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首页> 外文期刊>Value in health: the journal of the International Society for Pharmacoeconomics and Outcomes Research >Budget impact analysis - Principles of good practice: Report of the ISPOR 2012 budget impact analysis good practice II task force
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Budget impact analysis - Principles of good practice: Report of the ISPOR 2012 budget impact analysis good practice II task force

机译:良好的预算影响分析——原则实践:ISPOR 2012年预算报告的影响良好的实践分析II特遣部队

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摘要

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.
机译:背景(偏见)是一个预算影响分析全面经济的重要组成部分评估医疗干预和的越来越需要报销当局的清单或报销提交。报告显示更新的指导方法对于那些或进行这样的分析审查的结果分析。需要更新,在某种程度上,因为BIA的发展以及不断增长的方法兴趣,尤其是在新兴市场,能力和人口有关的事物健康的影响卫生保健干预措施。工作组是批准的方法国际药物经济学和社会结果研究健康科学政策委员会并由其董事会任命。有经验的开发人员或用户的偏见;在学术界和产业界和顾问工作政府;在北美洲和南美洲,大洋洲,亚洲和欧洲。评论草稿的核心组审稿人,更广泛地说,从国际社会的成员药物经济学和结果的研究。工作组建议的设计BIA新卫生保健干预考虑到健康的相关特征保健系统,可能的访问限制预期的吸收新的干预,当前的使用和效果干预措施。估算的尺寸合格的人口,目前的治疗方法和预期混合后的引入新的干预,治疗混合的成本,并在与预期的任何更改成本。应该由使用一个简单的成本计算器的方法由于其易用性预算持有人。合格的人口规模的变化,疾病严重程度,或治疗模式使用成本不能可靠地捕捉到计算器的方法,一个队列或患者的立场condition-specific模型可用于估计的预算影响新的干预,这些进入和适当的会计离开人口随着时间的资格。这两种情况下,反映BIA应该使用数据特定于特定决策者的价值观人口。替代方案选择的视角的决策者。模型应该至少包括表面效度决策者和验证的计算。包括临床试验评估和公布比较研究的疗效和安全性当前和新干预措施以及其他决策者的人口参数估计,在可能的情况下。包括使用公布的数据来源,公认当地或国家的统计信息,在特殊情况下,专家的意见。提供详细的信息输入参数值和计算水平细节会让另一个modeler复制的分析。应该在感兴趣的格式医疗决策者。项目,应提供不同的选项类别的成本中包含或排除从分析。BIA框架,提供指导获取和使用的数据,并提供一个共同的报告格式,将促进标准化和透明度。这些良好的研究实践原则不会必然取代jurisdiction-specific BIA但可能支持,提高当地的指导方针建议或作为一个起点纳税人希望传播方法指导方针。

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