25301 Department of Health Outcomes and Behavior, Division of Population Science, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA.
Department of Gastrointestinal Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA.
Public Health Rep. 2022 May-Jun;137(3):498-505. doi: 10.1177/00333549211005812. Epub 2021 Apr 8.
Chronic hepatitis C virus (HCV) infection is one of the main causes of hepatocellular carcinoma. Before initiating a multilevel HCV screening intervention, we sought to (1) describe concordance between the electronic health record (EHR) data warehouse and manual medical record review in recording aspects of HCV testing and treatment and (2) estimate the percentage of patients with chronic HCV infection who initiated and completed HCV treatment using manual medical record review.
We examined the medical records for 177 patients (100 randomly selected patients born during 1945-1965 without evidence of HCV testing and 77 adult patients of any birth cohort who had completed HCV testing) with a primary care or relevant specialist visit at an academic health care system in Tampa, Florida, from 2015 through 2018. We used the Cohen κ coefficient to examine the degree of concordance between the searchable data warehouse and the medical record review abstractions. Descriptive statistics characterized referral to and receipt of treatment among patients with chronic HCV infection from medical record review.
We found generally good concordance between the data warehouse abstraction and medical record review for HCV testing data (κ ranged from 0.66 to 0.87). However, the data warehouse failed to capture data on HCV treatment variables. According to medical record review, 28 patients had chronic HCV infection; 16 patients were prescribed treatment, 14 initiated treatment, and 9 achieved and had a reported posttreatment undetected HCV viral load.
Using data warehouse data provides generally reliable HCV testing information. However, without the use of natural language processing and purposeful EHR design, manual medical record reviews will likely be required to characterize treatment initiation and completion.
慢性丙型肝炎病毒（HCV）感染是肝细胞癌的主要病因之一。在启动多层次 HCV 筛查干预措施之前，我们旨在：（1）描述电子健康记录（EHR）数据仓库与手动病历审查在记录 HCV 检测和治疗方面的一致性；（2）使用手动病历审查估计接受慢性 HCV 感染治疗的患者的起始和完成 HCV 治疗的百分比。
我们对 177 名患者的病历进行了检查（100 名随机选择的 1945-1965 年出生且无 HCV 检测证据的患者和 77 名接受过 HCV 检测的任何出生队列的成年患者），这些患者在佛罗里达州坦帕市的一家学术医疗保健系统中进行了初级保健或相关专科就诊，就诊时间为 2015 年至 2018 年。我们使用 Cohen κ 系数来检查可搜索数据仓库和病历审查摘要之间的一致性程度。从病历审查中描述慢性 HCV 感染患者的转诊和接受治疗的情况。
我们发现 HCV 检测数据的数据库提取与病历审查之间具有良好的一致性（κ 值范围为 0.66 至 0.87）。但是，数据仓库无法捕获 HCV 治疗变量的数据。根据病历审查，有 28 名患者患有慢性 HCV 感染；有 16 名患者被开处治疗处方，有 14 名患者开始治疗，有 9 名患者实现并报告了治疗后未检测到 HCV 病毒载量。
使用数据仓库数据可提供一般可靠的 HCV 检测信息。但是，如果不使用自然语言处理和有针对性的 EHR 设计，则可能需要手动病历审查来描述治疗的开始和完成。
