF within 5 months of implementation. In addition, the system has generated over 325,188 unique, readily-accessible data points in under 4 years of use. The PEF system has since been deployed to other settings demonstrating that the system may have broader clinical utility.

摘要

电子健康记录(EHRs)为研究和改善患者护理提供了机会。然而,由于临床记录中存在大量信息,使用电子健康记录中的数据存在挑战,采用现有策略将这些信息转化为可用数据可能会耗费大量人力且成本高昂。本病例报告详细介绍了在伊利诺伊州芝加哥拉什大学医学中心“回家之路”项目中,将会诊后表格(PEF)系统协同开发并应用于电子健康记录的过程,以解决这些问题,同时尽量减少对临床工作流程的负担。PEF系统被证明是一种有效的工具,在实施后的5个月内,超过98%的临床会诊都包含一份已完成的PEF。此外,该系统在使用不到4年的时间里生成了超过325,188个独特的、易于获取的数据点。此后,PEF系统已被部署到其他机构,表明该系统可能具有更广泛的临床实用性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc9a/7171586/1219a7e7a355/formative_v4i4e17429_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc9a/7171586/7d07e65c0356/formative_v4i4e17429_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc9a/7171586/1219a7e7a355/formative_v4i4e17429_fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc9a/7171586/7d07e65c0356/formative_v4i4e17429_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc9a/7171586/1219a7e7a355/formative_v4i4e17429_fig2.jpg

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本文引用的文献

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Predictive analytics in health care: how can we know it works?医疗保健中的预测分析:我们如何知道它是否有效?
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