Budget Impact Analysis Principles of Good Practice: Report of the ISPOR 2012 Budget Impact Analysis Good Practice II Task Force
Budget Impact Analysis Principles of Good Practice: Report of the ISPOR 2012 Budget Impact Analysis Good Practice II Task Force
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DOI：
10.1016/j.jval.2013.08.2291
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发表时间：
2014-01-01
期刊：
影响因子：
4.5
通讯作者：
Shau, Wen-Yi
中科院分区：
文献类型：
--
作者：
Sullivan, Sean D.;Mauskopf, Josephine A.;Shau, Wen-Yi
背景：预算影响分析(BIAS)是卫生保健干预的全面经济评估的重要组成部分，越来越多的报销当局要求将其作为清单或报销提交的一部分。目标：本报告的目的是为那些进行这种分析或审查这种分析结果的人提供关于方法的最新指导。这一更新是必要的，部分原因是BIA方法的发展，以及人们对卫生保健干预措施的可负担性和人口健康影响的兴趣日益增长，特别是在新兴市场。方法：该工作组由国际药物经济学和结果研究协会健康科学政策理事会批准，并由其董事会任命。成员是BIAS的经验丰富的开发者或用户；在学术界和工业界工作，并担任政府顾问；来自北美和南美、大洋洲、亚洲和欧洲的几个国家。工作队征求了一个核心外部审查员小组以及更广泛地说，征求国际药物经济学和成果研究学会成员对草案的意见。结果：特别工作组建议，为新的卫生保健干预措施设计BIA时，应考虑到卫生保健系统的相关特点、可能的准入限制、对新干预措施的预期吸收以及当前和新干预措施的使用和效果。BIA的关键要素包括估计符合条件的人群的规模、目前的治疗组合和引入新干预措施后的预期组合、治疗组合的成本以及与病情相关的成本预期的变化。在可能的情况下，应使用简单的成本计算器方法进行BIA计算，因为它便于预算持有者使用。然而，在使用成本计算器方法不能可信地捕捉到符合条件的人群规模、疾病严重程度组合或治疗模式的变化的情况下，可以使用队列或患者水平的特定条件模型来估计新干预措施的预算影响，适当地考虑那些随着时间的推移进入和离开符合条件的人群。在任何一种情况下，BIA都应该使用反映特定决策者群体特定价值的数据。敏感性分析应该是从决策者的角度选择的备选方案。模型的验证至少应该包括与决策者的表面有效性和对计算的验证。BIA的数据来源应包括已发表的关于当前和新干预措施的有效性和安全性的临床试验评估和比较研究，以及可能的情况下其他参数估计的决策者自己的人群。其他数据来源包括使用已公布的数据、公认的地方或国家统计信息，以及在特殊情况下的专家意见。BIA的报告应提供有关输入参数值和计算的详细信息，其详细程度将允许另一建模师复制分析。BIA的结果应以卫生保健决策者感兴趣的格式提出。在计算机程序中，应该为不同类别的成本提供包括或排除在分析中的选项。结论：我们建议BIA的框架，提供数据获取和使用的指导，并提供将促进标准化和透明度的通用报告格式。遵守这些良好的研究实践原则并不一定会取代特定于司法管辖区的BIA指南，但可以支持和加强地方建议，或作为付款人希望公布方法指南的起点。
Background: Budget impact analyses (BIAs) are an essential part of a comprehensive economic assessment of a health care intervention and are increasingly required by reimbursement authorities as part of a listing or reimbursement submission. Objectives: The objective of this report was to present updated guidance on methods for those undertaking such analyses or for those reviewing the results of such analyses. This update was needed, in part, because of developments in BIA methods as well as a growing interest, particularly in emerging markets, in matters related to affordability and population health impacts of health care interventions. Methods: The Task Force was approved by the International Society for Pharmacoeconomics and Outcomes Research Health Sciences Policy Council and appointed by its Board of Directors. Members were experienced developers or users of BIAs; worked in academia and industry and as advisors to governments; and came from several countries in North America and South America, Oceania, Asia, and Europe. The Task Force solicited comments on the drafts from a core group of external reviewers and, more broadly, from the membership of the International Society for Pharmacoeconomics and Outcomes Research. Results: The Task Force recommends that the design of a BIA for a new health care intervention should take into account relevant features of the health care system, possible access restrictions, the anticipated uptake of the new intervention, and the use and effects of the current and new interventions. The key elements of a BIA include estimating the size of the eligible population, the current mix of treatments and the expected mix after the introduction of the new intervention, the cost of the treatment mixes, and any changes expected in condition-related costs. Where possible, the BIA calculations should be performed by using a simple cost calculator approach because of its ease of use for budget holders. In instances, however, in which the changes in eligible population size, disease severity mix, or treatment patterns cannot be credibly captured by using the cost calculator approach, a cohort or patient level condition-specific model may be used to estimate the budget impact of the new intervention, accounting appropriately for those entering and leaving the eligible population over time. In either case, the BIA should use data that reflect values specific to a particular decision maker's population. Sensitivity analysis should be of alternative scenarios chosen from the perspective of the decision maker. The validation of the model should include at least face validity with decision makers and verification of the calculations. Data sources for the BIA should include published clinical trial estimates and comparator studies for the efficacy and safety of the current and new interventions as well as the decision maker's own population for the other parameter estimates, where possible. Other data sources include the use of published data, well-recognized local or national statistical information, and, in special circumstances, expert opinion. Reporting of the BIA should provide detailed information about the input parameter values and calculations at a level of detail that would allow another modeler to replicate the analysis. The outcomes of the BIA should be presented in the format of interest to health care decision makers. In a computer program, options should be provided for different categories of costs to be included or excluded from the analysis.Conclusions: We recommend a framework for the BIA, provide guidance on the acquisition and use of data, and offer a common reporting format that will promote standardization and transparency. Adherence to these good research practice principles would not necessarily supersede jurisdiction-specific BIA guidelines but may support and enhance local recommendations or serve as a starting point for payers wishing to promulgate methodology guidelines.