首页 > 最新文献

Forum for Health Economics and Policy最新文献

英文 中文
A Note on Income Effects and Health Care Cost Growth in Medicare 关于医疗保险的收入效应和医疗保健成本增长的说明
Q3 Economics, Econometrics and Finance Pub Date : 2014-02-01 DOI: 10.1515/fhep-2013-0001
T. Mcguire
Abstract This paper sets out a model of technical change and health care cost growth for a representative Medicare beneficiary facing a budget constraint. Derivation of an explicit expression for health care cost growth shows how technological change and preferences, including income effects, affect cost growth. The analysis highlights the role of the 76% subsidy from current taxpayers to Medicare beneficiaries for purchase of health insurance. This subsidy insulates beneficiaries from the income effects of cost growth by shifting the costs and income effects to taxpayers. Simulations show that over the next 10–20 years, income effects will have little effect on cost growth in Medicare.
摘要本文提出了一个具有代表性的医疗保险受益人面临预算约束的技术变革和医疗保健成本增长模型。对医疗保健成本增长的显式表达式的推导表明,技术变革和偏好,包括收入效应,如何影响成本增长。分析强调了当前纳税人向医疗保险受益人提供的76%的医疗保险补贴的作用。这种补贴通过将成本和收入效应转移到纳税人身上,使受益人免受成本增长的收入效应的影响。模拟显示,在未来10-20年,收入效应对医疗保险成本增长的影响微乎其微。
{"title":"A Note on Income Effects and Health Care Cost Growth in Medicare","authors":"T. Mcguire","doi":"10.1515/fhep-2013-0001","DOIUrl":"https://doi.org/10.1515/fhep-2013-0001","url":null,"abstract":"Abstract This paper sets out a model of technical change and health care cost growth for a representative Medicare beneficiary facing a budget constraint. Derivation of an explicit expression for health care cost growth shows how technological change and preferences, including income effects, affect cost growth. The analysis highlights the role of the 76% subsidy from current taxpayers to Medicare beneficiaries for purchase of health insurance. This subsidy insulates beneficiaries from the income effects of cost growth by shifting the costs and income effects to taxpayers. Simulations show that over the next 10–20 years, income effects will have little effect on cost growth in Medicare.","PeriodicalId":38039,"journal":{"name":"Forum for Health Economics and Policy","volume":"12 1","pages":"1 - 12"},"PeriodicalIF":0.0,"publicationDate":"2014-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85873619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
A Note on Income Effects and Health Care Cost Growth in Medicare. 关于医疗保险的收入效应和医疗保健成本增长的说明。
Q3 Economics, Econometrics and Finance Pub Date : 2014-02-01 DOI: 10.1515/fhep-2013-0
Thomas G McGuire

This paper sets out a model of technical change and health care cost growth for a representative Medicare beneficiary facing a budget constraint. Derivation of an explicit expression for health care cost growth shows how technological change and preferences, including income effects, affect cost growth. The analysis highlights the role of the 76% percent subsidy from current taxpayers to Medicare beneficiaries for purchase of health insurance. This subsidy insulates beneficiaries from the income effects of cost growth by shifting the costs and income effects to taxpayers. Simulations show that over the next 10-20 years, income effects will have little effect on cost growth in Medicare.

本文为面临预算约束的代表性医疗保险受益人建立了一个技术变革和医疗保健成本增长的模型。对医疗保健成本增长的显式表达式的推导表明,技术变革和偏好,包括收入效应,如何影响成本增长。该分析强调了当前纳税人向医疗保险受益人提供的76%的购买健康保险补贴的作用。这种补贴通过将成本和收入效应转移到纳税人身上,使受益人免受成本增长的收入效应的影响。模拟显示,在未来10-20年,收入效应对医疗保险成本增长的影响微乎其微。
{"title":"A Note on Income Effects and Health Care Cost Growth in Medicare.","authors":"Thomas G McGuire","doi":"10.1515/fhep-2013-0","DOIUrl":"https://doi.org/10.1515/fhep-2013-0","url":null,"abstract":"<p><p>This paper sets out a model of technical change and health care cost growth for a representative Medicare beneficiary facing a budget constraint. Derivation of an explicit expression for health care cost growth shows how technological change and preferences, including income effects, affect cost growth. The analysis highlights the role of the 76% percent subsidy from current taxpayers to Medicare beneficiaries for purchase of health insurance. This subsidy insulates beneficiaries from the income effects of cost growth by shifting the costs and income effects to taxpayers. Simulations show that over the next 10-20 years, income effects will have little effect on cost growth in Medicare.</p>","PeriodicalId":38039,"journal":{"name":"Forum for Health Economics and Policy","volume":"17 1","pages":"1-12"},"PeriodicalIF":0.0,"publicationDate":"2014-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4548929/pdf/nihms-713000.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34026350","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
The Crowd, the Cloud and Improving the Future of Medical Device Innovation 人群、云与改善医疗器械创新的未来
Q3 Economics, Econometrics and Finance Pub Date : 2014-01-01 DOI: 10.1515/fhep-2012-0023
Marco D. Huesch, R. Szczerba
Abstract Barriers and delays to medical device innovation are often solely attributable to the regulatory environment instead of both the current state of innovation practices and product development processes in the industry. Increasing the pace of innovation while reducing costs requires the creation of a new approach that fits both established medical device corporations as well as entrepreneurial start-ups. In this commentary we advance the concept of innovation platforms to facilitate ideation in the medical device space. Such platforms could also allow the full health benefits from individual medical devices to be reaped, by overcoming interoperability concerns through simulation and credentialing. Given the dramatic benefits of medical device success, such non-traditional business models for development may be potential solutions for industry, users and regulators.
