Multimorbidity as a predictor of health service utilization in primary care: a registry-based study of the Catalan population

Abstract Background Multimorbidity is highly relevant for both service commissioning and clinical decision-making. Optimization of variables assessing multimorbidity in order to enhance chronic care management is an unmet need. To this end, we have explored the contribution of multimorbidity to pred...

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Main Authors: D. Monterde, E. Vela, M. Clèries, L. Garcia-Eroles, J. Roca, P. Pérez-Sust
Format: Article
Language:English
Published: BMC 2020-02-01
Series:BMC Family Practice
Subjects:
Online Access:http://link.springer.com/article/10.1186/s12875-020-01104-1
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spelling doaj-52fa2148ab904d08828974dc78b16a8e2020-11-25T03:12:00ZengBMCBMC Family Practice1471-22962020-02-012111910.1186/s12875-020-01104-1Multimorbidity as a predictor of health service utilization in primary care: a registry-based study of the Catalan populationD. Monterde0E. Vela1M. Clèries2L. Garcia-Eroles3J. Roca4P. Pérez-Sust5Sistemes d’Informació, Institut Català de la SalutUnitat d’informació i Coneixement, Servei Català de la SalutUnitat d’informació i Coneixement, Servei Català de la SalutGerència de Sistemes d’informació, Servei Català de la SalutHospital Clinic de Barcelona, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), CIBERES, Universitat de BarcelonaSistemes d’Informació, Institut Català de la SalutAbstract Background Multimorbidity is highly relevant for both service commissioning and clinical decision-making. Optimization of variables assessing multimorbidity in order to enhance chronic care management is an unmet need. To this end, we have explored the contribution of multimorbidity to predict use of healthcare resources at community level by comparing the predictive power of four different multimorbidity measures. Methods A population health study including all citizens ≥18 years (n = 6,102,595) living in Catalonia (ES) on 31 December 2014 was done using registry data. Primary care service utilization during 2015 was evaluated through four outcome variables: A) Frequent attendants, B) Home care users, C) Social worker users, and, D) Polypharmacy. Prediction of the four outcome variables (A to D) was carried out with and without multimorbidity assessment. We compared the contributions to model fitting of the following multimorbidity measures: i) Charlson index; ii) Number of chronic diseases; iii) Clinical Risk Groups (CRG); and iv) Adjusted Morbidity Groups (GMA). Results The discrimination of the models (AUC) increased by including multimorbidity as covariate into the models, namely: A) Frequent attendants (0.771 vs 0.853), B) Home care users (0.862 vs 0.890), C) Social worker users (0.809 vs 0.872), and, D) Polypharmacy (0.835 vs 0.912). GMA showed the highest predictive power for all outcomes except for polypharmacy where it was slightly below than CRG. Conclusions We confirmed that multimorbidity assessment enhanced prediction of use of healthcare resources at community level. The Catalan population-based risk assessment tool based on GMA presented the best combination of predictive power and applicability.http://link.springer.com/article/10.1186/s12875-020-01104-1Chronic careComorbidityPrimary careHealth service utilizationRisk assessment
collection DOAJ
language English
format Article
sources DOAJ
author D. Monterde
E. Vela
M. Clèries
L. Garcia-Eroles
J. Roca
P. Pérez-Sust
spellingShingle D. Monterde
E. Vela
M. Clèries
L. Garcia-Eroles
J. Roca
P. Pérez-Sust
Multimorbidity as a predictor of health service utilization in primary care: a registry-based study of the Catalan population
BMC Family Practice
Chronic care
Comorbidity
Primary care
Health service utilization
Risk assessment
author_facet D. Monterde
E. Vela
M. Clèries
L. Garcia-Eroles
J. Roca
P. Pérez-Sust
author_sort D. Monterde
title Multimorbidity as a predictor of health service utilization in primary care: a registry-based study of the Catalan population
title_short Multimorbidity as a predictor of health service utilization in primary care: a registry-based study of the Catalan population
title_full Multimorbidity as a predictor of health service utilization in primary care: a registry-based study of the Catalan population
title_fullStr Multimorbidity as a predictor of health service utilization in primary care: a registry-based study of the Catalan population
title_full_unstemmed Multimorbidity as a predictor of health service utilization in primary care: a registry-based study of the Catalan population
title_sort multimorbidity as a predictor of health service utilization in primary care: a registry-based study of the catalan population
publisher BMC
series BMC Family Practice
issn 1471-2296
publishDate 2020-02-01
description Abstract Background Multimorbidity is highly relevant for both service commissioning and clinical decision-making. Optimization of variables assessing multimorbidity in order to enhance chronic care management is an unmet need. To this end, we have explored the contribution of multimorbidity to predict use of healthcare resources at community level by comparing the predictive power of four different multimorbidity measures. Methods A population health study including all citizens ≥18 years (n = 6,102,595) living in Catalonia (ES) on 31 December 2014 was done using registry data. Primary care service utilization during 2015 was evaluated through four outcome variables: A) Frequent attendants, B) Home care users, C) Social worker users, and, D) Polypharmacy. Prediction of the four outcome variables (A to D) was carried out with and without multimorbidity assessment. We compared the contributions to model fitting of the following multimorbidity measures: i) Charlson index; ii) Number of chronic diseases; iii) Clinical Risk Groups (CRG); and iv) Adjusted Morbidity Groups (GMA). Results The discrimination of the models (AUC) increased by including multimorbidity as covariate into the models, namely: A) Frequent attendants (0.771 vs 0.853), B) Home care users (0.862 vs 0.890), C) Social worker users (0.809 vs 0.872), and, D) Polypharmacy (0.835 vs 0.912). GMA showed the highest predictive power for all outcomes except for polypharmacy where it was slightly below than CRG. Conclusions We confirmed that multimorbidity assessment enhanced prediction of use of healthcare resources at community level. The Catalan population-based risk assessment tool based on GMA presented the best combination of predictive power and applicability.
topic Chronic care
Comorbidity
Primary care
Health service utilization
Risk assessment
url http://link.springer.com/article/10.1186/s12875-020-01104-1
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