Multimorbidity in middle-aged women and COVID-19: binary data clustering for unsupervised binning of rare multimorbidity features and predictive modeling.

BACKGROUND: Multimorbidity is typically associated with deficient health-related quality of life in mid-life, and the likelihood of developing multimorbidity in women is elevated. We address the issue of data sparsity in non-prevalent features by clustering the binary data of various rare medical conditions in a cohort of middle-aged women. This study aims to enhance understanding of how multimorbidity affects COVID-19 severity by clustering rare medical conditions and combining them with prevalent features for predictive modeling. The insights gained can guide the development of targeted interventions and improved management strategies for individuals with multiple health conditions. METHODS: The study focuses on a cohort of 4477 female patients, (aged 45-60) in Piedmont, Italy, and utilizes their multimorbidity data prior to the COVID-19 pandemic from their medical history from 2015 to 2019. The COVID-19 severity is determined by the hospitalization status of the patients from February to May 2020. Each patient profile in the dataset is depicted as a binary vector, where each feature denotes the presence or absence of a specific multimorbidity condition. By clustering the sparse medical data, newly engineered features are generated as a bin of features, and they are combined with the prevalent features for COVID-19 severity predictive modeling. RESULTS: From sparse data consisting of 174 input features, we have created a low-dimensional feature matrix of 17 features. Machine Learning algorithms are applied to the reduced sparsity-free data to predict the Covid-19 hospital admission outcome. The performance obtained for the corresponding models are as follows: Logistic Regression (accuracy 0.72, AUC 0.77, F1-score 0.69), Linear Discriminant Analysis (accuracy 0.7, AUC 0.77, F1-score 0.67), and Ada Boost (accuracy 0.7, AUC 0.77, F1-score 0.68). CONCLUSION: Mapping higher-dimensional data to a low-dimensional space can result in information loss, but reducing sparsity can be beneficial for Machine Learning modeling due to improved predictive ability. In this study, we addressed the issue of data sparsity in electronic health records and created a model that incorporates both prevalent and rare medical conditions, leading to more accurate and effective predictive modeling. The identification of complex associations between multimorbidity and the severity of COVID-19 highlights potential areas of focus for future research, including long COVID and intervention efforts.

Hospitalisation for herpes zoster in people with and without diabetes: A 10-year-observational study.

AIMS: This study explores the association between Herpes Zoster (HZ) hospitalizations and diabetes in Piedmont, Italy from 2010 to 2019. Focusing on the burden of HZ hospitalizations in diabetic and non-diabetic groups, it aims to identify risk factors in diabetics to enhance prevention strategies. METHODS: In a two-phase study, we first compared age-standardized HZ hospitalization rates between diabetic and non-diabetic individuals from 2010 to 2019. We then examined hospitalization risk factors for HZ within a diabetic patient cohort managed by regional diabetes clinics. RESULTS: Of 3,423 HZ hospitalizations in 2010-2019, 17.9 % (613 cases) were diabetic patients, who exhibited higher hospitalization rates (15.9 to 6.0 per 100,000) compared to non-diabetese individuals. Among diabetics subjects risk factors for HZ hospitalization included age over 65, obesity (BMI > 30), and poor glycemic control (HbA1c > 8.0 %). These patients had a 40 % increased rehospitalization risk and a 25 % higher risk of severe complications, such as stroke and myocardial infarction, post-HZ. CONCLUSIONS: Diabetes markedly increases HZ hospitalization rates, rehospitalization, and complication risks. These findings underscore the need for preventive strategies, especially improved glycemic control among high-risk diabetic patients, to inform public health policies and clinical practices aimed at mitigating HZ's impact on this population.

Equity in the recovery of elective and oncological surgery volumes after the COVID-19 lockdown: a multicentre cohort study in Italy.