医疗器械创新的障碍和延迟通常仅仅归因于监管环境,而不是行业中创新实践和产品开发过程的现状。要在降低成本的同时加快创新步伐,就需要创造一种既适合老牌医疗设备公司,也适合创业型初创企业的新方法。在这篇评论中,我们提出了创新平台的概念,以促进医疗器械领域的创新。这些平台还可以通过模拟和认证克服互操作性问题,从而实现个人医疗设备的全部健康效益。鉴于医疗设备成功带来的巨大好处,这种非传统的发展商业模式可能是行业、用户和监管机构的潜在解决方案。
{"title":"The Crowd, the Cloud and Improving the Future of Medical Device Innovation","authors":"Marco D. Huesch, R. Szczerba","doi":"10.1515/fhep-2012-0023","DOIUrl":"https://doi.org/10.1515/fhep-2012-0023","url":null,"abstract":"Abstract Barriers and delays to medical device innovation are often solely attributable to the regulatory environment instead of both the current state of innovation practices and product development processes in the industry. Increasing the pace of innovation while reducing costs requires the creation of a new approach that fits both established medical device corporations as well as entrepreneurial start-ups. In this commentary we advance the concept of innovation platforms to facilitate ideation in the medical device space. Such platforms could also allow the full health benefits from individual medical devices to be reaped, by overcoming interoperability concerns through simulation and credentialing. Given the dramatic benefits of medical device success, such non-traditional business models for development may be potential solutions for industry, users and regulators.","PeriodicalId":38039,"journal":{"name":"Forum for Health Economics and Policy","volume":"75 1","pages":"13 - 20"},"PeriodicalIF":0.0,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89012401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Medicare Reimbursement Reform for Provider Visits and Health Outcomes in Patients on Hemodialysis. 医疗保险报销改革对提供者访问和血液透析患者的健康结果。
Q3 Economics, Econometrics and Finance Pub Date : 2014-01-01 DOI: 10.1515/fhep-2012-0018
Kevin F Erickson, Wolfgang C Winkelmayer, Glenn M Chertow, Jay Bhattacharya

The relation between the quantity of many healthcare services delivered and health outcomes is uncertain. In January 2004, the Centers for Medicare and Medicaid Services introduced a tiered fee-for-service system for patients on hemodialysis, creating an incentive for providers to see patients more frequently. We analyzed the effect of this change on patient mortality, transplant wait-listing, and costs. While mortality rates for Medicare beneficiaries on hemodialysis declined after reimbursement reform, mortality declined more - or was no different - among patients whose providers were not affected by the economic incentive. Similarly, improved placement of patients on the kidney transplant waitlist was no different among patients whose providers were not affected by the economic incentive; payments for dialysis visits increased 13.7% in the year following reform. The payment system designed to increase provider visits to hemodialysis patients increased Medicare costs with no evidence of a benefit on survival or kidney transplant listing.

