入院时患者与医生诊断的一致性

IF 2.1 2区 医学 Q4 MEDICAL INFORMATICS
Alyssa Lam, Savanna Plombon, Alison Garber, Pamela Garabedian, Ronen Rozenblum, Jacqueline A. Griffin, Jeffrey L. Schnipper, Stuart R. Lipsitz, David W. Bates, Anuj K. Dalal
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引用次数: 0

摘要

目的 本研究旨在试用基于应用程序的患者诊断问卷(PDQ),并评估患者报告的入院诊断与临床医生输入的诊断是否一致。方法 符合条件的患者在住院 24 小时后独立或在他人协助下完成 PDQ,评估患者对诊断的理解和信心。从电子病历(EHR)中检索人口统计学数据、入院时的主要问题以及国际疾病分类第十版(ICD-10)代码。由两名医生独立将患者报告的诊断与临床医生输入的主要问题之间的一致性分为完全一致、部分一致或不一致。不一致之处通过协商一致的方式解决。描述性统计用于报告结果一致组(完全一致)和不一致组(部分一致或不一致)的人口统计学特征。将 PDQ 问题和事先选定的 EHR 数据作为自变量进行多变量逻辑回归,以预测不一致情况。结果 202 名参与者共完成了 157 份(77.7%)问卷;77 份(49.0%)、46 份(29.3%)和 34 份(21.7%)分别被评为完全一致、部分一致和不一致。独立审稿人对预共识评级的一致性科恩卡帕为 0.81(0.74,0.88)。在多变量分析中,在调整其他 PDQ 问题后(3.43 [1.30, 10.39],p = 0.02)以及在使用选定变量的模型中(4.02 [1.80, 9.55],p 结论:约有二分之一的患者报告的诊断与临床医生在入院时输入的诊断一致。作为主要问题输入的 ICD-10 "R 代码 "和患者报告的缺乏信心可能会通过这种方法预测住院早期患者与临床医生的诊断不一致。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Patient–Clinician Diagnostic Concordance upon Hospital Admission

Objectives This study aimed to pilot an application-based patient diagnostic questionnaire (PDQ) and assess the concordance of the admission diagnosis reported by the patient and entered by the clinician.

Methods Eligible patients completed the PDQ assessing patients' understanding of and confidence in the diagnosis 24 hours into hospitalization either independently or with assistance. Demographic data, the hospital principal problem upon admission, and International Classification of Diseases 10th Revision (ICD-10) codes were retrieved from the electronic health record (EHR). Two physicians independently rated concordance between patient-reported diagnosis and clinician-entered principal problem as full, partial, or no. Discrepancies were resolved by consensus. Descriptive statistics were used to report demographics for concordant (full) and nonconcordant (partial or no) outcome groups. Multivariable logistic regressions of PDQ questions and a priori selected EHR data as independent variables were conducted to predict nonconcordance.

Results A total of 157 (77.7%) questionnaires were completed by 202 participants; 77 (49.0%), 46 (29.3%), and 34 (21.7%) were rated fully concordant, partially concordant, and not concordant, respectively. Cohen's kappa for agreement on preconsensus ratings by independent reviewers was 0.81 (0.74, 0.88). In multivariable analyses, patient-reported lack of confidence and undifferentiated symptoms (ICD-10 “R-code”) for the principal problem were significantly associated with nonconcordance (partial or no concordance ratings) after adjusting for other PDQ questions (3.43 [1.30, 10.39], p = 0.02) and in a model using selected variables (4.02 [1.80, 9.55], p < 0.01), respectively.

Conclusion About one-half of patient-reported diagnoses were concordant with the clinician-entered diagnosis on admission. An ICD-10 “R-code” entered as the principal problem and patient-reported lack of confidence may predict patient–clinician nonconcordance early during hospitalization via this approach.

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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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