BACKGROUND: The COVID-19 pandemic has had, and still has, a profound impact on national health systems, altering trajectories of care and exacerbating existing inequalities in health. Postponement of surgeries and cancellation of elective surgical procedures have been reported worldwide. In Italy, the lock-down measures following the COVID-19 pandemic caused cancellations of surgical procedures and important backlogs; little is known about potential social inequalities in the recovery process that occurred during the post-lockdown period. This study aims at evaluating whether all population social strata benefited equally from the surgical volumes' recovery in four large Italian regions. METHODS: This multicentre cohort study covers a population of approximately 11 million people. To assess if social inequalities exist in the recovery of eight indicators of elective and oncological surgery, we estimated Risk Ratios (RR) through Poisson models, comparing the incidence proportions of events recorded during COVID-19 (2020-21) with those in pre-pandemic years (2018-19) for each pandemic period and educational level. RESULTS: Compared to 2018-19, volumes of elective surgery showed a U-shape with the most significant drops during the second wave or the vaccination phase. The recovery was socially unequal. At the end of 2021, incidence proportions among highly educated people generally exceeded the expected ones; RRs were 1.31 (95%CI 1.21-1.42), 1.24 (95%CI 1.17-1.23), 1.17 (95%CI 1.08-1.26) for knee and hip replacement and prostatic surgery, respectively. Among low educated patients, RR remained always < 1. Oncological surgery indicators showed a similar social gradient. Whereas volumes were preserved among the highly educated, the low educated were still lagging behind at the end of 2021. CONCLUSIONS: Surgical procedures generally returned to pre-pandemic levels but the low educated experienced the slowest recovery. An equity-oriented appraisal of trends in healthcare provision should be included in pandemic preparedness plans, to ensure that social inequalities are promptly recognised and tackled.

Triptans utilization in Italian population: A real-life study in community pharmacies.

The term Headache Disorders (HD) refers to a number of nervous system pathologies characterised by recurrent headaches. Despite the serious impact HD have on the health system, society, and the economy, these are an underestimated, underdiagnosed, and, hence, undertreated phenomenon. Triptans are the first-line therapy for the acute treatment of moderate to severe migraine but their utilization is still inadequate, perhaps also because in Italy no triptan can be bought without a medical prescription. In this article, the data from a 2016-2017 study has been further analysed with the aim of evaluating any associations between the use of triptans and the other series of variables identified in the questionnaire. This further analysis has been connected to the role that community pharmacies could play on this issue. The questionnaire was administered to 4,424 pharmacy users by 610 purposely trained pharmacists working in 514 pharmacies. The survey was carried out in 19 of the 20 Italian regions. The data shows that only 25% of patients suffering from HDs are prescribed triptans. Older patients, those with definite migraines, and those with a chronic disorder resort more frequently to this class of pharmaceuticals, as do those patients in care at a specialist headache centre. The multivariable analysis also confirmed these results. Our study, which performed a direct detection, in real life, on patients requesting pharmacological treatment for a migraine headache, therefore confirmed the need to investigate the reasons behind the low use and prescription of triptans in the Italian population. Moreover, any future studies should take advantage of community pharmacies, plan actions that would allow a series of evaluations over time of the requirements of migraineurs, and establish a process to put these patients under the care of the pharmacy to ensure adherence to therapy.

Monitoring and screening COPD in community pharmacies: experimentation in Italy

Objective: COPD is one of the most important causes of morbidity and mortality worldwide. The health and economic burden of COPD may in part be reduced by early disease case finding and a correct therapy. This study aimed to investigate the feasibility of a community pharmacy programme for COPD case finding among previously undiagnosed subjects and for monitoring and enhancing adherence to prescribed pharmacological therapies among patients with confirmed COPD. Methods: The intervention was conducted in hundred community pharmacies in Piedmont (northwest Italy) and developed in two different arms: a case finding one through the administration of a specific questionnaire and the spirometry measurement and the adherence one through the administration of a questionnaire exploring the impact of the disease and the therapy adherence. Persons considered at risk to develop the COPD disease or non-controlled patients were referred to the GP or were invited to return in the pharmacy for a follow-up interview. Results: Overall, 844 subjects, out of 934 enrolled, completed the baseline interview. 103 subjects (25.7% of the 401 enrolled in the case finding arm) were considered at risk of suffering from COPD. Lower educated subjects and those without social support were more frequently at very high risk. Five returned to the pharmacy with a confirmed medical diagnosis. Among the 443 patients interviewed we found non-adherence value (depending on the drug) varying from 31% to 46%. A significant protection from non-adherence to bronchodilators was found among patients with comorbidities and among people living alone. Conclusions: We showed that opportunistic screening for COPD is feasible in community pharmacies. Concerning adherence to therapy in pharmacies, it would be necessary to identify different methods of enrolment in order to involve only those patients who are less adherent or who have difficulties in the management of therapy and chronic pathology. (AU)

