Validation of an Algorithm to Detect Multiple Sclerosis Cases in Administrative Health Databases in Piedmont (Italy): An Application to the Estimate of Prevalence by Age and Urbanization Level

Abstract

Introduction: Italy is considered a high-risk country for multiple sclerosis (MS). Exploiting electronic health archives (EHAs) is highly useful to continuously monitoring the prevalence of the disease, as well as the care delivered to patients and its outcomes. The aim of this study was to validate an EHA-based algorithm to identify MS patients, suitable for epidemiological purposes, and to estimate MS prevalence in Piedmont (North Italy). Methods: MS cases were identified, in the period between January 1, 2012 and December 31, 2017, linking data from 4 different sources: hospital discharges, drug prescriptions, exemptions from co-payment to health care, and long-term care facilities. Sensitivity of the algorithm was tested through record linkage with a cohort of 656 neurologist-confirmed MS cases; specificity was tested with a cohort of 2,966,293 residents presumably not affected by MS. Undercount was estimated by a capture-recapture method. We calculated crude, and age- and gender-specific prevalence. We also calculated age-adjusted prevalence by level of urbanization of the municipality of residence. Results: On December 31, 2017, the algorithm identified 8,850 MS cases. Sensitivity was 95.9%, specificity was 99.97%, and the estimated completeness of ascertainment was 91.9%. The overall prevalence, adjusted for undercount, was 152 per 100,000 among men and 286 among women; it increased with increasing age and reached its peak value in the 45- to 54-year class, followed by a progressive reduction. The age-adjusted prevalence of residents in cities was 15% higher than in those living in the countryside. Discussion/Conclusion: We validated an algorithm based on EHAs to identify cases of MS for epidemiological use. The prevalence of MS, adjusted for undercount, was among the highest in Italy. We also found that the prevalence was higher in highly urbanized areas.

Multiple sclerosis epidemiological trends in Italy highlight the environmental risk factors

“…More recently, significant variations in MS prevalence between urban areas and adjacent hilly areas associated to PM 2.5 concentrations in both Provinces [ 10 , 18 ]. In addition, a recent study in Piedemont region (North-West of Padan Plain) further disclosed a relationship between MS prevalence and levels of urbanization [ 49 ]. Thus, air quality may be identified as one of the possible risk factors for MS in the Padan Plain.…”

Performance of administrative databases for identifying individuals with multiple sclerosis

“…Several countries have conducted validation studies of algorithms used to detect individuals with MS in ADs. The criteria used were close to those of the French AD: mainly inpatient/outpatient encounters 39 – 41 , more rarely drug dispensing records as well or even disease-specific payment exemption 42 , 43 . However, the chosen references were imperfect in exhaustively identifying MS cases.…”

“…Therefore, this strategy does not adequately detect the FNs missed by ADs. Additional studies used regional registries populated by one 45 or more 42 , 43 specialized regional care centers. Nevertheless, in contrast with individuals in the ReLSEP, those not followed up in these institutions could not be identified by the reference.…”

COVID-19 and Health Outcomes in People with Multiple Sclerosis: A Population-Based Study in Italy

“…Using a previously validated algorithm that has shown to be highly reliable (sensitivity 95.9%, specificity 99.9%) [ 19 ], we identified PWMS residing in Piedmont on 22 February 2020: the date of the first death from COVID-19 recorded in Italy. Briefly, the algorithm was based on the deterministic record linkage of four data sources: hospital discharges with a primary or secondary diagnosis of MS; the drug prescriptions used for MS; subjects who obtained exemption from the co-payment of drugs and outpatient visits due to the diagnosis of MS; patient resident in long-term care facilities with a diagnosis of MS. Any subject recorded in at least one of the above databases was considered an MS case.…”