Proposals for enhanced health risk assessment and stratification in an integrated care scenario

Ivan Dueñas-Espín, Emili Vela, Steffen Pauws, Cristina Bescos, Isaac Cano, Montserrat Cleries, Joan Carles Contel, Esteban de Manuel Keenoy, Judith Garcia-Aymerich, David Gomez-Cabrero, Rachelle Kaye, Maarten M H Lahr, Magí Lluch-Ariet, Montserrat Moharra, David Monterde, Joana Mora, Marco Nalin, Andrea Pavlickova, Jordi Piera, Sara Ponce & 7 others Sebastià Santaeugenia, Helen Schonenberg, Stefan Störk, Jesper Tegner, Filip Velickovski, Christoph Westerteicher, Josep Roca

Research output: Contribution to journalArticleScientificpeer-review

Abstract

OBJECTIVES: Population-based health risk assessment and stratification are considered highly relevant for large-scale implementation of integrated care by facilitating services design and case identification. The principal objective of the study was to analyse five health-risk assessment strategies and health indicators used in the five regions participating in the Advancing Care Coordination and Telehealth Deployment (ACT) programme (http://www.act-programme.eu). The second purpose was to elaborate on strategies toward enhanced health risk predictive modelling in the clinical scenario.

SETTINGS: The five ACT regions: Scotland (UK), Basque Country (ES), Catalonia (ES), Lombardy (I) and Groningen (NL).

PARTICIPANTS: Responsible teams for regional data management in the five ACT regions.

PRIMARY AND SECONDARY OUTCOME MEASURES: We characterised and compared risk assessment strategies among ACT regions by analysing operational health risk predictive modelling tools for population-based stratification, as well as available health indicators at regional level. The analysis of the risk assessment tool deployed in Catalonia in 2015 (GMAs, Adjusted Morbidity Groups) was used as a basis to propose how population-based analytics could contribute to clinical risk prediction.

RESULTS: There was consensus on the need for a population health approach to generate health risk predictive modelling. However, this strategy was fully in place only in two ACT regions: Basque Country and Catalonia. We found marked differences among regions in health risk predictive modelling tools and health indicators, and identified key factors constraining their comparability. The research proposes means to overcome current limitations and the use of population-based health risk prediction for enhanced clinical risk assessment.

CONCLUSIONS: The results indicate the need for further efforts to improve both comparability and flexibility of current population-based health risk predictive modelling approaches. Applicability and impact of the proposals for enhanced clinical risk assessment require prospective evaluation.

Original languageEnglish
Pages (from-to)e010301
JournalBMJ Open
Volume6
Issue number4
DOIs
Publication statusPublished - 15 Apr 2016

Keywords

  • Delivery of Health Care, Integrated
  • Europe
  • Health Status Indicators
  • Humans
  • Population Surveillance
  • Prospective Studies
  • Risk Assessment
  • Journal Article
  • Research Support, Non-U.S. Gov't

Cite this

Dueñas-Espín, I., Vela, E., Pauws, S., Bescos, C., Cano, I., Cleries, M., ... Roca, J. (2016). Proposals for enhanced health risk assessment and stratification in an integrated care scenario. BMJ Open, 6(4), e010301. https://doi.org/10.1136/bmjopen-2015-010301
Dueñas-Espín, Ivan ; Vela, Emili ; Pauws, Steffen ; Bescos, Cristina ; Cano, Isaac ; Cleries, Montserrat ; Contel, Joan Carles ; de Manuel Keenoy, Esteban ; Garcia-Aymerich, Judith ; Gomez-Cabrero, David ; Kaye, Rachelle ; Lahr, Maarten M H ; Lluch-Ariet, Magí ; Moharra, Montserrat ; Monterde, David ; Mora, Joana ; Nalin, Marco ; Pavlickova, Andrea ; Piera, Jordi ; Ponce, Sara ; Santaeugenia, Sebastià ; Schonenberg, Helen ; Störk, Stefan ; Tegner, Jesper ; Velickovski, Filip ; Westerteicher, Christoph ; Roca, Josep. / Proposals for enhanced health risk assessment and stratification in an integrated care scenario. In: BMJ Open. 2016 ; Vol. 6, No. 4. pp. e010301.
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Dueñas-Espín, I, Vela, E, Pauws, S, Bescos, C, Cano, I, Cleries, M, Contel, JC, de Manuel Keenoy, E, Garcia-Aymerich, J, Gomez-Cabrero, D, Kaye, R, Lahr, MMH, Lluch-Ariet, M, Moharra, M, Monterde, D, Mora, J, Nalin, M, Pavlickova, A, Piera, J, Ponce, S, Santaeugenia, S, Schonenberg, H, Störk, S, Tegner, J, Velickovski, F, Westerteicher, C & Roca, J 2016, 'Proposals for enhanced health risk assessment and stratification in an integrated care scenario', BMJ Open, vol. 6, no. 4, pp. e010301. https://doi.org/10.1136/bmjopen-2015-010301

Proposals for enhanced health risk assessment and stratification in an integrated care scenario. / Dueñas-Espín, Ivan; Vela, Emili; Pauws, Steffen; Bescos, Cristina; Cano, Isaac; Cleries, Montserrat; Contel, Joan Carles; de Manuel Keenoy, Esteban; Garcia-Aymerich, Judith; Gomez-Cabrero, David; Kaye, Rachelle; Lahr, Maarten M H; Lluch-Ariet, Magí; Moharra, Montserrat; Monterde, David; Mora, Joana; Nalin, Marco; Pavlickova, Andrea; Piera, Jordi; Ponce, Sara; Santaeugenia, Sebastià; Schonenberg, Helen; Störk, Stefan; Tegner, Jesper; Velickovski, Filip; Westerteicher, Christoph; Roca, Josep.