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

People with multiple sclerosis (PWMS) are at high risk of being affected by the disruption of health services that occurred during the COVID-19 pandemic months. The aim of this study was to evaluate the effect of the pandemic on the health outcomes of PWMS. PWMS and MS-free residing in Piedmont (north-west of Italy) were identified from electronic health records and linked with the regional COVID-19 database, the hospital-discharge database, and the population registry. Both cohorts (9333 PWMS and 4,145,856 MS-free persons) were followed-up for access to swab testing, hospitalisation, access to the Intensive Care Unit (ICU), and death from 22 February 2020 to 30 April 2021. The relationship between the outcomes and MS was evaluated using a logistic model, which was adjusted for potential confounders. The rate of swab testing was higher in PWMS, but the positivity to infection was similar to that of MS-free subjects. PWMS had a higher risk of hospitalisation (OR = 1.74; 95% IC, 1.41-2.14), admission to ICU (OR = 1.79; 95% IC, 1.17-2.72), and a slight, albeit not statistically significant, increase in mortality (OR = 1.28; 95% IC, 0.79-2.06). Compared to the general population PWMS with COVID-19 had an increased risk of hospitalization and admission to the ICU; the mortality rate did not differ.

Hepatocellular carcinoma in a large cohort of type 2 diabetes patients.

AIMS: To elucidate the current burden of hepatocellular carcinoma (HCC) in type 2 diabetes (DM2) with a focus on the associated clinical determinants. METHODS: Incidence of HCC between 2009 and 2019 in the diabetic and general population was calculated from regional administrative and hospital databases. Potential determinants of the disease were evaluated with a follow-up study. RESULTS: In the DM2 population, the incidence resulted in 8.05 cases per 10,000 yearly. This rate was three times higher than that of the general population. 137,158 patients with DM2 and 902 HCC were found for the cohort study. The survival of HCC patients was 1/3 of that of cancer-free diabetic controls. Age, male sex, alcohol abuse, previous viral hepatitis B and C, cirrhosis, low platelet count, elevated GGT/ALT, higher BMI and HbA1c levels were associated with HCC occurrence. Diabetes therapy was not adversely associated with HCC development. CONCLUSION: Incidence of HCC in DM2 is more than tripled compared to the general population with high mortality. These figures are higher than those expected from the previous evidence. In parallel with known risk factors for liver disease, such as viruses and alcohol, insulin-resistance characteristics are associated with a higher probability of HCC.

Multimorbidity and SARS-CoV-2-Related Outcomes: Analysis of a Cohort of Italian Patients.

