Department of General Practice, Erasmus MC University Medical Center, Rotterdam, the Netherlands.
Department of General Practice, Erasmus MC University Medical Center, Rotterdam, the Netherlands.
Osteoarthritis Cartilage. 2022 Jun;30(6):843-851. doi: 10.1016/j.joca.2022.03.001. Epub 2022 Mar 18.
To determine the incidence and prevalence of hip osteoarthritis (OA) in electronic health records (EHRs) of Dutch general practices by using narrative and codified data.
A retrospective cohort study was conducted using the Integrated Primary Care Information database. An algorithm was developed to identify patients with narratively diagnosed hip OA in addition to patients with codified hip OA. Incidence and prevalence estimates among people aged ≥30 were assessed from 2008 to 2019. The association of comorbidities with codified hip OA diagnosis was analysed using multivariable logistic regression.
Using the hip OA narrative data algorithm (positive predicted value = 72%) in addition to codified hip OA showed a prevalence of 1.76-1.95 times higher and increased from 4.03% in 2008 to 7.34% in 2019. The incidence was 1.83-2.41 times higher and increased from 6.83 to 7.78 per 1000 person-years from 2008 to 2019. Among codified hip OA patients, 39.4% had a previous record of narratively diagnosed hip OA, on average approximately 1.93 years earlier. Hip OA patients with a previous record of spinal OA, knee OA, hypertension, and hyperlipidaemia were more likely to be recorded with a hip OA code.
This study using Dutch EHRs showed that epidemiological estimates of hip OA are likely to be an underestimation. Using our algorithm, narrative data can be added to codified data for more realistic epidemiological estimates based on routine healthcare data. However, developing a valid algorithm remains a challenge, possibly due to the diagnostic complexity of hip pain in general practice.
利用荷兰普通诊所的电子健康记录（EHR）中的叙述性和编码数据，确定髋关节骨关节炎（OA）的发病率和患病率。
本研究采用回顾性队列研究，使用综合初级保健信息数据库。此外，我们还开发了一种算法，以识别出经叙述诊断患有髋关节 OA 的患者以及编码诊断为髋关节 OA 的患者。我们评估了 2008 年至 2019 年期间年龄≥30 岁人群的发病率和患病率。使用多变量逻辑回归分析了合并症与编码髋关节 OA 诊断之间的关系。
在使用髋关节 OA 叙述性数据算法（阳性预测值为 72%）的基础上，加上编码髋关节 OA，其患病率增加了 1.76-1.95 倍，从 2008 年的 4.03%增加到 2019 年的 7.34%。发病率增加了 1.83-2.41 倍，从 2008 年的每 1000 人年 6.83 例增加到 2019 年的 7.78 例。在编码髋关节 OA 患者中，39.4%有既往经叙述诊断为髋关节 OA 的记录，平均早于编码诊断约 1.93 年。有既往记录的脊柱关节炎、膝关节骨关节炎、高血压和高脂血症的髋关节 OA 患者更有可能被记录为髋关节 OA 编码。
本研究使用荷兰 EHR 表明，髋关节 OA 的流行病学估计可能存在低估。通过使用我们的算法，可以将叙述性数据添加到编码数据中，以便基于常规医疗保健数据进行更真实的流行病学估计。然而，开发有效的算法仍然是一个挑战，这可能是由于一般实践中髋关节疼痛的诊断复杂性所致。
