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中美两国医保预算影响分析研究文献的质量评估

2019-10-20柳鹏程顾佳慧白铭钰董雅琦林佳儿林夕涵吴文思彭楠邵蓉姚文兵

中国药房 2019年12期
关键词:医疗费用质量评估文献研究

柳鹏程 顾佳慧 白铭钰 董雅琦 林佳儿 林夕涵 吴文思 彭楠 邵蓉 姚文兵

摘 要 目的:為我国医保预算影响分析(BIA)研究的开展提供经验借鉴。方法:在PubMed、ProQuest、中国知网、万方和中国生物医学文献服务系统等数据库中检索建库至今的中美两国关于医保BIA研究的相关文献,对其基本信息、分析结果和数据来源等内容进行归纳和整理,并基于模型设计、研究角度、治疗成本、参考情景、目标人群、研究时限及贴现/通货膨胀、敏感性分析这7个关键要素对纳入文献进行描述性分析。结果:本研究共纳入72篇文献,其中中国研究24项(33.33%),美国地区研究48项(66.67%);适应证为慢性病的相关研究有45项(62.50%),急性病的相关研究有21项(37.50%);研究方法上,单独使用BIA的有49项(68.06%),联用BIA和药物经济学评价的有23项(31.94%);模型设计方面,有 50项(69.44%)研究采用了成本计算模型;研究角度方面,有60项(83.33%)研究基于医保部门研究视角;治疗成本的计算中,有69项(95.84%)研究包含了药品费用;参考情景方面,有61项(84.72%)研究对比了以药物为主的不同治疗组合的经济性;目标人群方面,仅有31项(43.06%)研究采用了真实世界数据;研究时限及贴现/通货膨胀方面,有14项(19.44%)研究使用治疗疗程或住院时长表示研究时限,19项(26.39%)研究使用了贴现率或通货膨胀率调整成本;敏感性分析方面,有62项(86.11%)研究做了敏感性分析,其中 49项(68.06%)研究采用了单因素敏感性分析。结论:中美两国医保BIA研究文献尚存在数据使用不合理、成本范围涵盖不全和敏感性分析因变量变化范围不合理等局限。建议BIA研究应规范数据来源,提高预算证据质量;合理评估市场规模,提高预测真实性;科学设置变量和变化范围,提升结果稳健性;建立BIA研究范式或评级标准,科学指导BIA研究。

关键词 医保预算影响分析;医疗费用;中国;美国;文献研究;质量评估;药物经济学

Quality Evaluation of the Literatures about Medical Insurance Budget Impact Analysis in China and the United States

LIU Pengcheng,GU Jiahui,BAI Mingyu,DONG Yaqi,LIN Jiaer,LIN Xihan,WU Wensi,PENG Nan,SHAO Rong,YAO Wenbing(National Center for Pharmaceutical Policy and Pharmaceutical Industry Economy, China Pharmaceutical University, Nanjing 211198, China)

