目的: 分析国际医保准入环节中专家调研产生的真实世界数据（RWD）的应用实践及规范,为我国在医保准入环节合理、规范使用专家调研数据提供参考。方法: 在应用实践层面,选取英国国家卫生与临床优化研究所（NICE）通过高度专业化技术评估（HST）纳入英国国家医疗服务体系（NHS）的26种罕见病药品作为样本,分析探讨其在NICE、加拿大药品与健康技术署（CADTH）、美国临床与经济评论研究所（ICER）的药品医保准入评估报告中,专家调研数据的应用实践及评估机构考量情况;在应用规范层面,分析澳大利亚药品福利咨询委员会（PBAC）与荷兰国家卫生保健所（ZIN）发布的专家调研数据在医保准入环节的应用与报告规范。结果: 在应用实践层面,从专家调研数据在NICE、CADTH和ICER使用RWD的药品占比情况来看,NICE共6种药品（24%）使用专家调研数据,CADTH共6种药品（38%）使用专家调研数据,研究未发现专家调研数据在ICER评价中的应用。专家调研数据可用于解决效果、成本、人群和市场份额不确定性等三种核心用途,且大部分能被评估机构所接受。部分专家调研数据因其固有局限和方法学操作不当等原因,被评估机构提出异议。在应用规范层面,PBAC和ZIN从方案设计与前期准备、调研实施、分析及结果解释三个环节规范专家调研数据的使用。结论: 专家调研产生的真实世界数据在医保准入环节具有一定的应用价值和必要性,且能被评估机构所采纳,但其在运用过程中仍面临一系列挑战,且应用与报告规范有待进一步明确。未来,可进一步探索、明确专家调研数据在我国医保准入中的角色定位、应用场景及应用规范。
Abstract
Objective: The paper analyzes the application practices and standards for real-world data (RWD) generated from expert surveys in international health insurance access processes, providing reference for the rational and standardized use of expert survey data in China's health insurance access procedures. Methods: At the application level, we selected 26 rare disease drugs approved for inclusion in the UK National Health Service (NHS) through the National Institute for Health and Care Excellence (NICE)'s Highly Specialised Technology (HST) assessment as case studies. We analyzed the application practices of expert survey data and the considerations of assessment bodies in drug reimbursement review reports from NICE, the Canadian Agency for Drugs and Technologies in Health (CADTH), and the Institute for Clinical and Economic Review (ICER). At the application standard level, we analyzed the application and reporting standards of expert survey data published by the Pharmaceutical Benefits Advisory Committee (PBAC) of Australia and the Zorginstituut Nederland,(ZIN) of the Netherlands in the context of health insurance access. Results: At the application level, based on the proportion of drugs using expert survey data in RWD across NICE, CADTH, and ICER: NICE used expert survey data for 6 drugs (24%), CADTH used it for 6 drugs (38%); and the study found no application of expert survey data in ICER assessments. Expert survey data can be utilized for three core purposes: addressing uncertainties related to efficacy (D1), cost (D2), and population and market share (D3). Most such data is generally accepted by evaluation agencies (P2). However, certain expert survey data has been contested by evaluation agencies due to inherent limitations and methodological flaws. At the application standard level, PBAC and ZIN regulate the use of expert survey data across three stages: proposal design and preliminary preparation, survey implementation, and analysis and interpretation of results. Conclusion: RWD generated from expert surveys holds certain application value and necessity in the medical insurance access process and can be adopted by evaluation agencies. However, its implementation still faces a series of challenges, and its application and reporting standards require further clarification. Future efforts should explore and define the role, application scenarios, and application standards of expert survey data in China's medical insurance access process.
关键词
真实世界数据 /
医保准入 /
专家调研数据 /
应用实践 /
应用规范
Key words
real-world data /
medical insurance admission /
expert survey data /
application practice /
application specifications
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
参考文献
[1] 国家药品监督管理局药品审评中心.用于产生真实世界证据的真实世界数据指导原则(试行) [EB/OL].(2021-04-13)[2025-07-23].https://www.cde.org.cn/main/news/viewInfoCommon/2a1c437ed54e7b838a7e86f4ac21c539.
[2] National Institute for Health and Care Excellence. NICE real-world evidence framework[EB/OL]. (2017-10-08)[2025-07-23]. https://www.nice.org.uk/corporate/ecd9/chapter/overview.
[3] National Institute for Health and Care Excellence. NICE real-world evidence framework[EB/OL]. (2022-06-23)[2025-07-23]. https://www.nice.org.uk/corporate/ecd9/chapter/overview.
