分析患者提供的回复,改进健康公平数据元素的收集。

AMIA ... Annual Symposium proceedings. AMIA Symposium Pub Date : 2024-01-11 eCollection Date: 2023-01-01
Jennifer Prey Dawson, Heather Finn, Aliasgar Z Chittalia, David K Vawdrey
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引用次数: 0

摘要

自我报告据称是收集人口统计信息的黄金标准。除结构化回答外,许多输入表格还包括自由文本 "写入 "选项。如果要使数据有助于衡量和减少健康差异,在自由文本的灵活性与结构化格式的数据收集价值之间取得平衡是一项挑战。虽然在改进种族和民族信息收集方面已经做了很多工作,但如何更好地收集与性少数群体、性别少数群体身份和退伍军人身份相关的数据却鲜有研究。我们分析了通过患者门户网站收集到的 3,381 条患者提供的有关性别认同、性取向、代词和退伍军人经历的自由文本回复。我们找出了常见的回答,以便更好地了解患者群体,帮助改进未来的数据收集工具迭代。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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Analyzing Patient-Provided Responses to Improve Collection of Health Equity Data Elements.

Self-report is purported to be the gold standard for collecting demographic information. Many entry forms include a free-text "write-in" option in addition to structured responses. Balancing the flexibility of free-text with the value of collecting data in a structured format is a challenge if the data are to be useful for measuring and mitigating health disparities. While much work has been done to improve collection of race and ethnicity information, how to best collect data related to sexual and gender minority status and military veteran status has been less commonly studied. We analyzed 3,381 patient-provided free-text responses collected via a patient portal for gender identity, sexual orientation, pronouns, and veteran experiences. We identified common responses to better understand our patient population and help improve future iterations of data collection tools.

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