ABSTRACT OBJECTIVE: To provide experience and reference for the study of medical insurance budget impact analysis (BIA) in China. METHODS: Retrieved from PubMed, ProQuest, CNKI, Wanfang database and CBM, related literatures about medical insurance BIA research in China and the United States were collected since the establishment of the database. The basic information, analysis results and data sources were summarized and sorted out, and descriptive analysis of the included literature was carried out on basis of seven key elements such as model design, research perspective, treatment cost, reference scenario, target population, research time limit and discount/inflation, sensitivity analysis. RESULTS: A total of 72 literatures were included in this study, involving 24 (33.33%) studies in China, 48 (66.67%) studies in the United States; the indications of 45 studies were chronic diseases (62.50%), and those of 21 studies were acute diseases (37.50%). Among the research methods, 49 studies (68.06%) used BIA alone and 23 studies (31.94%) adopted BIA combined with pharmaceutical economics. In terms of model design, 50 studies (69.44%) adopted cost calculation models. In terms of research perspective, 60 studies (81.94%) were based on the perspective of medical insurance department research. In the calculation of treatment cost, 69 studies (95.84%) included drug cost. In terms of reference scenarios, 61 studies (84.72%) compared the economics of different drug-based treatment groups. For target population, only 31 (43.06%) studies used real world data. In terms of research duration and discount/inflation, 14 studies (19.44%) used treatment or length of hospitalization to indicate research duration, and 19 studies (26.39%) used discount rate or inflation rate to adjust costs. As for sensitivity analysis, 62 studies (86.11%) conducted sensitivity analysis, of which 49 (68.06%) used single factor sensitivity analysis. CONCLUSIONS: There are still some limitations in medical insurance BIA research literature in China and the United States, such as unreasonable use of data, incomplete coverage of the cost, and unreasonable setting of sensitivity analysis variables. It is recommended that BIA research should standardize data sources to improve the quality of budget evidence quality, reasonably evaluate market size to improve the authenticity of prediction, scientifically set variables and their scope of change to improve the stability of results, establish BIA research paradigms or evaluating standards so as to guide BIA research scientifically.

KEYWORDS Medical insurance budget impact analysis; Medical costs; China; United States; Literature research; Quality evaluation; Pharmacoeconomics

21世纪以来,随着社会年龄结构的变化,我国老龄化趋势进一步加深,2017 年我国60周岁及以上老年人口已高达2.41亿,占总人口的17.3%[1]。同时,经济的快速发展、医疗技术水平的不断提升,又进一步推高了群众对于医药卫生资源的需求,使得个人医疗费用支出和国家医保基金都面临极大压力。因此,探索评估药物经济性的正确方式,以遏制医药费用的快速增长,对保障人民的用药需求具有重要意义。

当前,国际社会主要使用药物经济学评价(Pharmaceutical economics,PE)和醫保预算影响分析(Budget impact analysis,BIA)来评估药物的经济性。PE评价的结果通常指向个体药物或治疗方案间成本-效益的比较;而BIA是从预算持有人角度出发,在有限医疗资源约束的前提下,分析将一种健康干预措施纳入或排除在某一医疗系统所产生的经济后果[2]。相对而言,BIA可用于预测一种治疗方案的变化对医疗总费用的影响,对于保障有限预算的可支付性和长期稳定性起着重要作用,因此越来越受到各国卫生决策部门的重视。

我国医保BIA研究起步较晚,研究质量参差不齐。而美国作为全球较早开展预算影响评估的国家之一,其研究数量与质量均位于全球前列。因此,本研究选择中美两国医保BIA的相关研究文献进行质量评估,分析其文献研究的规范性,为我国医保BIA研究提供经验借鉴。

1 资料与方法

1.1 资料来源与纳排标准

检索PubMed、ProQuest、中国知网、万方和中国生物医学文献服务系统等数据库中中美两国的医保BIA相关文献。中文关键词为“医保”“预算影响分析“预算影响模型”,英文关键词为“Medical insurance”“Budget impact analysis”“Budget impact model”。

纳入标准:(1)发表时间为建库至2018年5月;(2)语种为中文和英文。排除标准:(1)学位论文、会议文献;(2)综述;(3)投稿通知、报纸;(4)无法获取的文献;(5)重复发表的文献;(6)非中英文文献;(7)非中美医药领域的研究。

1.2 资料提取

对纳入文献的基本信息、分析结果和数据来源等内容进行归纳和整理,并基于BIA关键要素对文献质量进行描述性分析。提取资料内容主要包括纳入研究的基本信息、BIA相关信息、BIA 数据来源、研究局限性等。资料提取内容要点详见表1。

