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本文引用的文献

1
Use of real-world evidence in economic assessments of pharmaceuticals in the United States.在美国,药品经济评估中真实世界证据的应用。
J Manag Care Spec Pharm. 2021 Jan;27(1):5-14. doi: 10.18553/jmcp.2021.27.1.005.
2
Preapproval Information Exchange: Perspectives of U.S. Population Health Decision Makers on Preferences for Early Engagement with Investigational Therapies.预审批信息交流:美国人口健康决策制定者对早期参与试验性治疗偏好的观点。
J Manag Care Spec Pharm. 2019 Feb;25(2):164-173. doi: 10.18553/jmcp.2019.25.2.164.
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A Methodological Review of US Budget-Impact Models for New Drugs.美国新药预算影响模型的方法学综述
Pharmacoeconomics. 2016 Nov;34(11):1111-1131. doi: 10.1007/s40273-016-0426-8.
4
Questionnaire to assess relevance and credibility of modeling studies for informing health care decision making: an ISPOR-AMCP-NPC Good Practice Task Force report.评估建模研究在为医疗保健决策提供信息方面的相关性和可信度的调查问卷:ISPOR-AMCP-NPC 良好实践工作组报告。
Value Health. 2014 Mar;17(2):174-82. doi: 10.1016/j.jval.2014.01.003.

支付方对经济模型在肿瘤决策中的使用的看法。

Payer perceptions on the use of economic models in oncology decision making.

机构信息

College of Pharmacy, University of Utah, Salt Lake City.

Pfizer, Inc., Collegeville, PA.

出版信息

J Manag Care Spec Pharm. 2021 Nov;27(11):1560-1567. doi: 10.18553/jmcp.2021.27.11.1560.

DOI:10.18553/jmcp.2021.27.11.1560
PMID:34714111
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10390914/
Abstract

To support oncology formulary decisions, especially with accelerated regulatory approvals and niche populations, payers desire data beyond what regulators review. Economic models showing financial impact of treatments may help, but data on payers' use of economic models in oncology are limited. To assess payer perceptions regarding use of economic models in informing oncology formulary decisions. A multidisciplinary steering committee involving health economists and payers developed a survey containing singleanswer, multiple-answer, and free-response questions. The pilot survey was tested at a mini-advisory board with 5 US payers and revised based on feedback. In February 2020, the survey was distributed to 221 US payers through the AMCP Market Insights program and 10 additional payer panelists, who were invited to discuss survey results. Results were presented primarily as frequencies of responses and evaluated by plan size, type of health plan, and geography (regional vs national). Differences in categorical data responses were compared using Pearson chi-square or Fisher's exact tests. Two-tailed values were reported and an alpha level of 0.05 or less was used to indicate statistical significance. Overall, 106 of 231 payers completed the survey (45.9%); 45.5% represented small plans (< 1 million lives), and 54.5% represented large plans (≥ 1 million lives). Respondents were largely pharmacists (89.9%), and 55.6% indicated that their job was pharmacy administrator. Payers indicated moderate/most interest in cost-effectiveness models (CEMs; 85.3%) and budget impact models (BIMs; 80.4%). Overall, 51.6% of respondents claimed oncology expertise on their pharmacy and therapeutics committees. Large plans were more likely to have expertise in reviewing oncology economic models than small plans (55.6% vs 31.1%, = 0.015). The most common reasons for not reviewing economic models included "not available at time of review" (44.1%) and "potential bias" (38.2%). Overall, 43.1% of payers conduct analyses using their own data after reviewing a manufacturer-sponsored economic model. To inform formulary decisions, 62.7% of payers use BIMs and 66.7% use CEMs sometimes, often, or always. When comparing therapies with similar safety/efficacy profiles, 68.6% of payers reported economic models as helpful a moderate amount, a lot, or a great deal. Over one-third of payers (37.3%) were willing to partner with manufacturers on economic models using their plans' data. Payers valued preapproval information, data on total cost of care, and early access to models. Concerns remained regarding model transparency and assumptions. Most US payers reported interest in using economic models to inform oncology formulary decision making. Opportunities exist to educate payers in assessing economic models, especially among small health plans. Ensuring model availability at launch, transparency in model assumptions, and payer-manufacturer partnership in model development may increase the utility of oncology economic models among US payers. Pfizer provided funding for this research, and Pfizer employees led the development of the survey instrument, were involved in the analysis and interpretation of the data, and contributed to the manuscript as authors. Arondekar and Niyazov are employed by Pfizer. Biskupiak, Oderda, and Brixner are managers of Millcreek Outcomes Group and were paid as consultants on this project. Burgoyne was a consultant for Pfizer on this project.

