Measuring multimorbidity inequality across Italy through the multisource comorbidity score: a nationwide study

Abstract

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.

Comparing the Prevalence of Polypharmacy and Potential Drug-Drug Interactions in Nursing Homes and in the Community Dwelling Elderly of Emilia Romagna Region

“…Our findings should undoubtedly be ascribed to the local setting. Nevertheless, the Emilia Romagna Region represents an Italian area with high-quality healthcare data archives and they are largely used for research and surveillance purposes ( Gini et al, 2014 ; Trifirò et al, 2019 ; Corrao et al, 2020 ). Therefore, they could represent a reference for international comparisons and an input toward an Italian mapping of polypharmacy and DDIs especially in nursing homes.…”

Cardiovascular Outcomes and Mortality Associated With Discontinuing Statins in Older Patients Receiving Polypharmacy

“… 22 In addition, we considered the Multisource Comorbidity Score (MCS), which is a new index of patients’ clinical status based on 34 CV and non-CV conditions (eg, heart failure, arrhythmia, cancer) derived from inpatient diagnostic information and outpatient drug prescriptions and weighted according to their strength with mortality. 23 , 24 Members in the statin discontinuing and maintaining groups were then 1:1 matched on their PS using a nearest neighbor matching algorithm without replacement with a caliper of 0.01. 25 …”

“…22 In addition, we considered the Multisource Comorbidity Score (MCS), which is a new index of patients' clinical status based on 34 CV and non-CV conditions (eg, heart failure, arrhythmia, cancer) derived from inpatient diagnostic information and outpatient drug prescriptions and weighted according to their strength with mortality. 23,24 Members in the statin discontinuing and maintaining groups were then 1:1 matched on their PS using a nearest neighbor matching algorithm without replacement with a caliper of 0.01. 25 Pairs in the statin discontinuing and maintaining groups accumulated PYs of follow-up from 180 days after the discontinuation date of the exposed member (ie, the starting point for patients in the maintaining group was set at 180 days after the discontinuation date of the paired discontinuing patient) until the clinical outcome of interest or censoring (emigration or end of data availability, ie, June 30, 2018) (eFigure 3 in the Supplement).…”

Development and validation of a clinical risk score to predict the risk of SARS-CoV-2 infection from administrative data: a population-based cohort study from Italy

“…Categorization was made by assigning increasing values of 1, 2, 3 and 4 to 0, 1-4, 5-9 and ≥10 drugs (comedication score) and 1, 2, 3 and 4 to 0, 1-2 and ≥3 comorbidities (comorbidity score). In addition, cases and controls were categorized according to the Multisource Comorbidity Score (MCS), a new index of patients' clinical status derived from inpatients diagnostic information and outpatient drug prescriptions provided by the regional Italian data and validated for outcome prediction [22,33]. To simplify comparisons, the original five categories of worsening clinical profile (0, 1, 2, 3 and 4) as defined by MCS, were reduced to milder (MCS=0), middle (1MCS3) and severe (MCS≥4) categories.…”