1.3 文献质量评估要点

科学设计BIA分析框架是评估医保基金运营稳定性的基本前提。基于国际药物经济学与结果研究协会(International Society for Pharmacoeconomics and Outcomes Research,ISPOR)和加拿大、美国、爱尔兰等国家或地区[3-12]现有的BIA指南和其他已公开发布的方法学研究,本课题组归纳总结了BIA设计中的7个关键要素,即使用分析框架来研究BIA时,必须考虑以下7个因素:模型设计、研究角度、治疗成本、参考情景、目标人群、研究时限及贴现/通货膨胀、敏感性分析[12]。

1.3.1 模型设计 BIA基本原理是计算某项特定医疗措施或药品纳入预算持有人采购计划前、后的资金支出差额。通过BIA最终结果的正负情况可以反映纳入某项特定医疗措施或药品对预算持有人具体资金支出的影响,从而可以帮助预算持有人更好地作出是否纳入该项医疗措施或药品的决定,以维持有限预算的平稳运行,促进卫生资源合理分配。

BIA可基于不同疾病特征采用静态建模或者动态建模的方法。静态模型可以是一个编写在Excel等电子表格中的成本计算模型或者简单的决策树模型,适用于病程较短的急性病或者病情不太复杂的疾病。其中,成本计算模型是BIA类文章的基本模型,也是应用最为广泛的模型。动态模型可采用Markov模型和离散事件模拟来计算,适用于病情延续时间长、病情反复或频繁变化的慢性疾病的模拟[13]。Markov模型考虑了患者治疗方案的选择变化以及每个疾病状态在一定时间内的转变概率[14];而离散事件模拟则不需要固定的状态和周期,比Markov模型更加灵活,但缺乏与模型相适应的数据[15]。

1.3.2 研究角度 BIA研究应基于预算持有人的角度,其最终是为了预测将某种医疗措施纳入或排除采购计划对医疗费用可能的经济影响[16],从而为调整药品目录和制定实际支付价提供重要参考依据。预算持有人包括了医保基金管理方和有资金约束的医疗机构等,BIA研究需要灵活地适应各个变量的变化,基于具体情形给出科学合理的预算估计。

1.3.3 治疗成本 纳入BIA的治疗成本应为从预算持有人角度出发的、在预算报销范围内的、患者自身产生的直接医疗费用。其多指在疾病检查、诊断和治疗过程中所产生的费用,包括药物成本、特定疾病的检查费用以及因疾病进展带来的手术、医疗器械等外科介入的费用;在正常治疗情况下产生的不良反应和并发症等相关疾病的治疗费用也应纳入其中。治疗成本的选取应基于不同的研究角度,根据实际情况具体考量。

1.3.4 参考情景 BIA通过比较参考情景和新药情景的支出差额,以评估在研究时限内有限预算的年度增量成本,其内容应包括参考情景的选取和市场规模的预估两大部分。新药情景考察的是将某项医疗措施纳入医保目录后对医保基金的影响;参考情景则考量该项医疗措施未纳入医保目录时,使用它的替代疗法或互补疗法对于医保基金的影响。纳入医保目录研究应对两大情景相关假设提供清晰的描述,并提供作出这些假设的依据。参考情景可通过查询特定适应证的诊断指南或医务人员提供的临床实际使用情况获取。两大情景的市场规模预估须参考诊疗方案当前的市场规模、患者对该方案的依从性以及新药对于现有药物的替代或互补效应等因素。

3.1.2 成本衡量涵盖不全 虽然BIA应该只考虑对预算持有人产生影响的直接医疗成本,不考虑治疗间接成本(如患者与陪护人员因病不能正常工作)和隐性成本(如患者带来的痛苦和生活不便),但是在本次纳入评估的研究中,部分研究未考虑不良反应、并发症和其他医疗服务费用,如未衡量不良反应产生的其他治疗费用和用药剂量的调整对整体费用的影响,未考虑基础疾病的治疗和预后所产生的费用;部分研究未测算药物治疗失败等情形产生的额外治疗费用;多数研究未按照疾病严重程度选择不同的治疗方案,分析结果缺乏真实性。