[4] Canada's Drug Agency. Guidance for Reporting Real-World Evidence[EB/OL]. (2023-05-31)[2025-07-23]. https://www.cda-amc.ca/guidance-reporting-real-world-evidence.
[5] Institute for Clinical and Economic Review. A Framework to Guide the Optimal Development and Use of Real World Evidence for Coverage and Formulary Decisions[EB/OL]. (2017-12-01)[2025-07-23]. https://icer.org/assessment/a-framework-to-guide-the-optimal-development-and-use-of-real-world-evidence-for-coverage-and-formulary-decisions-2017/.
[6] DEL GIACCO S, CANONICA GW, AGACHE I, et al.Expert perspectives on next generation health guidelines: how to integrate RWE in EBM[J]. Pragmatic and observational research, 2025, 16: 169-177.
[7] EVANS C, CRAWFORD B.Expert judgement in pharmacoeconomic studies. Guidance and future use[J]. Pharmacoeconomics, 2000, 17(6): 545-553.
[8] IGLESIAS C P, THOMPSON A, ROGOWSKI W H, et al.Reporting guidelines for the use of expert judgement in model-based economic evaluations[J]. Pharmacoeconomics, 2016, 34(11): 1161-1172.
[9] National Institute for Health and Care Excellence. NICE health technology evaluation manual[EB/OL]. (2017-10-08)[2025-07-23]. https://www.nice.org.uk/about/what-we-do/our-programmes/nice-guidance/nice-technology-appraisal-guidance/changes-to-health-technology-evaluation.
[10] BOJKE L, SOARES M, CLAXTON K, et al.Developing a reference protocol for structured expert elicitation in health-care decision-making: a mixed-methods study[J]. Health technology assessment, 2021, 25(37): 1-124.
[11] Pharmaceutical Benefits Advisory Committee. Guidelines for preparing a submission to the Pharmaceutical Benefits Advisory Committee[EB/OL]. (2016-09)[2025-07-23]. https://pbac.pbs.gov.au/appendixes/appendix-1-expert-opinion.html.
[12] Zorginstituut Nederland. Richtlijn voor het uitvoeren van economische evaluaties in de gezondheidszorg (versie2024)[EB/OL]. (2024-01-16)[2025-07-23].https://www.zorginstituutnederland.nl/publicaties/publicatie/2024/01/16/richtlijn-voor-het-uitvoeren-van-economische-evaluaties-in-de-gezondheidszorg.
[13] SOARES M, COLSON A, BOJKE L, et al.Recommendations on the use of structured expert elicitation protocols for healthcare decision making: a good practices report of an ISPOR task force[J]. Value in health, 2024, 27(11): 1469-1478.
[14] MARSHALL M N.The key informant technique[J]. Family practice, 1996, 13(1): 92-97.
[15] MEREGAGLIA M, NICOD E, DRUMMOND M.The estimation of health state utility values in rare diseases: do the approaches in submissions for NICE technology appraisals reflect the existing literature? a scoping review[J].The European journal of health economics, 2023, 24(7): 1151-1216.
[16] LANDFELDT E, LINDBERG C, SEJERSEN T.Improvements in health status and utility associated with ataluren for the treatment of nonsense mutation duchenne muscular dystrophy[J]. Muscle and Nerve, 2020, 61(3): 363-368.
[17] LLOYD A, PIGLOWSKA N, CIULLA T, et al.Estimation of impact of RPE65-mediated inherited retinal disease on quality of life and the potential benefits of gene therapy[J].British Journal of Ophthalmology, 2019, 103(11): 1610-1614.
[18] BOULKEDID R, ABDOUL H, LOUSTAU M, et al.Using and reporting the delphi method for selecting healthcare quality indicators: a systematic review[J]. Public library of science one, 2011, 6(6): e20476.
[19] 国家药品监督管理局药品审评中心.真实世界证据支持药物研发与审评的指导原则[EB/OL].(2020-01-03)[2025-07-23].http://www.srsrmyy.cn/uploads/files/20211224/ffa4170eaa8552befcf040d5c741ea9d.pdf.
[20] Canada's Drug Agency. Guidelines for the Economic Evaluation of Health Technologies: Canada-4th Edition[EB/OL]. (2025-05-14)[2025-11-02]. https://www.cda-amc.ca/guidelines-economic-evaluation-health-technologies-canada-4th-edition.
[21] SHEPARD D S.Cost-effectiveness in health and medicine[J].Journal of mental health policy and economics, 1999, 2(2): 91-92.
[22] BURNS L, LE ROUX N, KALESNIK-ORSZULAK R, et al.Real-world evidence for regulatory decision-making: updated guidance from around the world[J]. Frontiers in medicine, 2023, 10: 1236462.