In: BMJ Open, Vol. 6, No. 4, 15.04.2016, p. e010301.

Research output: Contribution to journalArticleScientificpeer-review

TY - JOUR

T1 - Proposals for enhanced health risk assessment and stratification in an integrated care scenario

AU - Dueñas-Espín, Ivan

AU - Vela, Emili

AU - Pauws, Steffen

AU - Bescos, Cristina

AU - Cano, Isaac

AU - Cleries, Montserrat

AU - Contel, Joan Carles

AU - de Manuel Keenoy, Esteban

AU - Garcia-Aymerich, Judith

AU - Gomez-Cabrero, David

AU - Kaye, Rachelle

AU - Lahr, Maarten M H

AU - Lluch-Ariet, Magí

AU - Moharra, Montserrat

AU - Monterde, David

AU - Mora, Joana

AU - Nalin, Marco

AU - Pavlickova, Andrea

AU - Piera, Jordi

AU - Ponce, Sara

AU - Santaeugenia, Sebastià

AU - Schonenberg, Helen

AU - Störk, Stefan

AU - Tegner, Jesper

AU - Velickovski, Filip

AU - Westerteicher, Christoph

AU - Roca, Josep

N1 - Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

PY - 2016/4/15

Y1 - 2016/4/15

N2 - OBJECTIVES: Population-based health risk assessment and stratification are considered highly relevant for large-scale implementation of integrated care by facilitating services design and case identification. The principal objective of the study was to analyse five health-risk assessment strategies and health indicators used in the five regions participating in the Advancing Care Coordination and Telehealth Deployment (ACT) programme (http://www.act-programme.eu). The second purpose was to elaborate on strategies toward enhanced health risk predictive modelling in the clinical scenario.SETTINGS: The five ACT regions: Scotland (UK), Basque Country (ES), Catalonia (ES), Lombardy (I) and Groningen (NL).PARTICIPANTS: Responsible teams for regional data management in the five ACT regions.PRIMARY AND SECONDARY OUTCOME MEASURES: We characterised and compared risk assessment strategies among ACT regions by analysing operational health risk predictive modelling tools for population-based stratification, as well as available health indicators at regional level. The analysis of the risk assessment tool deployed in Catalonia in 2015 (GMAs, Adjusted Morbidity Groups) was used as a basis to propose how population-based analytics could contribute to clinical risk prediction.RESULTS: There was consensus on the need for a population health approach to generate health risk predictive modelling. However, this strategy was fully in place only in two ACT regions: Basque Country and Catalonia. We found marked differences among regions in health risk predictive modelling tools and health indicators, and identified key factors constraining their comparability. The research proposes means to overcome current limitations and the use of population-based health risk prediction for enhanced clinical risk assessment.CONCLUSIONS: The results indicate the need for further efforts to improve both comparability and flexibility of current population-based health risk predictive modelling approaches. Applicability and impact of the proposals for enhanced clinical risk assessment require prospective evaluation.

AB - OBJECTIVES: Population-based health risk assessment and stratification are considered highly relevant for large-scale implementation of integrated care by facilitating services design and case identification. The principal objective of the study was to analyse five health-risk assessment strategies and health indicators used in the five regions participating in the Advancing Care Coordination and Telehealth Deployment (ACT) programme (http://www.act-programme.eu). The second purpose was to elaborate on strategies toward enhanced health risk predictive modelling in the clinical scenario.SETTINGS: The five ACT regions: Scotland (UK), Basque Country (ES), Catalonia (ES), Lombardy (I) and Groningen (NL).PARTICIPANTS: Responsible teams for regional data management in the five ACT regions.PRIMARY AND SECONDARY OUTCOME MEASURES: We characterised and compared risk assessment strategies among ACT regions by analysing operational health risk predictive modelling tools for population-based stratification, as well as available health indicators at regional level. The analysis of the risk assessment tool deployed in Catalonia in 2015 (GMAs, Adjusted Morbidity Groups) was used as a basis to propose how population-based analytics could contribute to clinical risk prediction.RESULTS: There was consensus on the need for a population health approach to generate health risk predictive modelling. However, this strategy was fully in place only in two ACT regions: Basque Country and Catalonia. We found marked differences among regions in health risk predictive modelling tools and health indicators, and identified key factors constraining their comparability. The research proposes means to overcome current limitations and the use of population-based health risk prediction for enhanced clinical risk assessment.CONCLUSIONS: The results indicate the need for further efforts to improve both comparability and flexibility of current population-based health risk predictive modelling approaches. Applicability and impact of the proposals for enhanced clinical risk assessment require prospective evaluation.

KW - Delivery of Health Care, Integrated

KW - Europe

KW - Health Status Indicators

KW - Humans

KW - Population Surveillance

KW - Prospective Studies

KW - Risk Assessment

KW - Journal Article

KW - Research Support, Non-U.S. Gov't

U2 - 10.1136/bmjopen-2015-010301

DO - 10.1136/bmjopen-2015-010301

M3 - Article

VL - 6

SP - e010301

JO - BMJ Open

JF - BMJ Open

SN - 2044-6055

IS - 4

ER -