Evidence map›Paper›PMID 27084274›Full record

ArticleBMJ open2016

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 and 17 more

Abstract read
In one paragraph

Article in BMJ open, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

44 citing papers in PubMed.

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  14. Adjusted Morbidity Groups and Intracerebral Haemorrhage: A Retrospective Primary Care Cohort Study.International journal of environmental research and public health · 2021
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

27 authors.

Ivan Dueñas-EspínHospital Clinic de Barcelona, Institut d'Investigacions Biomèdiques August Pii Sunyer (IDIBAPS), CIBERES, Universitat de Barcelona, Barcelona, Spain Centre for Research in Environmental Epidemiology (CREAL), Universitat Pompeu Fabra, CIBER en Epidemiologia y Salud Pública (CIBERESP), Barcelona, Spain.
Emili VelaCatSalut, Servei Català de la Salut, Barcelona, Catalonia, Spain.
Steffen PauwsRoyal Philips Netherlands BV acting through Philips Research, Eindhoven, The Netherlands.
Cristina BescosRoyal Philips Netherlands BV acting through Philips Homecare, Boeblingen, Germany.
Isaac CanoHospital Clinic de Barcelona, Institut d'Investigacions Biomèdiques August Pii Sunyer (IDIBAPS), CIBERES, Universitat de Barcelona, Barcelona, Spain.
Montserrat CleriesCatSalut, Servei Català de la Salut, Barcelona, Catalonia, Spain.
Joan Carles ContelDepartament de Salut, Generalitat de Catalunya, Barcelona, Catalonia, Spain.
Esteban de Manuel KeenoyKronikgune-Centro de Investigación en Cronicidad, Basque Country, Bilbao, Spain.
Judith Garcia-AymerichCentre for Research in Environmental Epidemiology (CREAL), Universitat Pompeu Fabra, CIBER en Epidemiologia y Salud Pública (CIBERESP), Barcelona, Spain.
David Gomez-CabreroDepartment of Medicine, Karolinska Institute, Stockholm, Sweden.
Rachelle KayeMaccabi Health Services, Tel Aviv, Israel.
Maarten M H LahrDepartment of Epidemiology, Health Technology Assessment, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
Magí Lluch-ArietEurecat, Barcelona, Catalonia, Spain Networking Department, Technical University of Catalonia (UPC), Barcelona, Spain.
Montserrat MoharraAgència de Qualitat i Avaluació Sanitàries de Catalunya (AQuAS), Barcelona, Catalonia, Spain.
David MonterdeInstitut Català de la Salut, Barcelona, Catalonia, Spain.
Joana MoraKronikgune-Centro de Investigación en Cronicidad, Basque Country, Bilbao, Spain.
Marco NalinTelbios (TLB), Milan, Italy.
Andrea PavlickovaNHS 24, Scottish Centre for Telehealth and Telecare (SCTT), Edinburgh, UK.
Jordi PieraBadalona Serveis Assistencials (BSA), Badalona, Catalonia, Spain.
Sara PonceKronikgune-Centro de Investigación en Cronicidad, Basque Country, Bilbao, Spain.
Sebastià SantaeugeniaBadalona Serveis Assistencials (BSA), Badalona, Catalonia, Spain.
Helen SchonenbergRoyal Philips Netherlands BV acting through Philips Homecare, Boeblingen, Germany.
Stefan StörkComprehensive Heart Failure Center (CHFC), Universität Würsburg, Würsburg, Germany.
Jesper TegnerDepartment of Medicine, Karolinska Institute, Stockholm, Sweden.
Filip VelickovskiEurecat, Barcelona, Catalonia, Spain ViCOROB, Universitat de Girona, Girona, Spain.
Christoph WesterteicherRoyal Philips Netherlands BV acting through Philips Homecare, Boeblingen, Germany.
Josep RocaHospital Clinic de Barcelona, Institut d'Investigacions Biomèdiques August Pii Sunyer (IDIBAPS), CIBERES, Universitat de Barcelona, Barcelona, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesPopulation-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).

participantsResponsible 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.

resultsThere 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.

conclusionsThe 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.

Indexed as

Delivery of Health Care, IntegratedEuropeHealth Status IndicatorsHumansPopulation SurveillanceProspective StudiesRisk Assessmentcase findingchronic careclinical decision makingHealth risk assessmentPatient stratification

Identifiers

PMID27084274
PMCPMC4838738

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.