TY - JOUR
T1 - Picturing inequities for health impact assessment
T2 - linked electronic records, mortality and regional disparities in Portugal
AU - Bacelar-Nicolau, Leonor
AU - Rodrigues, Teresa
AU - Fernandes, Elisabete
AU - Lobo, Mariana F.
AU - Nisa, Cláudia Fernandes
AU - Azzone, Vanessa
AU - Teixeira-Pinto, Armando
AU - Costa-Pereira, Altamiro
AU - Normand, Sharon Lise Teresa
AU - Pereira Miguel, José
N1 - Publisher Copyright:
© 2017 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
PY - 2018/1/2
Y1 - 2018/1/2
N2 - Health 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.
AB - Health 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.
KW - acute myocardial infarction
KW - Big Data
KW - data science
KW - decision-making
KW - Equity
KW - quantification
UR - http://www.scopus.com/inward/record.url?scp=85033232612&partnerID=8YFLogxK
U2 - 10.1080/14615517.2017.1364016
DO - 10.1080/14615517.2017.1364016
M3 - Article
AN - SCOPUS:85033232612
SN - 1461-5517
VL - 36
SP - 90
EP - 104
JO - Impact Assessment and Project Appraisal
JF - Impact Assessment and Project Appraisal
IS - 1
ER -