Suppr超能文献

计算机自适应患者报告结局无缝整合至电子健康记录中。

Seamless Integration of Computer-Adaptive Patient Reported Outcomes into an Electronic Health Record.

机构信息

Department of Medical Social Sciences, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, United States.

Department of Preventative Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, United States.

出版信息

Appl Clin Inform. 2024 Jan;15(1):145-154. doi: 10.1055/a-2235-9557. Epub 2023 Dec 28.

Abstract

BACKGROUND

Patient-reported outcome (PRO) measures have become an essential component of quality measurement, quality improvement, and capturing the voice of the patient in clinical care. In 2004, the National Institutes of Health endorsed the importance of PROs by initiating the Patient-Reported Outcomes Measurement Information System (PROMIS), which leverages computer-adaptive tests (CATs) to reduce patient burden while maintaining measurement precision. Historically, PROMIS CATs have been used in a large number of research studies outside the electronic health record (EHR), but growing demand for clinical use of PROs requires creative information technology solutions for integration into the EHR.

OBJECTIVES

This paper describes the introduction of PROMIS CATs into the Epic Systems EHR at a large academic medical center using a tight integration; we describe the process of creating a secure, automatic connection between the application programming interface (API) which scores and selects CAT items and Epic.

METHODS

The overarching strategy was to make CATs appear indistinguishable from conventional measures to clinical users, patients, and the EHR software itself. We implemented CATs in Epic without compromising patient data security by creating custom middleware software within the organization's existing middleware framework. This software communicated between the Assessment Center API for item selection and scoring and Epic for item presentation and results. The middleware software seamlessly administered CATs alongside fixed-length, conventional PROs while maintaining the display characteristics and functions of other Epic measures, including automatic display of PROMIS scores in the patient's chart. Pilot implementation revealed differing workflows for clinicians using the software.

RESULTS

The middleware software was adopted in 27 clinics across the hospital system. In the first 2 years of hospital-wide implementation, 793 providers collected 70,446 PROs from patients using this system.

CONCLUSION

This project demonstrated the importance of regular communication across interdisciplinary teams in the design and development of clinical software. It also demonstrated that implementation relies on buy-in from clinical partners as they integrate new tools into their existing clinical workflow.

摘要

背景

患者报告的结果(PRO)测量已成为质量测量、质量改进以及在临床护理中倾听患者意见的重要组成部分。2004 年,美国国立卫生研究院通过启动患者报告结局测量信息系统(PROMIS),认可了 PRO 的重要性,该系统利用计算机自适应测试(CAT)来减轻患者负担,同时保持测量精度。从历史上看,PROMIS CAT 已在电子健康记录(EHR)之外的大量研究中使用,但对 PRO 临床应用的需求不断增长,需要创造性的信息技术解决方案将其整合到 EHR 中。

目的

本文描述了在一家大型学术医疗中心,通过紧密集成将 PROMIS CAT 引入 Epic 系统电子健康记录的情况;我们描述了创建应用程序编程接口(API)和 Epic 之间安全、自动连接的过程,该 API 用于评分和选择 CAT 项目。

方法

总体策略是使 CAT 对临床用户、患者和 EHR 软件本身来说与常规测量方法无异。我们通过在组织现有的中间件框架内创建自定义中间件软件,在不损害患者数据安全性的情况下在 Epic 中实现 CAT。该软件在评估中心 API 用于项目选择和评分以及 Epic 用于项目呈现和结果之间进行通信。中间件软件在与常规 PRO 一起管理 CAT 的同时,保持了其他 Epic 措施的显示特征和功能,包括在患者图表中自动显示 PROMIS 分数。试点实施揭示了使用该软件的临床医生的不同工作流程。

结果

该中间件软件在医院系统的 27 个诊所中得到采用。在全院实施的头 2 年中,793 名提供者使用该系统从患者处收集了 70446 份 PRO。

结论

该项目表明了在设计和开发临床软件时跨学科团队之间定期沟通的重要性。它还表明,实施依赖于临床合作伙伴的认可,因为他们将新工具整合到现有的临床工作流程中。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40bf/10881259/319dcd496aff/10-1055-a-2235-9557-i202308cr0178-1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验