摘要

为了支持肿瘤学处方集决策,尤其是在加速监管审批和利基人群方面,支付方希望获得监管机构审查范围之外的数据。展示治疗经济影响的经济模型可能会有所帮助,但关于支付方在肿瘤学中使用经济模型的信息有限。评估支付方在肿瘤学处方集决策中使用经济模型的看法。一个涉及健康经济学家和支付方的多学科指导委员会开发了一份包含单项答案、多项答案和自由回答问题的调查。试点调查在一个由 5 家美国支付方组成的小型顾问委员会进行了测试,并根据反馈进行了修订。2020 年 2 月,通过 AMCP Market Insights 计划向 221 家美国支付方和 10 名额外的支付方小组成员分发了调查,邀请他们讨论调查结果。结果主要以回应的频率呈现,并根据计划规模、健康计划类型和地理位置(区域与全国)进行评估。使用 Pearson 卡方检验或 Fisher 确切概率检验比较分类数据的响应差异。报告双侧值,使用 0.05 或更小的 alpha 水平表示统计学意义。 总体而言,231 家支付方中有 106 家(45.9%)完成了调查;45.5%代表小型计划(<100 万生命),54.5%代表大型计划(≥100 万生命)。受访者主要是药剂师(89.9%),其中 55.6%表示他们的工作是药房管理员。支付方表示对成本效益模型(CEM)和预算影响模型(BIM)有中等/最大兴趣(分别为 85.3%和 80.4%)。总体而言,51.6%的受访者声称在其药房和治疗委员会中有肿瘤学专业知识。大型计划比小型计划更有可能在审查肿瘤学经济模型方面具有专业知识(55.6%对 31.1%, = 0.015)。不审查经济模型的最常见原因包括“审查时不可用”(44.1%)和“潜在偏见”(38.2%)。总体而言,43.1%的支付方在审查制造商赞助的经济模型后使用自己的数据进行分析。为了告知处方集决策,62.7%的支付方有时、经常或总是使用 BIM,66.7%的支付方使用 CEM。当比较具有相似安全性/疗效特征的疗法时,68.6%的支付方报告经济模型有一定帮助,有很多帮助,有很大帮助。超过三分之一的支付方(37.3%)愿意与制造商合作,使用其计划的数据制作经济模型。支付方重视预批准信息、总成本信息和早期获得模型的机会。对于模型的透明度和假设,仍然存在担忧。 大多数美国支付方报告有兴趣使用经济模型来告知肿瘤学处方集决策。在评估经济模型方面,特别是在小型健康计划中,为支付方提供教育机会。确保模型在推出时可用、模型假设的透明度以及支付方与制造商在模型开发方面的合作,可能会提高美国支付方对肿瘤学经济模型的使用效果。辉瑞为这项研究提供了资金,辉瑞员工领导了调查工具的开发,参与了数据分析和解释,并作为作者为手稿做出了贡献。Arondekar 和 Niyazov 受雇于辉瑞。Biskupiak、Oderda 和 Brixner 是 Millcreek Outcomes Group 的经理,他们作为顾问参与了该项目。Burgoyne 是该项目辉瑞的顾问。