Kosowan Leanne, Singer Alexander G, Abrams Elissa M, Kassim Sameer S, O'Neill Braden, Protudjer Jennifer L P
Manitoba Primary Care Research Network Manager in the Department of Family Medicine at the University of Manitoba in Winnipeg and Canadian Primary Care Research Network Research Manager.
Associate Professor and Director of Research and Quality Improvement in the Department of Family Medicine at the University of Manitoba and Director of the Manitoba Primary Care Research Network.
Can Fam Physician. 2025 Jul-Aug;71(7-8):e195-e204. doi: 10.46747/cfp.710708e195.
To validate a primary care electronic medical record (EMR) case definition for mood and anxiety disorders (including depression, anxiety, and bipolar disorder) and schizophrenia that can be used to estimate prevalence and co-occurrence.
Retrospective cross-sectional study.
Canada.
De-identified EMR data was used from 1574 primary care providers participating in the Canadian Primary Care Sentinel Surveillance Network (CPCSSN) from 1,692,987 patients who had 1 or more visits with a primary care provider. The reference set included 2488 patients, with 434 positive and 2054 negative for 1 or more mental health conditions of interest. A second reference set for schizophrenia represented 760 patients (30 positive and 730 negative).
The agreement of 29 case definitions was assessed against a reference set by reporting sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy. Prevalence was estimated and co-occurrence was assessed in the CPCSSN dataset (N=1,692,987).
The strongest definition for mood disorders captured anxiety, depression, and bipolar disorder with a sensitivity of 80.7%, specificity of 88.7%, PPV of 59.9%, and NPV of 95.7%; and an estimated prevalence of 21.8% (95% CI 21.7 to 21.9). The inclusion of psychosis did not improve agreement (sensitivity 95.2%, specificity 80.7%, PPV 51.0%, NPV 98.8%), but schizophrenia alone had high agreement (sensitivity 93.3%, specificity 100%, PPV 100%, NPV 99.9%).
High co-occurrence of anxiety, depression, and bipolar disorder was found. Algorithms validated to capture these conditions together produced stronger agreement compared with individual definitions. Schizophrenia was less likely to co-occur with other mental health conditions and produced higher agreement when validated separately. Application of validated algorithms to capture mental health conditions can inform disease surveillance and health system planning.
验证一种用于情绪和焦虑障碍（包括抑郁症、焦虑症和双相情感障碍）及精神分裂症的初级保健电子病历（EMR）病例定义，该定义可用于估计患病率和共病情况。
回顾性横断面研究。
加拿大。
使用了来自参与加拿大初级保健哨点监测网络（CPCSSN）的1574名初级保健提供者的去识别化EMR数据，这些数据来自1,692,987名曾就诊于初级保健提供者1次或以上的患者。参考集包括2488名患者，其中434名患有1种或以上感兴趣的心理健康状况为阳性，2054名阴性。精神分裂症的第二个参考集包括760名患者（30名阳性和730名阴性）。
通过报告敏感性、特异性、阳性预测值（PPV）、阴性预测值（NPV）和准确性，评估29种病例定义与参考集的一致性。在CPCSSN数据集（N = 1,692,987）中估计患病率并评估共病情况。
情绪障碍的最强定义涵盖焦虑症、抑郁症和双相情感障碍，敏感性为80.7%，特异性为88.7%，PPV为59.9%，NPV为95.7%；估计患病率为21.8%（95%CI 21.7至21.9）。纳入精神病并未提高一致性（敏感性95.2%，特异性80.7%，PPV 51.0%，NPV 98.8%），但仅精神分裂症具有较高的一致性（敏感性93.3%，特异性100%，PPV 100%，NPV 99.9%）。
发现焦虑症、抑郁症和双相情感障碍共病率较高。与单独的定义相比，经过验证可同时捕捉这些状况的算法产生了更强的一致性。精神分裂症与其他心理健康状况共病的可能性较小，单独验证时一致性更高。应用经过验证的算法来捕捉心理健康状况可为疾病监测和卫生系统规划提供信息。
