专题倦怠:基于机器学习的初级保健医生倦怠预测因子的定性验证:一项探索性研究。

IF 2.2 2区 医学 Q4 MEDICAL INFORMATICS
Applied Clinical Informatics Pub Date : 2025-08-01 Epub Date: 2025-04-28 DOI:10.1055/a-2595-0415
Daniel Tawfik, Stefanie S Sebok-Syer, Cassandra Bragdon, Cati Brown-Johnson, Marcy Winget, Mohsen Bayati, Tait Shanafelt, Jochen Profit
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引用次数: 0

摘要

背景:电子健康记录(EHR)使用测量可以量化医生的活动规模,并预测医生职业倦怠高风险的实践环境,但它们与经验的关系尚不清楚。目的:探讨与电子病历相关的经验和初级保健医生的幸福感,并将其与通过机器学习模型预测职业倦怠的重要电子病历使用指标进行比较。方法:探索性质的研究与半结构化访谈初级保健医生和临床管理人员从一个大型学术卫生系统及其社区医生合作伙伴。我们纳入了相对于卫生系统中所有初级保健诊所而言,在2020年至2022年期间,倦怠得分高、倦怠得分低或倦怠得分变化大的初级保健诊所。我们使用与机器学习模型类别相关的先验主题对访谈回答进行归纳和演绎编码,这些类别包括患者负荷、文档负担、消息负担、订单以及医生的痛苦和履行。结果:通过对16名医生和4名诊所管理人员的访谈,确定了与3个主要主题相关的负担:1)信息和文件负担高,需要的时间超过大多数医生在标准工作时间内的可用时间;2)虽然与ehr相关的负担很高,但它们也提供了患者护理福利;3)人员流动和人员配备不足加剧了与患者负荷相关的时间需求。难以量化的维度,比如工作需求和个人资源之间的感知不平衡,也会导致倦怠,并且在所有主题中都是一致的。结论和相关性:电子病历相关的工作负担,很大程度上可以通过电子病历使用措施量化,是初级保健医生痛苦的主要来源。组织对这项工作的认可以及预测相关工作负担的人员配备和支持可能会增加初级保健医生的专业满足感并减少职业倦怠。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Qualitative Verification of Machine Learning-Based Burnout Predictors in Primary Care Physicians: An Exploratory Study.

Electronic health record (EHR) usage measures may quantify physician activity at scale and predict practice settings with a high risk for physician burnout, but their relation to experiences is poorly understood.This study aimed to explore the EHR-related experiences and well-being of primary care physicians in comparison to EHR usage measures identified as important for predicting burnout from a machine learning model.Exploratory qualitative study with semi-structured interviews of primary care physicians and clinic managers from a large academic health system and its community physician partners. We included primary care clinics with high burnout scores, low burnout scores, or large changes in burnout scores between 2020 and 2022, relative to all primary care clinics in the health system. We conducted inductive and deductive coding of interview responses using a priori themes related to the machine learning model categories of patient load, documentation burden, messaging burden, orders, and physician distress and fulfillment.Interviews with 16 physicians and 4 clinic managers identified burdens related to three dominant themes: (1) messaging and documentation burdens are high and require more time than most physicians have available during standard working hours. (2) While EHR-related burdens are high they also provide patient-care benefits. (3) Turnover and insufficient staffing exacerbate time demands associated with patient load. Dimensions that are difficult to quantify, such as a perceived imbalance between job demands and individual resources, also contribute to burnout and were consistent across all themes.EHR-related work burden, largely quantifiable through EHR usage measures, are major source of distress among primary care physicians. Organizational recognition of this work as well as staffing and support to predict associated work burden may increase professional fulfillment and reduce burnout among primary care physicians.

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来源期刊
Applied Clinical Informatics
Applied Clinical Informatics MEDICAL INFORMATICS-
CiteScore
4.60
自引率
24.10%
发文量
132
期刊介绍: ACI is the third Schattauer journal dealing with biomedical and health informatics. It perfectly complements our other journals Öffnet internen Link im aktuellen FensterMethods of Information in Medicine and the Öffnet internen Link im aktuellen FensterYearbook of Medical Informatics. The Yearbook of Medical Informatics being the “Milestone” or state-of-the-art journal and Methods of Information in Medicine being the “Science and Research” journal of IMIA, ACI intends to be the “Practical” journal of IMIA.
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