INTRODUCTION Health administrative databases are widely used for the estimation of the prevalence of Parkinson's disease (PD). Few in general, and none used in Italy, have been validated by testing their diagnostic accuracy. The primary objective was to validate two algorithms for the identification of persons with PD using clinical diagnosis as the reference standard on an Italian sample of people with PD. The second objective was to estimate 10-year trends in PD prevalence in the Bologna Local Health Trust from 2010 to 2019. METHODS Two algorithms (index tests) applied to health administrative databases (hospital discharge, drug prescriptions, exemptions for medical costs) were validated against clinical diagnosis of PD by an expert neurologist (reference standard) in a cohort of consecutive outpatients. Sensitivity and specificity with relative 95% confidence intervals (CIs) were calculated. The prevalence of PD in a specific year was estimated as the ratio between the number of subjects fulfilling any criteria of the algorithm with better diagnostic accuracy and the total population in the same year (×1,000), stratified by age, sex, and district of residence. RESULTS The two algorithms showed high accuracy for identifying patients with PD: one with greater sensitivity of 94.2% (CI: 88.4-97.6) and the other with greater specificity of 98.1% (CI: 97.7-98.5). For the estimation of prevalence, we chose the most specific algorithm with the fewest total number of misclassified cases. We identified 3,798 people with PD as of December 31, 2019, corresponding to a prevalence of 4.3 per 1,000 inhabitants (CI: 4.2-4.4). Prevalence was higher in males (4.7, CI: 4.5-5.0) than females (3.8, CI: 3.7-4.0) and increased with age. The crude prevalence over time was slightly elevated as it followed a progressive aging of the population. When stratifying the prevalence for age groups, we did not observe a trend except in the 45-64 year category where we observed an increasing trend over time. CONCLUSION Algorithms based on administrative data are accurate when detecting people with PD in the Italian public health system. In a large northern Italian population, increased prevalence of about 10% was observed in the decade 2010-2019 and is explained by increased life expectancy. These data may be useful in planning the allocation of health care resources for people with PD.

中文翻译：

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用于识别帕金森病患者的行政健康数据算法的验证以及意大利博洛尼亚的 10 年患病率趋势。

简介 卫生管理数据库广泛用于估计帕金森病 (PD) 的患病率。一般情况下，很少有（在意大利也没有使用过）通过测试其诊断准确性进行验证。主要目标是使用临床诊断作为意大利帕金森病患者样本的参考标准，验证两种识别帕金森病患者的算法。第二个目标是估计博洛尼亚地方健康信托基金 2010 年至 2019 年 PD 患病率的 10 年趋势。 方法 验证了应用于健康管理数据库（出院、药物处方、医疗费用豁免）的两种算法（指数测试）与神经科医生专家对一组连续门诊患者的 PD 临床诊断（参考标准）进行对比。计算了相对 95% 置信区间 (CI) 的敏感性和特异性。特定年份的帕金森病患病率估计为满足具有更好诊断准确性的算法的任何标准的受试者人数与当年总人口的比率（×1,000），按年龄、性别和地区分层。住宅。结果两种算法在识别 PD 患者方面显示出较高的准确性：一种算法的敏感性更高，为 94.2% (CI: 88.4-97.6)，另一种算法的特异性更高，为 98.1% (CI: 97.7-98.5)。为了估计患病率，我们选择了错误分类病例总数最少的最具体的算法。截至 2019 年 12 月 31 日，我们确定了 3,798 名帕金森病患者，相当于每 1,000 名居民中有 4.3 名帕金森病患者（CI：4.2-4.4）。男性患病率（4.7，CI：4.5-5.0）高于女性（3.8，CI：3.7-4.0），并且随着年龄的增长而增加。随着人口逐渐老龄化，粗患病率随时间略有上升。在对年龄组的患病率进行分层时，除了 45-64 岁类别之外，我们没有观察到任何趋势，在该类别中我们观察到随着时间的推移呈上升趋势。结论 在意大利公共卫生系统中检测帕金森病患者时，基于管理数据的算法是准确的。在意大利北部的大量人口中，2010 年至 2019 年十年间观察到患病率增加了约 10%，这可以通过预期寿命的延长来解释。这些数据可能有助于规划帕金森病患者的医疗保健资源分配。