3.1.3 敏感性分析因变量变化范围设置不尽合理 部分研究未考虑敏感性分析或敏感性分析计算要素不全;部分研究在实际计算中纳入敏感性分析的要素使用统一的变化范围,无法反映实际情况;多数研究未指明因变量的变动范圍依据,导致敏感性分析结果缺乏科学性,不具说服力。

3.2 对今后研究的建议

3.2.1 规范数据来源,提高预算证据质量 针对本次质量评估中出现的数据缺乏或替换、简化假设和预测不准确的问题,建议文献中所有数据均需标明明确的数据来源,以保持数据的可追溯性。在计算过程中,应优先考虑真实世界数据,同时可参考相似药物在同一市场或是同一药物在相似市场的相关资料;其次,建议使用已公开发表的文献资料,以保证不同主体提交的预测中数据结果的一致性。在上述数据不可得的情况下,才可通过德尔菲法、专家访谈和问卷调查等形式进行估算。

3.2.2 合理评估市场规模,提高预测真实性 本次纳入的多数文献未对研究市场规模预测的详细方法进行说明,降低了评估结果的科学性。市场规模的预测分为两大部分:一是对于市场份额的预估,二是对于市场增长率的预估。对于市场份额的预估应优先通过企业年终总结、相关机构的市场调查报告或是医院及医保部门数据库等的资料得出;对于市场增长率的预估应结合目标药物历年来的销售走向和市场需求变化综合分析[90]。若新药纳入采购计划对相关药物市场规模无影响或影响甚微,则目标人群的估计可以只考虑人口预测的增长;若引入新药会对相关药物市场规模产生显著影响,则市场份额的变化需从人口的预测增长和新药预测的影响两个方面进行考虑。

3.2.3 科学设置变量和变化范围,提升结果稳健性 BIA结果的不确定性主要来源于BIA模型框架的设定和计算过程中参数值的选取。而模型框架的不确定性取决于新干预措施的可及性和使用限制导致的预期治疗方案的变化;参数值的不确定性取决于对当前和新的干预措施预估的有效性。

对计算过程中的因变量常采用敏感性分析和情景分析进行检验。其中,敏感性分析包括单因素敏感性分析、多因素敏感性分析和极值分析。因变量应选取对于特定治疗方案成本影响较大的因素,如目标人群、药物成本和市场规模等。不同因变量对于结果的影响权重不同,故不建议使用统一的通用范围,其具体变化范围应通过真实情况、既往文献或是专家意见等途径得出,以增强敏感性分析结果的真实性。

3.2.4 建立BIA研究范式或评级标准,科学指导BIA研究 我国BIA尚未建立系统化的研究体系,因此独立的研究机构的建设和跨学科背景专业人员的培养于我国BIA的规范化开展意义重大。同时,还应着手建立结合我国实际情况的公开的BIA指南和质量评价量表,不仅要对本研究中提出的常见7个BIA要素进行详细规定,同时还应对超说明书用药、贴现率的取舍等问题作出明确的指示[91],为此类研究提供科学合理的方法学指导。

3.3 本研究的不足之处

(1)样本量不足:本研究所选取的BIA文献基于特定数据库产生,可能存在选择性偏倚;(2)文献质量评估要点即7个要素是基于部分国家成熟的BIA指南和方法论进行选取的,可能无法涵盖BIA的所有关键要素。

4 结语

BIA是完整的药物经济学评价的重要组成部分,它能评估短期内、特定情境下新药引入后的经济学影响,受到决策者的广泛关注。因此,为完善我国药物经济性评估方法,不仅需从制度上保障BIA方法的实施,鼓励卫生决策者将其作为我国新药申报、医保准入和药品价格谈判过程中的重要参考资料,弥补传统药物经济学评价方法缺乏从整体上统筹医保基金运行的问题,还需深入推进BIA相关研究,建立公开、规范化的评价量表,提高BIA在决策参考中的证据强度。

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(收稿日期:2019-01-21 修回日期:2019-05-15)

(编辑:孙 冰)

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