提供的许多保健服务的数量与健康结果之间的关系是不确定的。2004年1月,医疗保险和医疗补助服务中心为血液透析患者引入了分层收费服务体系,鼓励医疗服务提供者更频繁地为患者看病。我们分析了这一变化对患者死亡率、移植等待名单和费用的影响。虽然医疗保险受益人的血液透析死亡率在报销改革后下降了,但那些医疗服务提供者不受经济激励影响的患者死亡率下降得更多,或者没有什么不同。同样地,在供方不受经济激励影响的患者中,患者在肾移植等待名单上的位置改善没有什么不同;在改革后的一年里,透析就诊费用增加了13.7%。该支付系统旨在增加血透患者的就诊次数,增加了医疗保险费用,但没有证据表明对生存或肾移植有好处。
{"title":"Medicare Reimbursement Reform for Provider Visits and Health Outcomes in Patients on Hemodialysis.","authors":"Kevin F Erickson,&nbsp;Wolfgang C Winkelmayer,&nbsp;Glenn M Chertow,&nbsp;Jay Bhattacharya","doi":"10.1515/fhep-2012-0018","DOIUrl":"https://doi.org/10.1515/fhep-2012-0018","url":null,"abstract":"<p><p>The relation between the quantity of many healthcare services delivered and health outcomes is uncertain. In January 2004, the Centers for Medicare and Medicaid Services introduced a tiered fee-for-service system for patients on hemodialysis, creating an incentive for providers to see patients more frequently. We analyzed the effect of this change on patient mortality, transplant wait-listing, and costs. While mortality rates for Medicare beneficiaries on hemodialysis declined after reimbursement reform, mortality declined more - or was no different - among patients whose providers were not affected by the economic incentive. Similarly, improved placement of patients on the kidney transplant waitlist was no different among patients whose providers were not affected by the economic incentive; payments for dialysis visits increased 13.7% in the year following reform. The payment system designed to increase provider visits to hemodialysis patients increased Medicare costs with no evidence of a benefit on survival or kidney transplant listing.</p>","PeriodicalId":38039,"journal":{"name":"Forum for Health Economics and Policy","volume":"17 1","pages":"53-77"},"PeriodicalIF":0.0,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/fhep-2012-0018","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34293533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 12
A Cost-Benefit Analysis of Using Evidence of Effectiveness in Terms of Progression Free Survival in Making Reimbursement Decisions on New Cancer Therapies 使用无进展生存期的有效性证据来制定新的癌症治疗报销决策的成本-收益分析
Q3 Economics, Econometrics and Finance Pub Date : 2014-01-01 DOI: 10.1515/fhep-2013-0025
Warren Stevens, T. Philipson, Yanyu Wu, Connie Chen, D. Lakdawalla
Abstract Payers increasingly require evidence of a statistically significant difference in overall survival (OS) for reimbursement of new cancer therapies. At the same time, it becomes increasingly costly to design clinical trials that measure OS endpoints instead of progression-free survival (PFS) endpoints. While PFS is often an imperfect proxy for OS effects, it is also faster and cheaper to measure accurately. This study develops a general cost-benefit framework that quantifies the competing trade-offs of the use of PFS versus that of OS in oncology reimbursement. We then apply this general framework to the illustrative case of metastatic renal cell carcinoma (mRCC). In the particular case of mRCC, the framework demonstrates that the net benefit to society from basing reimbursement decisions on PFS endpoints could be between $271 and $1271 million in the United States, or between €171 and €1128 million in Europe. In longevity terms, waiting for OS data in this case would result in a net loss of 3549–14,557 life-years among US patients, or 6785–27,993 life-years for European patients. While more stringent standards for medical evidence improve accuracy, they also impose countervailing costs on patients in terms of foregone health gains. These costs must be weighed against the benefits of greater accuracy. The magnitudes of the costs and benefits may vary across tumor types and need to be quantified systematically.
