ObjectiveTo develop and validate a novel comorbidity score (multisource comorbidity score (MCS)) predictive of mortality, hospital admissions and healthcare costs using multiple source information from the administrative Italian National Health System (NHS) databases.MethodsAn index of 34 variables (measured from inpatient diagnoses and outpatient drug prescriptions within 2 years before baseline) independently predicting 1-year mortality in a sample of 500 000 individuals aged 50 years or older randomly selected from the NHS beneficiaries of the Italian region of Lombardy (training set) was developed. The corresponding weights were assigned from the regression coefficients of a Weibull survival model. MCS performance was evaluated by using an internal (ie, another sample of 500 000 NHS beneficiaries from Lombardy) and three external (each consisting of 500 000 NHS beneficiaries from Emilia-Romagna, Lazio and Sicily) validation sets. Discriminant power and net reclassification improvement were used to compare MCS performance with that of other comorbidity scores. MCS ability to predict secondary health outcomes (ie, hospital admissions and costs) was also investigated.ResultsPrimary and secondary outcomes progressively increased with increasing MCS value. MCS improved the net 1-year mortality reclassification from 27% (with respect to the Chronic Disease Score) to 69% (with respect to the Elixhauser Index). MCS discrimination performance was similar in the four regions of Italy we tested, the area under the receiver operating characteristic curves (95% CI) being 0.78 (0.77 to 0.79) in Lombardy, 0.78 (0.77 to 0.79) in Emilia-Romagna, 0.77 (0.76 to 0.78) in Lazio and 0.78 (0.77 to 0.79) in Sicily.ConclusionMCS seems better than conventional scores for predicting health outcomes, at least in the general population from Italy. This may offer an improved tool for risk adjustment, policy planning and identifying patients in need of a focused treatment approach in the everyday medical practice.

Access to healthcare services for undocumented migrants is one of the main public health issues currently being debated among European countries. Exclusion from primary healthcare services may lead to serious consequences for migrants' health. We analyzed the risk among undocumented migrants, in comparison with regular migrants, of being hospitalized for preventable conditions in the Region of Sicily (Italy). We performed a hospital-based cross-sectional study of the foreign population hospitalized in the Sicily region between 1 January 2003 and 31 December 2013. The first outcome was the proportion of avoidable hospitalization (AHs) among regular and irregular migrants. Second outcomes were the subcategories of AHs for chronic, acute and vaccine preventable diseases. 85 309 hospital admissions were analyzed. In the hospitalized population, in comparison to regular migrants, undocumented migrants show a higher proportion of hospitalization for diseases preventable through primary and preventive care (AOR1·48, 95%CI 1·37-1·59). The proportion of avoidable hospitalizations associated with the lack of legal status is higher for vaccine preventable conditions (AOR 2·06, 95%CI 1·66-2·56) than for chronic conditions (AOR 1·47, 95%CI 1·42-1·63) and acute conditions (AOR 1·37; 95%CI 1·23-1·53). Between 2003 and 2013, the proportion of avoidable hospitalizations decreased both in regular and undocumented migrants but decreased faster for regular than for undocumented migrants. Undocumented migrants experience higher proportion of hospitalization for preventable conditions in comparison with regular migrants probably due to a lack of access to the national healthcare service. Policies and strategies to involve them in primary healthcare and preventive services should be developed to tackle this inequality.

BackgroundThe area of Gela was included among the 57 Italian polluted sites of national interest for environmental remediation because of its widespread contamination from a petrochemical complex. The present study investigates mortality and morbidity of the cohort of Gela petrochemical workers with the aim of disentangling occupational from residential risk.MethodsMortality was assessed for 5,627 men hired from 1960, year of the plant start-up, to 1993; it was followed up for vital status in the period 1960–2002. Morbidity was analysed for 5,431 workers neither dead nor lost to follow-up from 1960 to 2001 and was based on Hospital Discharge Records in the period 2001–2006. The work experience was classified in terms of job categories such as blue collars, white collars, and both – workers who shifted from blue to white collar (95%) or vice versa. An ad hoc mobility model was applied to define qualitative categories of residence in Gela, as residents and commuters. Standardized Mortality Ratios (SMRs) and Mortality Rate Ratios (MRRs) were computed, the latter by using a Poisson regression model. Morbidity was analyzed in terms of Hospital Discharge Odds Ratios (HDORs) through a logistic regression model. While performing the internal comparisons, white collars was the reference category for the job analysis, and commuters was the reference category for the residential analysis.ResultsIn the light of epidemiological evidence about health risk from petrochemical industries in both occupational and environmental settings, and/or on the basis of information about occupational and residential contamination and health risk in the area of Gela, noteworthy results are shown for lung cancer [MRR: 2.11 (CI 90%; 0.96-4.63) in blue collars; 1.71 (1.09-2.69) in residents], respiratory diseases [HDOR: 2.0 (1.0-3.0) in blue collars; 1.4 (0.96-2.06) in residents] and genitourinary diseases [HDOR: 1.34 (1.06-1.68) in blue collars; 1.23 (1.04-1.45) in residents].ConclusionsThe results support a role of the exposures in the occupational and residential settings, the latter due to the local ascertained contamination, in affecting the workers’ health. These results underline the urgent need of water, soil, air and food-chain monitoring programs, to discover active sources of exposure and consequently define public health interventions.

Background Multimorbidity is a growing concern for healthcare systems, with many countries experiencing demographic transition to older population profiles. A simple multisource comorbidity score (MCS) has been recently developed and validated. A very large real-world investigation was conducted with the aim of measuring inequalities in the MCS distribution across Italy. Methods Beneficiaries of the Italian National Health Service aged 50–85 years who in 2018 were resident in one of the 10 participant regions formed the study population (15.7 million of the 24.9 million overall resident in Italy). MCS was assigned to each beneficiary by categorizing the individual sum of the comorbid values (i.e. the weights corresponding to the comorbid conditions of which the individual suffered) into one of the six categories denoting a progressive worsening comorbidity status. MCS distributions in women and men across geographic partitions were compared. Results Compared with beneficiaries from northern Italy, those from centre and south showed worse comorbidity profile for both women and men. MCS median age (i.e. the age above which half of the beneficiaries suffered at least one comorbidity) ranged from 60 (centre and south) to 68 years (north) in women and from 63 (centre and south) to 68 years (north) in men. The percentage of comorbid population was lower than 50% for northern population, whereas it was around 60% for central and southern ones. Conclusion MCS allowed of capturing geographic variability of multimorbidity prevalence, thus showing up its value for addressing health policy in order to guide national health planning.