Department of Health Sciences, The University of York, Seebohm Rowntree Building, Heslington, York, YO10 5DD, UK.
Soc Psychiatry Psychiatr Epidemiol. 2019 Oct;54(10):1161-1175. doi: 10.1007/s00127-019-01744-4. Epub 2019 Jul 12.
Case-finding for common mental disorders (CMD) in routine data unobtrusively identifies patients for mental health research. There is absence of a review of studies examining CMD-case-finding accuracy in routine primary care data. CMD-case definitions include diagnostic/prescription codes, signs/symptoms, and free text within electronic health records. This systematic review assesses evidence for case-finding accuracy of CMD-case definitions compared to reference standards.
PRISMA-DTA checklist guided review. Eligibility criteria were outlined prior to study search; studies compared CMD-case definitions in routine primary care data to diagnostic interviews, screening instruments, or clinician judgement. Studies were quality assessed using QUADAS-2.
Fourteen studies were included, and most were at high risk of bias. Nine studies examined depressive disorders and seven utilised diagnostic interviews as reference standards. Receiver operating characteristic (ROC) planes illustrated overall variable case-finding accuracy across case definitions, quantified by Youden's index. Forest plots demonstrated most case definitions provide high specificity.
Case definitions effectively identify cases in a population with good accuracy and few false positives. For 100 anxiety cases, identified using diagnostic codes, between 12 and 20 will be false positives; 0-47 cases will be missed. Sensitivity is more variable and specificity is higher in depressive cases; for 100 cases identified using diagnostic codes, between 0 and 87 will be false positives; 4-18 cases will be missed. Incorporating context to case definitions may improve overall case-finding accuracy. Further research is required for meta-analysis and robust conclusions.
在常规数据中进行常见精神障碍（CMD）的病例发现，可以在不引人注目的情况下为心理健康研究识别患者。目前缺乏对在常规初级保健数据中检查 CMD 病例发现准确性的研究进行综述。CMD 病例定义包括诊断/处方代码、体征/症状以及电子健康记录中的自由文本。本系统评价评估了与参考标准相比，CMD 病例定义的病例发现准确性的证据。
PRISMA-DTA 检查表指导的综述。在进行研究搜索之前，制定了资格标准；研究将常规初级保健数据中的 CMD 病例定义与诊断访谈、筛查工具或临床医生判断进行了比较。使用 QUADAS-2 对研究进行了质量评估。
共纳入 14 项研究，大多数研究存在高偏倚风险。9 项研究检查了抑郁障碍，7 项研究使用了诊断访谈作为参考标准。接收器操作特征（ROC）平面说明了整个病例定义的病例发现准确性各不相同，由 Youden 指数进行量化。森林图表明，大多数病例定义提供了较高的特异性。
病例定义可以有效地识别出具有良好准确性和较少假阳性的人群中的病例。对于使用诊断代码识别的 100 个焦虑病例，将有 12 到 20 个是假阳性；47 个以下是漏诊病例。在抑郁病例中，敏感性更为多变，特异性更高；对于使用诊断代码识别的 100 个病例，将有 0 到 87 个是假阳性；4 到 18 个是漏诊病例。将上下文纳入病例定义可能会提高整体病例发现准确性。需要进一步研究进行荟萃分析和得出可靠的结论。
