An Algorithm for Incorporating Economic Evidence Into Clinical Practice Guidelines: Application to the Spanish Guideline for the Management of Chronic Primary Pain

Celia Muñoz, Patricia Gavín-Benavent, Silvia Moler-Zapata, Lucía Prieto Remón, María Bono Vega, Soledad Isern de Val, on behalf of GuíaSalud's Working Group on Incorporating Economic Evidence into CPGs
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Abstract

The importance of incorporating economic evidence (EE) such as resource use, cost or cost-effectiveness evidence into Clinical Practice Guidelines (CPG) is being increasingly recognised by decision makers, including healthcare providers and policy makers. Yet, this is a complex and resource-intensive process. EE can influence recommendations formulated about interventions in CPGs, especially when the desirable and undesirable effects are balanced. A group of methodologists, including health economists, in GuíaSalud (the organisation of the Spanish National Health System (NHS) that coordinates the national CPG Programme), has made important advances in the development of methodological guidance for how to develop evidence-based recommendations. In this article, we present an algorithm for informing decisions about incorporating EE in CPGs. The algorithm has three stages: (1) prioritise clinical questions in the CPG according to the influence that EE is expected to have on recommendations; (2) obtain EE for clinical questions that have been prioritised via a systematic review and/or a de novo economic evaluation; and (3) use EE to inform recommendations in CPG. We show how the algorithm was applied in the development of GuíaSalud's CPG for the management of chronic primary pain. In doing so, we provide specific guidance on how the algorithm could be applied using concrete examples. We show how this algorithm helps to make the process of incorporating EE into CPGs agile, dynamic and reproducible.

Abstract Image

将经济证据纳入临床实践指南的算法:应用于西班牙慢性原发性疼痛管理指南
将经济证据(EE),如资源利用、成本或成本效益证据纳入临床实践指南(CPG)的重要性正日益被决策者(包括医疗保健提供者和政策制定者)认识到。然而,这是一个复杂和资源密集的过程。情感表达可以影响关于cpg干预措施的建议,特别是当期望和不期望的效果达到平衡时。在GuíaSalud(西班牙国家卫生系统协调国家CPG方案的组织),包括卫生经济学家在内的一组方法学家在制定如何制定循证建议的方法指导方面取得了重要进展。在本文中,我们提出了一种算法,用于通知将EE纳入cpg的决策。该算法分为三个阶段:(1)根据预期情感表达对推荐的影响对CPG中的临床问题进行优先排序;(2)获得通过系统评价和/或重新进行经济评估优先考虑的临床问题的情感表达;(3)在CPG中使用情感表达来提供建议。我们展示了该算法如何应用于GuíaSalud的CPG开发中,用于慢性原发性疼痛的管理。在此过程中,我们提供了如何使用具体示例应用该算法的具体指导。我们将展示该算法如何帮助将EE纳入cpg的过程变得敏捷、动态和可重复。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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