Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States of America.
Division of General Internal Medicine and Primary Care, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States of America.
PLoS One. 2023 Apr 13;18(4):e0283775. doi: 10.1371/journal.pone.0283775. eCollection 2023.
To evaluate methods of identifying patients with systemic sclerosis (SSc) using International Classification of Diseases, Tenth Revision (ICD-10) codes (M34*), electronic health record (EHR) databases and organ involvement keywords, that result in a validated cohort comprised of true cases with high disease burden.
We retrospectively studied patients in a healthcare system likely to have SSc. Using structured EHR data from January 2016 to June 2021, we identified 955 adult patients with M34* documented 2 or more times during the study period. A random subset of 100 patients was selected to validate the ICD-10 code for its positive predictive value (PPV). The dataset was then divided into a training and validation sets for unstructured text processing (UTP) search algorithms, two of which were created using keywords for Raynaud's syndrome, and esophageal involvement/symptoms.
Among 955 patients, the average age was 60. Most patients (84%) were female; 75% of patients were White, and 5.2% were Black. There were approximately 175 patients per year with the code newly documented, overall 24% had an ICD-10 code for esophageal disease, and 13.4% for pulmonary hypertension. The baseline PPV was 78%, which improved to 84% with UTP, identifying 788 patients likely to have SSc. After the ICD-10 code was placed, 63% of patients had a rheumatology office visit. Patients identified by the UTP search algorithm were more likely to have increased healthcare utilization (ICD-10 codes 4 or more times 84.1% vs 61.7%, p < .001), organ involvement (pulmonary hypertension 12.7% vs 6% p = .011) and medication use (mycophenolate use 28.7% vs 11.4%, p < .001) than those identified by the ICD codes alone.
EHRs can be used to identify patients with SSc. Using unstructured text processing keyword searches for SSc clinical manifestations improved the PPV of ICD-10 codes alone and identified a group of patients most likely to have SSc and increased healthcare needs.
评估使用国际疾病分类第 10 版（ICD-10）代码（M34*）、电子健康记录（EHR）数据库和器官受累关键词识别系统性硬化症（SSc）患者的方法，这些方法可产生包含高疾病负担的真实病例的验证队列。
我们回顾性研究了医疗系统中可能患有 SSc 的患者。使用 2016 年 1 月至 2021 年 6 月期间的结构化 EHR 数据，我们确定了 955 名有 2 次或以上 M34*记录的成年患者。随机选择了 100 名患者的子集来验证 ICD-10 代码的阳性预测值（PPV）。然后，将数据集分为训练集和验证集，用于非结构化文本处理（UTP）搜索算法，其中两个算法使用雷诺氏综合征和食管受累/症状的关键词创建。
在 955 名患者中，平均年龄为 60 岁。大多数患者（84%）为女性；75%的患者为白人，5.2%为黑人。每年约有 175 名患者新记录该代码，总体而言，24%的患者有 ICD-10 食管疾病代码，13.4%有肺动脉高压代码。基线 PPV 为 78%，使用 UTP 后提高到 84%，确定了 788 名可能患有 SSc 的患者。ICD-10 代码放置后，63%的患者接受了风湿病就诊。通过 UTP 搜索算法识别的患者更有可能增加医疗保健利用率（ICD-10 代码 4 次或以上的患者占 84.1%，而 61.7%，p<.001）、器官受累（肺动脉高压患者占 12.7%，而 6%，p=.011）和药物使用（吗替麦考酚酯使用率 28.7%，而 11.4%，p<.001）高于仅通过 ICD 代码识别的患者。
EHR 可用于识别 SSc 患者。使用 SSc 临床表现的非结构化文本处理关键字搜索提高了 ICD-10 代码的单独 PPV，并确定了一组最有可能患有 SSc 和增加医疗需求的患者。