BACKGROUND: Since the outbreak of the COVID-19 pandemic, identifying the main risk factors has been imperative to properly manage the public health challenges that the pandemic exposes, such as organizing effective vaccination campaigns. In addition to gender and age, multimorbidity seems to be 1 of the predisposing factors coming out of many studies investigating the possible causes of increased susceptibility to SARS-CoV-2 infection and adverse outcomes. However, only a few studies conducted have used large samples. OBJECTIVE: The objective is to evaluate the association between multimorbidity, the probability to be tested, susceptibility, and the severity of SARS-CoV-2 infection in the Piedmont population (Northern Italy, about 4 million inhabitants). For this purpose, we considered 5 main outcomes: access to the swab, positivity to SARS-CoV-2, hospitalization, intensive care unit (ICU) admission, and death within 30 days from the first positive swab. METHODS: Data were obtained from different Piedmont health administrative databases. Subjects aged from 45 to 74 years and infections diagnosed from February to May 2020 were considered. Multimorbidity was defined both with the Charlson Comorbidity Index (CCI) and by identifying patients with previous comorbidities, such as diabetes and oncological, cardiovascular, and respiratory diseases. Multivariable logistic regression models (adjusted for age and month of infection and stratified by gender) were performed for each outcome. Analyses were also conducted by separating 2 age groups (45-59 and 60-74 years). RESULTS: Of 1,918,549 subjects, 85,348 (4.4%) performed at least 1 swab, of whom 12,793 (14.9%) tested positive for SARS-CoV-2. Of these 12,793 subjects, 4644 (36.3%) were hospitalized, 1508 (11.8%) were admitted to the ICU, and 749 (5.9%) died within 30 days from the first positive swab. Individuals with a higher CCI had a higher probability of being swabbed but a lower probability of testing positive. We observed the same results when analyzing subjects with previous oncological and cardiovascular diseases. Moreover, especially in the youngest group, we identified a greater risk of being hospitalized and dying. Among comorbidities considered in the study, respiratory diseases seemed to be the most likely to increase the risk of having a positive swab and worse disease outcomes. CONCLUSIONS: Our study shows that patients with multimorbidity, although swabbed more frequently, are less likely to get infected with SARS-CoV-2, probably due to greater attention on protective methods. Moreover, a history of respiratory diseases is a risk factor for a worse prognosis of COVID-19. Nonetheless, whatever comorbidities affect the patients, a strong dose-response effect was observed between an increased CCI score and COVID-19 hospitalization, ICU admission, and death. These results are important in terms of public health because they help in identifying a group of subjects who are more prone to worse SARS-CoV-2 outcomes. This information is important for promoting targeted prevention and developing policies for the prioritization of public health interventions.

Identification of dementia and MCI cases in health information systems: An Italian validation study.

Introduction: The identification of dementia cases through routinely collected health data represents an easily accessible and inexpensive method to estimate the prevalence of dementia. In Italy, a project aimed at the validation of an algorithm was conducted. Methods: The project included cases (patients with dementia or mild cognitive impairment [MCI]) recruited in centers for cognitive disorders and dementias and controls recruited in outpatient units of geriatrics and neurology. The algorithm based on pharmaceutical prescriptions, hospital discharge records, residential long-term care records, and information on exemption from health-care co-payment, was applied to the validation population. Results: The main analysis was conducted on 1110 cases and 1114 controls. The sensitivity, specificity, and positive and negative predictive values in discerning cases of dementia were 74.5%, 96.0%, 94.9%, and 79.1%, respectively, whereas in detecting cases of MCI these values were 29.7%, 97.5%, 92.2%, and 58.1%, respectively. The variables associated with misclassification of cases were also identified. Discussion: This study provided a validated algorithm, based on administrative data, which can be used to identify cases with dementia and, with lower sensitivity, also early onset dementia but not cases with MCI.

Health status assessment of a population of asylum seekers in Northern Italy.

BACKGROUND: Since 2011 Italy has faced an extraordinary increase in migrants arrivals, mainly from the Mediterranean route, one of the world's most dangerous journeys. The purpose of the present article is to provide a comprehensive picture of the migrants' health status in the "T. Fenoglio" centre, Settimo Torinese (Turin, Italy). METHODS: A retrospective cross-sectional study was conducted using data collected from June 2016 to May 2018 on adult migrants (over 18 years old) from Africa, Middle East and South East Asia (Bangladesh, Cambodia, India, Nepal). Data was collected through the migrants' medical records. Descriptive statistics were performed on socio-demographic variables. The diagnosed diseases were anonymously registered and classified according to the International Classification of Primary Care (ICPC-2). Conditional Inference Trees were used to perform a descriptive analysis of the sample and to detect the covariates with the strongest association with the variables Disease on arrival, Disease after arrival, ICPC on arrival and ICPC after arrival. RESULTS: Analyzed observations were 9 857. 81.8% were men, median age was 23 (Interquartile range: 20.0-27.4). 70.3% of the sample came from Sub-Saharan Africa. 2 365 individuals (24%) arrived at the centre with at least one disease. On arrival, skin (27.71%), respiratory (14.46%), digestive (14.73%) and generic diseases (20.88%) were the most frequent. During the stay respiratory diseases were the most common (25.70%). The highest probability of arriving with a disease occurred in 2018 and during the period September-November 2016, in particular for people from the Horn of Africa. During this period and also in the first half of 2017, skin diseases were the most reported. In seasons with lower prevalence of diseases on arrival the most common disease code was generic for both men and women (usually fever or trauma). CONCLUSIONS: This study provides information on the diverse diseases that affect the asylum seekers population. In our sample, the Horn of Africa was the most troubled area of arrival, with severe conditions frequently reported regarding skin diseases, in particular scabies. 2018 was the most critical year, especially for migrants from the Horn of Africa and Sub-Saharan Africa. During the stay at the camp, the prevalence of respiratory diseases increased. However, skin diseases remained the main issue for people from the Horn of Africa. Overall, the most reported diseases in the sample were dermatological, respiratory, digestive and generic diseases, both on arrival and during the stay. A better understanding of the health status of asylum seekers is an important factor to determine a more efficient reception and integration process and a better allocation of economic resources in the context of migrants' health care.

