Author(s): Nicolau, Leonor Bacelar ; Rodrigues, Teresa ; Fernandes, Elisabete ; Lobo, Mariana F. ; Nisa, Cláudia Fernandes ; Azzone, Vanessa ; Pinto, Armando Teixeira ; Pereira, Altamiro Costa ; Normand, Sharon-Lise Teresa ; Miguel, José Pereira
Date: 2017
Persistent ID: http://hdl.handle.net/10451/29665
Origin: Repositório da Universidade de Lisboa
Subject(s): Equity; Quantification; Decision-making; Big data; Data science; Acute myocardial infarction
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.
