Andermann Anne, Pang Tikki, Newton John N, Davis Adrian, Panisset Ulysses
Department of Family Medicine and Department of Epidemiology, Biostatistics and Occupational Health, Faculty of Medicine, McGill University, Montreal, Canada.
Lee Kuan Yew School of Public Policy, National University of Singapore, Singapore, Singapore.
Health Res Policy Syst. 2016 Mar 14;14:16. doi: 10.1186/s12961-016-0085-4.
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.
采用系统的方法有助于做出基于证据的决策,以改善个人或人群的健康状况。虽然已经存在许多算法,而且对于总结或排列做出此类与健康相关决策应涉及的各种要素,没有单一的“正确”方法,但本文提出了一种算法,该算法列出了许多应考虑的关键问题,并特别强调平衡个体患者和整个人群的价值观,以及纳入背景因素的重要性。事实上,在决策过程中需要许多不同类型的证据和价值判断来回答一系列广泛的问题,包括:(1)首要的健康问题是什么?(2)导致这个健康问题的原因是什么?(3)可以用来解决这个健康问题的不同策略或干预措施有哪些?(4)与现状相比,这些选项中哪一个的附加益处超过危害?(5)所涉及的个人或人群会接受哪些选项?(6)成本和机会成本是多少?(7)在这种特定背景下,这些选项是否可行和可持续?(8)选择一个选项而非另一个选项的伦理、法律和社会影响是什么?(9)不同的利益相关者从每个选项中可能获得或失去什么?以及(10)考虑到所涉及的多个观点和因素,哪一个选项最有可能在将危害降至最低的同时改善健康?“健康证据”系列的这第三篇也是最后一篇文章将更详细地介绍该算法中的每一个步骤,以促进做出更多旨在改善健康和减少不平等的基于证据的决策。