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Picturing inequities for health impact assessment : linked electronic records, mortality and regional disparities in Portugal

dc.contributor.authorNicolau, Leonor Bacelar
dc.contributor.authorRodrigues, Teresa
dc.contributor.authorFernandes, Elisabete
dc.contributor.authorLobo, Mariana F.
dc.contributor.authorNisa, Cláudia Fernandes
dc.contributor.authorAzzone, Vanessa
dc.contributor.authorPinto, Armando Teixeira
dc.contributor.authorPereira, Altamiro Costa
dc.contributor.authorNormand, Sharon-Lise Teresa
dc.contributor.authorMiguel, José Pereira
dc.date.accessioned2017-11-09T11:31:00Z
dc.date.available2017-11-09T11:31:00Z
dc.date.issued2017
dc.description© 2017 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Grouppt_PT
dc.description.abstractHealth impact assessment (HIA) focuses on minimizing inequities when studying the effects of a policy on the population’s health. Nevertheless, it is seldom simultaneously quantified, multivariate, and visually graphically comprehensible for non-statisticians. This paper aims to address that gap, assessing a policy promoting the quality of Electronic Health Records, linking hospital and primary health care data (Blood Pressure, Cholesterol, Triglycerides, Waist Circumference, Body Mass Index) to mortality outcomes and regional inequities. Acute Myocardial Infarction patients admitted in the hospital are then followed regularly in Portuguese NHS Primary Care. Regional disparities regarding recorded information are observed and different association patterns with mortality identified, ranked, and visualized through adjusted ORs for sex, age, and indicators of severity of hospital admission, complemented with multivariate correspondence analysis. A pathway to handling equity within quantitative HIA shows that complexity in data and methods may generate simplicity and clarity through visual graphical aids. Tackling Big Data with Data Science in HIA may even be at the center of future health reforms, assessing impacts of health promotion and chronic disease policies.pt_PT
dc.description.sponsorshipThis work was partially supported by the CUTEHeart Project – Comparative Use of Technologies for Coronary Heart Disease, funded by FCT, QREN, COMPETE [grant number HMSP-ICT/0013/2011] (http://cuteheart.med.up.pt).pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationImpact Assessment and Project Appraisal, 2018 VOL. 36, NO. 1, 90–104pt_PT
dc.identifier.doi10.1080/14615517.2017.1364016pt_PT
dc.identifier.issn1471-5465
dc.identifier.urihttp://hdl.handle.net/10451/29665
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherTaylor & Francispt_PT
dc.relation.publisherversionhttp://www.tandfonline.com/loi/tiap20pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/pt_PT
dc.subjectEquitypt_PT
dc.subjectQuantificationpt_PT
dc.subjectDecision-makingpt_PT
dc.subjectBig datapt_PT
dc.subjectData sciencept_PT
dc.subjectAcute myocardial infarctionpt_PT
dc.titlePicturing inequities for health impact assessment : linked electronic records, mortality and regional disparities in Portugalpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/3599-PPCDT/HMSP-ICT%2F0013%2F2011/PT
oaire.citation.endPage104pt_PT
oaire.citation.issue1pt_PT
oaire.citation.startPage90pt_PT
oaire.citation.titleImpact Assessment and Project Appraisalpt_PT
oaire.citation.volume36pt_PT
oaire.fundingStream3599-PPCDT
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isProjectOfPublication677c3133-fe93-4742-a034-1a85182a645d
relation.isProjectOfPublication.latestForDiscovery677c3133-fe93-4742-a034-1a85182a645d

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