Division of General Internal Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States.
Harvard Medical School, Boston, Massachusetts, United States.
Appl Clin Inform. 2024 Aug;15(4):733-742. doi: 10.1055/s-0044-1788330. Epub 2024 Sep 18.
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.
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.
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], = 0.02) and in a model using selected variables (4.02 [1.80, 9.55], < 0.01), respectively.
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.
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录入的诊断之间的一致性。
符合条件的患者在入院 24 小时内，独立或在他人协助下，使用 PDQ 评估其对诊断的理解程度和信心。从电子健康记录（EHR）中检索人口统计学数据、入院时的主要问题和国际疾病分类第 10 版（ICD-10）代码。两名医生独立评估患者报告的诊断与临床医生录入的主要问题之间的一致性，结果分为完全一致、部分一致或不一致。不一致的情况通过共识解决。采用描述性统计方法报告一致性（完全一致）和不一致（部分一致或不一致）结果组的人口统计学数据。采用多变量逻辑回归分析 PDQ 问题和预先选择的 EHR 数据作为自变量，预测不一致的情况。
共有 202 名患者中的 157 名（77.7%）完成了问卷，分别有 77 名（49.0%）、46 名（29.3%）和 34 名（21.7%）被评为完全一致、部分一致和不一致。独立审查员对预共识评分的 Cohen's kappa 值为 0.81（0.74，0.88）。在多变量分析中，调整其他 PDQ 问题后（3.43[1.30，10.39]， = 0.02）和使用选定变量的模型中（4.02[1.80，9.55]， < 0.01），患者报告的对主要问题缺乏信心和未分化症状（ICD-10“R 码”）与不一致（部分或不一致的评分）显著相关。
大约一半的患者报告的诊断与入院时临床医生录入的诊断一致。通过这种方法，入院时主要问题中输入的 ICD-10“R 码”和患者报告的缺乏信心可能预示着患者与临床医生之间的不一致。
