title: Evidence for Health III: Making evidence-informed decisions that integrate values and context.
abstract: Making evidence-informed decisions with the aim of improving the health of individuals or populations can be facilitated by using a systematic approach. While a number of algorithms already exist, and while there is no single 'right' way of summarizing or ordering the various elements that should be involved in making such health-related decisions, an algorithm is presented here that lays out many of the key issues that should be considered, and which adds a special emphasis on balancing the values of individual patients and entire populations, as well as the importance of incorporating contextual considerations. Indeed many different types of evidence and value judgements are needed during the decision-making process to answer a wide range of questions, including (1) What is the priority health problem? (2) What causes this health problem? (3) What are the different strategies or interventions that can be used to address this health problem? (4) Which of these options, as compared to the status quo, has an added benefit that outweighs the harms? (5) Which options would be acceptable to the individuals or populations involved? (6) What are the costs and opportunity costs? (7) Would these options be feasible and sustainable in this specific context? (8) What are the ethical, legal and social implications of choosing one option over another? (9) What do different stakeholders stand to gain or lose from each option? and (10) Taking into account the multiple perspectives and considerations involved, which option is most likely to improve health while minimizing harms? This third and final article in the 'Evidence for Health' series will go through each of the steps in the algorithm in greater detail to promote more evidence-informed decisions that aim to improve health and reduce inequities.
authors.affiliation: Department of Family Medicine and Department of Epidemiology, Biostatistics and Occupational Health, Faculty of Medicine, McGill University, Montreal, Canada. anne.andermann@mail.mcgill.ca.
authors.forename: Anne
authors.initials: A
authors.lastname: Andermann
authors.affiliation: Lee Kuan Yew School of Public Policy, National University of Singapore, Singapore, Singapore.
authors.forename: Tikki
authors.initials: T
authors.lastname: Pang
authors.affiliation: Institute of Population Health, Faculty of Medical and Human Sciences, University of Manchester, Manchester, England.
authors.forename: John N
authors.initials: JN
authors.lastname: Newton
authors.affiliation: Public Health England, London, England.
authors.forename: Adrian
authors.initials: A
authors.lastname: Davis
authors.affiliation: Department of Preventive and Social Medicine-Health Policy, Faculty of Medicine, Federal University of Minas Gerais, Belo Horizonte, Brazil.|Evidence Informed Policy Network (EVIPNet) Steering Group, World Health Organization, Geneva, Switzerland.
authors.forename: Ulysses
authors.initials: U
authors.lastname: Panisset
mesh_terms: D003299:Cooperative Behavior; D003657:Decision Making; D019317:Evidence-Based Medicine / Q000458:organization & administration*; D006292:Health Priorities; D054624:Health Status Disparities; D006801:Humans; D033181:Information Dissemination; D012107:Research Design; D057170:Translational Research, Biomedical
keywords: Decision-making; Evidence-based medicine; Health equity; Health outcomes; Health policy; Public health; Research