Indirect impact of the COVID-19 pandemic and its containment measures on social inequalities in hospital utilisation in Italy.

BACKGROUND: The pandemic may undermine the equity of access to and utilisation of health services for conditions other than COVID-19. The objective of the study is to evaluate the indirect impact of COVID-19 and lockdown measures on sociodemographic inequalities in healthcare utilisation in seven Italian areas. METHODS: In this multicentre retrospective study, we evaluated whether COVID-19 modified the association between educational level or deprivation and indicators of hospital utilisation and quality of care. We also assessed variations in gradients by sex and age class. We estimated age-standardised rates and prevalence and their relative per cent changes comparing pandemic (2020) and pre-pandemic (2018-2019) periods, and the Relative Index of Inequalities (RIIs) fitting multivariable Poisson models with an interaction between socioeconomic position and period. RESULTS: Compared with 2018-2019, hospital utilisation and, to a lesser extent, timeliness of procedures indicators fell during the first months of 2020. Larger declines were registered among women, the elderly and the low educated resulting in a shrinkage (or widening if RII <1) of the educational gradients for most of the indicators. Timeliness of procedures indicators did not show any educational gradient neither before nor during the pandemic. Inequalities by deprivation were nuanced and did not substantially change in 2020. CONCLUSIONS: The socially patterned reduction of hospital utilisation may lead to a potential exacerbation of health inequalities among groups who were already vulnerable before the pandemic. The healthcare service can contribute to contrast health disparities worsened by COVID-19 through more efficient communication and locally appropriate interventions.

Indirect impact of Covid-19 on hospital care pathways in Italy.

Earlier in 2020, seven Italian regions, which cover 62% of the Italian population, set up the Mimico-19 network to monitor the side effects of the restrictive measures against Covid-19 on volumes and quality of care. To this aim, we retrospectively analysed hospital discharges data, computing twelve indicators of volume and performance in three clinical areas: cardiology, oncology, and orthopaedics. Weekly indicators for the period January-July 2020 were compared with the corresponding average for 2018-2019; comparisons were performed within 3 sub-periods: pre-lockdown, lockdown, and post-lockdown. The weekly trend of hospitalisations for ST-segment elevation myocardial infarction (STEMI) showed a 40% reduction, but the proportion of STEMI patients with a primary PTCA did not significantly change from previous years. Malignant neoplasms surgery volumes differed substantially by site, with a limited reduction for lung cancer (< 20%) and greater declines (30-40%) for breast and prostate cancers. The percentage of timely surgery for femoral neck in the elderly remained constantly higher than the previous 2 years whereas hip and knee replacements fell dramatically. Hospitalisations have generally decreased, but the capacity of a timely and effective response in time-dependent pathways of care was not jeopardized throughout the period. General trends did not show important differences across regions, regardless of the different burden of Covid-19. Preventive and primary care services should adopt a pro-active approach, moving towards the identification of at-risk conditions that were neglected during the pandemic and timely addressing patients to the secondary care system.

Monitoring adherence to pharmacological therapy and follow-up examinations among patients with type 2 diabetes in community pharmacies. Results from an experience in Italy.

