Developing and validating a novel multisource comorbidity score from administrative data: a large population-based cohort study from Italy

Giovanni Corrao, Federico Rea, Mirko Di Martino, Rossana De Palma, Salvatore Scondotto, Danilo Fusco, Adele Lallo, Laura Maria Beatrice Belotti, Mauro Ferrante, Sebastiano Pollina Addario, Luca Merlino, Giuseppe Mancia, Flavia Carle, Giovanni Corrao, Federico Rea, Mirko Di Martino, Rossana De Palma, Salvatore Scondotto, Danilo Fusco, Adele Lallo, Laura Maria Beatrice Belotti, Mauro Ferrante, Sebastiano Pollina Addario, Luca Merlino, Giuseppe Mancia, Flavia Carle

Abstract

Objective: To 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.

Methods: An 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.

Results: Primary 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.

Conclusion: MCS 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.

Keywords: administrative database; comorbidity; prognostic score; record linkage.

Conflict of interest statement

Competing interests: GC received research support from the European Community (EC), the Italian Agency of Drug (AIFA) and the Italian Ministry of Education, University and Research (MIUR). GC took part in a variety of projects that were funded by pharmaceutical companies (ie, Novartis, GSK, Roche, AMGEN, BMS). GC also received honoraria as member of Advisory Board from Roche.

© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Figures

Figure 1
Figure 1
Multisource comorbidity score distribution among National Health System (NHS) beneficiaries (internal validation set) according to their gender and age category.
Figure 2
Figure 2
Receiver operating characteristic (ROC) curves comparing discriminant power of multisource comorbidity score (MCS), Charlson Comorbidity Index (CCI), Elixhauser Index (EI) and Chronic Disease Score (CDS) in predicting 1-year survival among National Health System (NHS) beneficiaries (internal validation set).
Figure 3
Figure 3
Receiver operating characteristic (ROC) curves comparing discriminant power of multisource comorbidity score (MCS) in predicting 1-year survival in four Italian regions (internal and external validation sets).
Figure 4
Figure 4
One-year Kaplan-Meier survival curves according to the value of the multisource comorbidity score (MCS) in four Italian regions (internal and external validation sets).
Figure 5
Figure 5
Five-year mortality, and hospital admissions and hospital cost annual rates according to the value of the multisource comorbidity score (MCS) of National Health System (NHS) beneficiaries (internal validation set). PY, person-years.

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