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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.

Background and aims To validate a set of indicators for monitoring the quality of care of patients with diabetes in ‘real-life’ practice through its relationship with measurable clinical outcomes and healthcare costs. Methods and results A population-based cohort study was carried out by including the 20,635 patients, residents in the Lombardy Region (Italy), who in the year 2012 were newly taken-in-care for diabetes. Adherence with clinical recommendations (i.e., controls for glycated haemoglobin, lipid profile, urine albumin excretion and serum creatinine) was recorded during the first year after the patient was taken-in-care, and categorized according whether he/she complied with none or almost none (0 or 1), just some (2) or all or almost all (3 or 4) the recommendations, respectively denoted as poor, intermediate and high adherence. Short- and long-term complications of diabetes, and healthcare cost incurred by the National Health Service, were assessed during follow-up. Compared with patients with poor adherence, those with intermediate and high adherence respectively showed (i) a delay in outcome occurrence of 13 days (95% CI, -2 to 27) and 23 days (9 to 38), and (ii) a lower healthcare cost of 54 € and 77 €. In average, a gain of 18 Euros and 15 Euros for each day free from diabetic complication by increasing adherence respectively from poor to intermediate and from poor to high were observed. Conclusion Close control of patients with diabetes through regular clinical examinations must be considered the cornerstone of national guidance, national audits, and quality improvement incentive schemes.

Background: Malnutrition in elderly inpatients hospitalized on medical wards is a significant public health concern. The aim of this study was to investigate nutritional markers as mortality predictors following discharge in hospitalized medical elderly patients. Materials and methods: This is a prospective observational cohort study with follow-up of 48 months. Two hundred and twenty-five individuals aged 60 and older admitted from the hospital emergency room in the past 48 h were investigated at the medical ward in the University hospital in Palermo (Italy). Anthropometric and clinical measurements, Mini-nutritional Assessment (MNA) questionnaire, bioelectrical (BIA) phase angle (PA), grip strength were obtained all within 48 h of admission. Mortality data were verified by means of mortality registry and analysed using Cox-proportional hazard models. Results: Ninety (40%) participants died at the end of follow-up. There were significant relationships between PA, MNA score, age and gender on mortality. Patients in the lowest tertile of PA (< 4·6°) had higher mortality estimates [I vs II tertile: hazard ratio (HR) = 3·40; 95% confidence interval (CI): 2·01–5·77; II vs III tertile: HR = 3·83; 95% CI: 2·21–6·64; log-rank test: χ2 = 43·6; P < 0·001]. Similarly, the survival curves demonstrated low MNA scores (< 22) were associated with higher mortality estimates (HR = 1·85; 95% CI: 1·22–2·81 χ2 = 8·2; P = 0·004). Conclusions: The MNA and BIA-derived phase angle are reasonable tools to identify malnourished patients at high mortality risk and may represent useful markers in intervention trials in this high-risk subgroup.

Aim: Primary endpoint was to report polypharmacy distribution in the general population vs ≥65 years old people and to examine the frequency of drug–drug interactions (DDIs) in the Health Local Unit of Palermo, Italy, in relationship with patients’ age. Methods: Drug prescription data for the year 2014 were extracted from the database of the Local Health Unit of Palermo Province, Italy. Patients were divided into five age groups (0–13, 14–64, 65–69, 70–74, and ≥75 year old). The detection of potential DDIs in polypharmacy profiles was performed with NavFarma software (Infologic srl, Padova, Italia), with DDI classification provided by tool Micromedex Drug Reax (Truven Health Analitics, Michigan, USA). Results: We analyzed data of 1,324,641 patients, and 15,801,191 medical prescription were recorded; of these, 11,337,796 regarded chronic conditions. The drug prescriptions reached the highest values in the 65–69 and 70–74 age groups (p = 0.005 and p = 0.008 vs age 14–64 respectively). An overall amount of 6,094,373 DDIs were detected, of which 47,173 were contraindicated. Median number of DDIs was higher in 65–69 and 70–74 age groups (p = 0.008 and p = 0.012 vs age 14–64, respectively). Regarding contraindicated DDIs a significant difference was detected comparing 14–64 vs ≥65 age groups (p = 0.010 vs 65–69 group, p= 0.005 vs 70–74 group and ≥75 group). Conclusions: Polypharmacy is a phenomenon acquiring increasing dimensions also in our province. It interests particularly the older subjects, and assumes a dramatic accent when it is put in relationship with the frequency of DDIs. A proactive vigilance about potential life threatening drug interactions is mandatory.