Multiple Sclerosis in the Campania Region (South Italy): Algorithm Validation and 2015–2017 Prevalence

International Journal of Environmental Research and Public Health

Maria Pia Sormani¹  Roberta Giordana²  Maria Triassi³  Ilaria Loperto³  Raffaele Palladino³  Roberta Lanzillo⁴  Nicola Capasso⁴  Marcello Moccia⁴  Vincenzo Brescia Morra⁴  Martina Petruzzo⁴  Maria Grazia Fumo⁵ 

[1] Biostatistics Unit, Department of Health Sciences, University of Genoa, 16121 Genoa, Italy;Campania Region Healthcare System Commissioner Office, 80131 Naples, Italy;Department of Public Health, Federico II University, 80131 Naples, Italy;Multiple Sclerosis Clinical Care and Research Centre, Department of Neuroscience, Reproductive Science and Odontostomatology, Federico II University, Via Sergio Pansini 5, 80131 Naples, Italy;Regional Healthcare Society (So.Re.Sa), 80131 Naples, Italy;

关键词: multiple sclerosis;    prevalence;    routinely collected healthcare data;    Italy;   

DOI  :  10.3390/ijerph17103388

来源: DOAJ

【 摘 要 】

We aim to validate a case-finding algorithm to detect individuals with multiple sclerosis (MS) using routinely collected healthcare data, and to assess the prevalence of MS in the Campania Region (South Italy). To identify individuals with MS living in the Campania Region, we employed an algorithm using different routinely collected healthcare administrative databases (hospital discharges, drug prescriptions, outpatient consultations with payment exemptions), from 1 January 2015 to 31 December 2017. The algorithm was validated towards the clinical registry from the largest regional MS centre (n = 1460). We used the direct method to standardise the prevalence rate and the capture-recapture method to estimate the proportion of undetected cases. The case-finding algorithm including individuals with at least one MS record during the study period captured 5362 MS patients (females = 64.4%; age = 44.6 ± 12.9 years), with 99.0% sensitivity (95% CI = 98.3%, 99.4%). Standardised prevalence rate per 100,000 people was 89.8 (95% CI = 87.4, 92.2) (111.8 for females [95% CI = 108.1, 115.6] and 66.2 for males [95% CI = 63.2, 69.2]). The number of expected MS cases was 2.7% higher than cases we detected. We developed a case-finding algorithm for MS using routinely collected healthcare data from the Campania Region, which was validated towards a clinical dataset, with high sensitivity and low proportion of undetected cases. Our prevalence estimates are in line with those reported by international studies conducted using similar methods. In the future, this cohort could be used for studies with high granularity of clinical, environmental, healthcare resource utilisation, and pharmacoeconomic variables.

【 授权许可】

Unknown