当前位置: X-MOL 学术Journal of Traumatic Stress › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Using electronic medical record diagnostic codes to identify veterans with posttraumatic stress disorder
Journal of Traumatic Stress ( IF 3.952 ) Pub Date : 2022-05-05 , DOI: 10.1002/jts.22844
Samantha J Moshier 1 , Kelly Harper 2 , Terence M Keane 2, 3 , Brian P Marx 2, 3
Affiliation  

Researchers studying posttraumatic stress disorder (PTSD) often use diagnostic codes within electronic medical records (EMRs) to identify individuals with the disorder. This study evaluated the performance of algorithms for defining PTSD based on International Classification of Diseases (ICD) code use within EMR data. We used data from a registry of U.S. veterans for whom both structured interview data and Veterans Health Administration EMR data were available. Using interview-diagnosed PTSD as the reference criterion, we calculated diagnostic accuracy statistics for algorithms that required the presence of at least one and up to seven encounters in which a PTSD diagnosis was present in EMR data within any clinical source, mental health clinic, or specialty PTSD clinic. We evaluated algorithm accuracy in the total sample (N = 1,343; 64.1% with PTSD), within a subsample constrained to lower PTSD prevalence (n = 712; 32.3% with PTSD), and as a function of demographic characteristics. Algorithm accuracy was influenced by PTSD prevalence. Results indicated that higher thresholds for the operationalization of PTSD may be justified among samples in which PTSD prevalence is lower. Requiring three PTSD diagnoses from a mental health clinic or four diagnoses from any clinical source may be a suitable minimum standard for identifying individuals with PTSD in EMRs; however, accuracy may be optimized by requiring additional diagnoses. The performance of many algorithms differed as a function of educational attainment and age, suggesting that samples of individuals with PTSD developed based on EMR ICD codes may skew toward including older, less-educated veterans.

中文翻译:

使用电子病历诊断代码识别患有创伤后应激障碍的退伍军人

研究创伤后应激障碍 (PTSD) 的研究人员经常使用电子病历 (EMR) 中的诊断代码来识别患有这种疾病的个体。本研究评估了基于国际疾病分类( ICD ) 定义 PTSD 的算法的性能) 代码在 EMR 数据中的使用。我们使用了来自美国退伍军人登记处的数据,他们可以获得结构化访谈数据和退伍军人健康管理局 EMR 数据。使用访谈诊断的 PTSD 作为参考标准,我们计算了算法的诊断准确性统计数据,这些算法需要在任何临床来源、心理健康诊所或专业 PTSD 诊所。我们评估了总样本中的算法准确性(N = 1,343;64.1% 患有 PTSD),在受限于较低 PTSD 患病率的子样本中(n= 712; 32.3% 患有 PTSD),并作为人口特征的函数。算法的准确性受 PTSD 患病率的影响。结果表明,在 PTSD 患病率较低的样本中,PTSD 操作化的较高阈值可能是合理的。要求来自心理健康诊所的三项 PTSD 诊断或来自任何临床来源的四项诊断可能是在 EMR 中识别患有 PTSD 的个体的合适的最低标准;但是,可以通过要求额外的诊断来优化准确性。许多算法的性能因教育程度和年龄而异,这表明基于 EMR ICD代码开发的 PTSD 个体样本可能偏向于包括年龄较大、受教育程度较低的退伍军人。
更新日期:2022-05-05
down
wechat
bug