L. Eder, MD, PhD, Assistant Professor of Medicine, University of Toronto, and Women's College Research Institute, Women's College Hospital, Toronto;
J. Widdifield, PhD, Assistant Professor, University of Toronto, Institute of Health Policy, Management and Evaluation, and Sunnybrook Research Institute, Institute for Clinical Evaluative Sciences, Toronto.
J Rheumatol. 2020 Nov 1;47(11):1644-1651. doi: 10.3899/jrheum.190659. Epub 2020 Feb 15.
We assessed the accuracy of case definition algorithms for psoriasis and psoriatic arthritis (PsA) in health administrative data and used primary care electronic medical records (EMR) to describe disease and treatment characteristics of these patients.
We randomly sampled 30,424 adult Ontario residents from the Electronic Medical Record Primary Care database and identified 2215 patients with any possible psoriatic disease-related terms in their EMR. The relevant patient records were chart abstracted to confirm diagnoses of psoriasis or PsA. This validation set was then linked to health administrative data to assess the performance of different algorithms for physician billing diagnosis codes, hospitalization diagnosis codes, and medications for psoriatic disease. We report the performance of selected case definition algorithms and describe the disease characteristics of the validation set.
Our reference standard identified 1028 patients with psoriasis and 77 patients with PsA, for an overall prevalence of 3.4% for psoriasis and 0.3% for PsA. Most patients with PsA (66%) had a rheumatology-confirmed diagnosis, while only 30% of the patients with psoriasis had dermatology-confirmed diagnosis. The use of systemic medications was much more common with PsA than with psoriasis. All algorithms had excellent specificity (97-100%). The sensitivity and positive predictive value were moderate and varied between different algorithms (34-72%).
The accuracy of case definition algorithms for psoriasis and PsA varies widely. However, selected algorithms produced population prevalence estimates that were within the expected ranges, suggesting that they may be useful for future research purposes.
我们评估了健康管理数据中银屑病和银屑病关节炎（PsA）病例定义算法的准确性，并使用初级保健电子病历（EMR）描述这些患者的疾病和治疗特征。
我们从电子病历初级保健数据库中随机抽取了 30424 名成年安大略省居民，并在他们的 EMR 中发现了 2215 名患有任何可能与银屑病相关疾病的患者。相关的患者记录被摘录以确认银屑病或 PsA 的诊断。这个验证集随后与健康管理数据相关联，以评估用于医师计费诊断代码、住院诊断代码和治疗银屑病药物的不同算法的性能。我们报告了选定病例定义算法的性能，并描述了验证集的疾病特征。
我们的参考标准确定了 1028 名银屑病患者和 77 名 PsA 患者，银屑病的总体患病率为 3.4%，PsA 的患病率为 0.3%。大多数 PsA 患者（66%）有风湿病学确认的诊断，而只有 30%的银屑病患者有皮肤科确认的诊断。与银屑病相比，PsA 更常使用系统药物。所有算法的特异性均很高（97-100%）。敏感性和阳性预测值适中，在不同算法之间有所不同（34-72%）。
银屑病和 PsA 的病例定义算法的准确性差异很大。然而，选定的算法产生了在预期范围内的人群患病率估计，这表明它们可能对未来的研究目的有用。
