IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy.
Dipartimento di Scienze Biomediche e NeuroMotorie, Università Degli Studi di Bologna, Bologna, Italy.
Neuroepidemiology. 2023;57(5):336-344. doi: 10.1159/000533362. Epub 2023 Aug 7.
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.
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.
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.
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.
健康行政数据库被广泛用于估计帕金森病（PD）的患病率。一般来说，很少有数据库经过验证以测试其诊断准确性，意大利也没有。主要目的是使用临床诊断作为参考标准，在意大利 PD 患者样本中验证两种用于识别 PD 患者的算法。第二个目的是从 2010 年到 2019 年，估计博洛尼亚地方卫生信托基金中 PD 的 10 年患病率趋势。
将两种算法（索引测试）应用于健康管理数据库（住院记录、药物处方、医疗费用豁免），并由一位专家神经病学家（参考标准）对连续门诊患者的 PD 临床诊断进行验证。计算了敏感性和特异性以及相对 95%置信区间（CI）。特定年份的 PD 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同年总人口数（×1000）的比值，按年龄、性别和居住地区分层。
两种算法对识别 PD 患者均具有较高的准确性：一种算法的敏感性为 94.2%（CI：88.4-97.6），另一种算法的特异性为 98.1%（CI：97.7-98.5）。对于患病率的估计，我们选择了特异性最高且总误分类病例数最少的算法。截至 2019 年 12 月 31 日，我们共确定了 3798 名 PD 患者，患病率为 4.3/1000 居民（CI：4.2-4.4）。男性（4.7，CI：4.5-5.0）的患病率高于女性（3.8，CI：3.7-4.0），并且随着年龄的增长而增加。随着时间的推移，粗患病率略有升高，因为人口老龄化逐渐加剧。当按年龄组分层患病率时，我们没有观察到趋势，除了 45-64 岁年龄段，我们观察到随着时间的推移呈上升趋势。
基于行政数据的算法在检测意大利公共卫生系统中的 PD 患者时具有较高的准确性。在意大利北部的一个大型人群中，在 2010-2019 年的十年间，患病率增加了约 10%，这是由于预期寿命的延长所致。这些数据可能有助于规划 PD 患者的医疗保健资源分配。