INTRODUCTION: Type 2 diabetes is an important public health issue, yet adherence to drugs and regular clinical follow-up is still suboptimal. This study aims to evaluate a community pharmacy programme for monitoring and enhancing adherence to prescribed pharmacological therapies and recommended examinations among patients with confirmed diabetes. METHODS: The intervention was conducted in different Italian areas between April 2017 and January 2018. All adult patients who entered a pharmacy with a personal prescription for any antidiabetic drug and agreed to participate, were interviewed. Those found to be non-adherent received counselling from the pharmacists. All patients were invited for a follow-up interview after 3 months. RESULTS: Overall, 930 patients were enrolled and completed the baseline interview. We found low rates of non-adherence, ranging from 8% to 13% for prescribed pharmacological therapies, and 11-29% for the recommended clinical examinations. Non-adherence to oral therapies was higher among younger and recently diagnosed patients; that to clinical examinations was higher in men, those with an intermediate duration of diabetes and less educated patients. Large geographical differences persisted after the adjustment for individual factors. Only 306 patients (32.9%) returned for the follow-up interview, most of whom were already adherent at baseline. CONCLUSIONS: Poor adherence to drugs or clinical examinations is not easy to identify in the usual operating setting of community pharmacies. Furthermore, the majority of patients did not return for follow-up, making it impossible to evaluate the efficacy of the pharmacists' counselling. It might be more effective to plan interventions addressed to specific subgroups of patients or areas.

Hepatic fibrosis of any origin in a large population of type 2 diabetes patients.

BACKGROUND AND AIMS: Excess morbidity and mortality from chronic liver disease in type 2 diabetes (T2DM) is recognized; however, the clinical features associated with liver fibrosis (LF) of any origin are poorly known. Metabolic status and/or coexisting complications over time may play a role. METHODS AND RESULTS: We interrogated the database of the diabetes unit network of Piedmont (Italy) (71,285 T2DM patients) and calculated a fibrosis-4 score (FIB-4) from data recorded between 2006 and 2019. Comorbidities were obtained by linkage with hospital data. The study population was subdivided by aetiology of LF (alcoholic, viral, metabolic). Associations between upper level of FIB-4 and demographic and clinical variables were evaluated separately for each group using robust Poisson models and presented as prevalence ratios. Nearly one-quarter (24%) of T2DM patients had some form of LF: viral (0.44%) and alcoholic (0.53%) forms were far less frequent than metabolic ones (22.7%). Only 1 out of 5 of these patients had a history of known cirrhosis. Age, male sex, duration of diabetes, coronary disease, hyperuricemia, renal failure, and features of liver failure (e.g., lower body-mass index, lipid and HbA1c levels) were positively associated with metabolic LF. More intensive treatments with insulin and segretagogue emerged as a significant predictive indicators of LF of metabolic origin. CONCLUSION: A sizeable proportion of T2DM patients has some degree of LF, mainly of metabolic origin and often undiagnosed. There is a need to clarify whether the link between insulin therapy and advanced LF is causal or not.

From swab testing to health outcomes within the T2DM population: Impact of diabetes background on COVID19 progression.

BACKGROUND: We aimed to study the impact of diabetes background on COVID-19 progression from swab testing to health outcomes in type 2 diabetes (T2DM). METHODS: From the database of the diabetes units of Piedmont-Italy we extracted records of T2DM patients, which were linked with the swab-testing-database, and the database of hospital discharges. Five outcomes (PCR testing, PCR testing positivity, hospitalization, Intensive Care Unit (ICU), death) were evaluated using robust Poisson models. RESULTS: Among 125,021 T2DM patients, 1882 had a positive PCR test. Of these patients, 49.4% were hospitalized within 30 days, 11.8% were admitted to an ICU, and 27.1% died. Greater probability of death was associated with age, male sex, liver and renal impairment, Hba1c above 8%, and former smoking. Hospitalization and ICU admission were mainly affected by age, male sex, hypertension, and metabolic control. Notably, ICU admissions were reduced in very elderly people. No outcomes were associated with educational level. CONCLUSIONS: Hospitalization and ICU admission are heavily affected by age and local triage policy. A key finding was that men who were > 75 years old and poorly compensated were highly vulnerable patients. Renal and/or hepatic impairment are additional factors. This information may be useful for addressing intervention priorities.

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.

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.