[23] GRIFFITHS A, DUNNING L, FACEY K, et al.Recommended methods for the collection of clinical expert judgment in rare diseases: generating evidence to support reimbursement of orphan drugs[J]. International journal of technology assessment in health care, 2025, 41(1): e76.
[24] FORSYTH J E, UTTLEY L, WONG R, et al.Structured expert elicitation for long-term survival outcomes in health technology assessment: a systematic review[J]. BMC medical informatics and decision making, 2025, 25(1): 387.
[25] HADORN D, KVIZHINADZE G, COLLINSON L, et al.Use of expert knowledge elicitation to estimate parameters in health economic decision models[J]. International journal of technology assessment in health care, 2014, 30(4): 461-468.
[26] GRIGORE B, PETERS J, HYDE C, et al.Methods to elicit probability distributions from experts: a systematic review of reported practice in health technology assessment[J]. Pharmacoeconomics, 2013, 31(11): 991-1003.
[27] SOARES M O, SHARPLES L, MORTON A, et al.Experiences of structured elicitation for model-based cost-effectiveness analyses[J]. Value in health, 2018, 21(6): 715-723.
[28] IGLESIAS C P, THOMPSON A, ROGOWSKI W H, et al.Reporting guidelines for the use of expert judgement in model-based economic evaluations[J]. Pharmacoeconomics, 2016, 34(11): 1161-1172.
[29] CADHAM C J, KNOLL M, SÁNCHEZ-ROMERO L M, et al. The use of expert elicitation among computational modeling studies in health research: A systematic review[J]. Medical Decision Making, 2022, 42(5): 684-703.
[30] EVANS C, CRAWFORD B.Expert judgement in pharmacoeconomic studies. Guidance and future use[J]. Pharmacoeconomics, 2000, 17(6): 545-553.
[31] BOJKE L, GRIGORE B, JANKOVIC D, et al.Informing reimbursement decisions using cost-effectiveness modelling: A guide to the process of generating elicited priors to capture model uncertainties[J]. PharmacoEconomics, 2017, 35(9): 867-877.
[32] SHELF: the sheffield elicitation framework | springer nature link (formerly SpringerLink)[EB/OL]. [2025-07-23]. https://link.springer.com/chapter/10.1007/978-3-319-65052-4_4.
[33] GRIGORE B, PETERS J, HYDE C, et al.EXPLICIT: a feasibility study of remote expert elicitation in health technology assessment[J]. BMC medical informatics and decision making, 2017, 17(1): 131.
[34] Elicitation of expert opinion for uncertainty and risks | request PDF[EB/OL]. [2025-07-23]. https://www.researchgate.net/publication/266732257_Elicitation_of_Expert_Opinion_for_Uncertainty_and_Risks.
[35] BOJKE L, SOARES M O, CLAXTON K, et al.Reference case methods for expert elicitation in health care decision making[J]. Medical decision making, 2022, 42(2): 182-193.
[36] O'LEARY R A, CHOY S L, MURRAY J V, et al. Comparison of three expert elicitation methods for logistic regression on predicting the presence of the threatened brush‐tailed rock‐wallaby petrogale penicillata[J]. Environmetrics, 2009, 20(4): 379-398.
[37] MONTIBELLER G, VON WINTERFELDT D.Cognitive and motivational biases in decision and risk analysis[J]. Risk analysis 2015, 35(7): 1230-1251.
[38] HUSEREAU D, DRUMMOND M, AUGUSTOVSKI F, et al.Consolidated health economic evaluation reporting standards 2022 (CHEERS 2022) statement: updated reporting guidance for health economic evaluations[J]. Value in health, 2022, 25(1): 3-9.
[39] SOARES M, COLSON A, BOJKE L, et al.Recommendations on the use of structured expert elicitation protocols for healthcare decision making: a good practices report of an ISPOR task force[J]. Value in health, 2024, 27(11): 1469-1478.
[40] SULLIVAN W, PAYNE K.The appropriate elicitation of expert opinion in economic models: making expert data fit for purpose[J]. Pharmacoeconomics, 2011,29(6):455-459.
[41] Uncertain judgements: eliciting experts' probabilities | wiley online books[EB/OL]. [2025-07-23]. https://onlinelibrary.wiley.com/doi/book/10.1002/0470033312.
[42] HORA S C, VON WINTERFELDT D.Nuclear waste and future societies: a look into the deep future[J]. Technological forecasting and social change, 1997, 56(2): 155-170.
[43] MORGAN M G.Use (and abuse) of expert elicitation in support of decision making for public policy[J]. Proceedings of the National Academy of Sciences of the United States of America, 2014, 111(20): 7176-7184.
