邀请患者通过对其在线就诊记录的结构化评估来确定诊断问题

Traber Davis, D. T. Choi, Divvy K. Upadhyay, Saritha Korukonda, Taylor M. T. Scott, C. Spitzmueller, C. Schuerch, Dennis Torretti, Hardeep Singh
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引用次数: 6

摘要

背景:《21世纪治愈法案》要求患者访问他们的电子健康记录(EHR)笔记。据我们所知,以前没有研究系统地邀请患者主动报告诊断问题,同时通过基于电子病历的临床医生记录审查记录和跟踪他们的诊断经历。目的通过对患者在线就诊记录的结构化评估,测试患者是否能够识别出对其诊断的担忧。方法:在一个大型综合卫生系统中,如果EHR算法检测到首次初级保健咨询后近期出现任何意外回访(“风险”回访),请在2019年10月至2020年2月期间积极使用患者门户网站的18-85岁患者回答一份在线问卷。我们开发并测试了一种仪器(Safer Dx患者仪器),以帮助患者根据病历审查和最近“风险”就诊的回忆,确定与诊断过程中几个维度相关的问题。额外的问题评估了患者对他们的提供者的信任和他们对访问的总体感受。主要结果是自我报告的诊断关注。多变量逻辑回归检验了主要结局是否由工具变量预测。结果在293 566次访问中,该算法识别出1282名符合条件的患者,其中486名患者回应。应用排除标准后,418例患者纳入分析。51名患者(12.2%)确定了诊断问题。如果患者不同意“提供者为我制定的护理计划解决了我所有的医疗问题”的说法,则他们更有可能报告担忧[优势比(OR), 2.65;95%置信区间[CI], 1.45-4.87)和“我信任我在访问期间看到的提供者”(OR, 2.10;95% CI, 1.19-3.71),并同意“我对我的访问感觉不太好”的说法(OR, 1.48;95% ci, 1.09-2.01)。结论患者可以通过对就诊记录的主动在线结构化评估来识别诊断问题。这一监测战略有可能提高诊断过程的透明度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Inviting patients to identify diagnostic concerns through structured evaluation of their online visit notes
Abstract Background The 21st Century Cures Act mandates patients’ access to their electronic health record (EHR) notes. To our knowledge, no previous work has systematically invited patients to proactively report diagnostic concerns while documenting and tracking their diagnostic experiences through EHR-based clinician note review. Objective To test if patients can identify concerns about their diagnosis through structured evaluation of their online visit notes. Methods In a large integrated health system, patients aged 18–85 years actively using the patient portal and seen between October 2019 and February 2020 were invited to respond to an online questionnaire if an EHR algorithm detected any recent unexpected return visit following an initial primary care consultation (“at-risk” visit). We developed and tested an instrument (Safer Dx Patient Instrument) to help patients identify concerns related to several dimensions of the diagnostic process based on notes review and recall of recent “at-risk” visits. Additional questions assessed patients’ trust in their providers and their general feelings about the visit. The primary outcome was a self-reported diagnostic concern. Multivariate logistic regression tested whether the primary outcome was predicted by instrument variables. Results Of 293 566 visits, the algorithm identified 1282 eligible patients, of whom 486 responded. After applying exclusion criteria, 418 patients were included in the analysis. Fifty-one patients (12.2%) identified a diagnostic concern. Patients were more likely to report a concern if they disagreed with statements “the care plan the provider developed for me addressed all my medical concerns” [odds ratio (OR), 2.65; 95% confidence interval [CI], 1.45–4.87) and “I trust the provider that I saw during my visit” (OR, 2.10; 95% CI, 1.19–3.71) and agreed with the statement “I did not have a good feeling about my visit” (OR, 1.48; 95% CI, 1.09–2.01). Conclusion Patients can identify diagnostic concerns based on a proactive online structured evaluation of visit notes. This surveillance strategy could potentially improve transparency in the diagnostic process.
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