支付方越来越多地需要总生存期(OS)有统计学显著差异的证据来报销新的癌症疗法。与此同时,设计临床试验测量OS终点而不是无进展生存期(PFS)终点的成本越来越高。虽然PFS通常是OS效果的不完美代理,但准确测量它也更快、更便宜。本研究开发了一个一般的成本效益框架,量化了肿瘤报销中使用PFS与使用OS的竞争权衡。然后,我们将这一总体框架应用于转移性肾细胞癌(mRCC)的说明性病例。在mRCC的特殊情况下,该框架表明,基于PFS端点的报销决策对社会的净效益在美国可能在2.71亿至1.271亿美元之间,在欧洲可能在1.71亿至1.128亿欧元之间。就寿命而言,在这种情况下,等待OS数据将导致美国患者净损失3549-14,557生命年,或欧洲患者净损失6785-27,993生命年。虽然更严格的医学证据标准提高了准确性,但就放弃的健康收益而言,它们也给患者带来了相应的成本。这些代价必须与更高的准确性所带来的好处进行权衡。成本和收益的大小可能因肿瘤类型而异,需要系统地量化。
{"title":"A Cost-Benefit Analysis of Using Evidence of Effectiveness in Terms of Progression Free Survival in Making Reimbursement Decisions on New Cancer Therapies","authors":"Warren Stevens, T. Philipson, Yanyu Wu, Connie Chen, D. Lakdawalla","doi":"10.1515/fhep-2013-0025","DOIUrl":"https://doi.org/10.1515/fhep-2013-0025","url":null,"abstract":"Abstract Payers increasingly require evidence of a statistically significant difference in overall survival (OS) for reimbursement of new cancer therapies. At the same time, it becomes increasingly costly to design clinical trials that measure OS endpoints instead of progression-free survival (PFS) endpoints. While PFS is often an imperfect proxy for OS effects, it is also faster and cheaper to measure accurately. This study develops a general cost-benefit framework that quantifies the competing trade-offs of the use of PFS versus that of OS in oncology reimbursement. We then apply this general framework to the illustrative case of metastatic renal cell carcinoma (mRCC). In the particular case of mRCC, the framework demonstrates that the net benefit to society from basing reimbursement decisions on PFS endpoints could be between $271 and $1271 million in the United States, or between €171 and €1128 million in Europe. In longevity terms, waiting for OS data in this case would result in a net loss of 3549–14,557 life-years among US patients, or 6785–27,993 life-years for European patients. While more stringent standards for medical evidence improve accuracy, they also impose countervailing costs on patients in terms of foregone health gains. These costs must be weighed against the benefits of greater accuracy. The magnitudes of the costs and benefits may vary across tumor types and need to be quantified systematically.","PeriodicalId":38039,"journal":{"name":"Forum for Health Economics and Policy","volume":"4 1","pages":"21 - 52"},"PeriodicalIF":0.0,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75709695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 5
Opportunities in the Economics of Personalized Health Care and Prevention 个性化卫生保健和预防经济学中的机遇
Q3 Economics, Econometrics and Finance Pub Date : 2013-09-01 DOI: 10.1515/fhep-2013-0012
D. Meltzer
Abstract Personalized medicine is best viewed from a broad perspective of trying to use information about a patient to improve care. While “personalized medicine” often emphasizes the value of genetic information, traditional clinical approaches to personalizing care based on patient phenotype, provider and system-level factors should not be neglected. As these diverse approaches to personalization are examined, tools such as cost-effectiveness analysis can provide important insights into the value of these approaches, strategies for their implementation and dissemination, and priorities for future research. Such analyses are likely to be most insightful if they recognize that patient and provider behaviors are essential determinants of the value of treatments and that patient factors in particular may have large effects on the value of treatments and the need for interventions to improve decision making. These comments suggest three major areas of opportunity for economic analyses of personalized medicine: (1) traditional clinical approaches to personalized medicine, (2) multi-perspective studies of the benefits and costs of personalized medicine, and (3) the role of behavior in the value of personalized medicine.
个性化医疗最好从一个广泛的角度来看待,即试图利用病人的信息来改善护理。虽然“个性化医疗”往往强调遗传信息的价值,但基于患者表型、提供者和系统层面因素的个性化护理的传统临床方法不应被忽视。随着对这些不同的个性化方法的研究,成本效益分析等工具可以为这些方法的价值、实施和传播策略以及未来研究的优先事项提供重要的见解。如果这些分析认识到患者和提供者的行为是治疗价值的基本决定因素,特别是患者因素可能对治疗价值和干预以改善决策的需要有很大影响,那么这些分析可能是最有见地的。这些评论提出了个性化医疗经济分析的三个主要机会领域:(1)个性化医疗的传统临床方法,(2)个性化医疗收益和成本的多视角研究,以及(3)行为在个性化医疗价值中的作用。
{"title":"Opportunities in the Economics of Personalized Health Care and Prevention","authors":"D. Meltzer","doi":"10.1515/fhep-2013-0012","DOIUrl":"https://doi.org/10.1515/fhep-2013-0012","url":null,"abstract":"Abstract Personalized medicine is best viewed from a broad perspective of trying to use information about a patient to improve care. While “personalized medicine” often emphasizes the value of genetic information, traditional clinical approaches to personalizing care based on patient phenotype, provider and system-level factors should not be neglected. As these diverse approaches to personalization are examined, tools such as cost-effectiveness analysis can provide important insights into the value of these approaches, strategies for their implementation and dissemination, and priorities for future research. Such analyses are likely to be most insightful if they recognize that patient and provider behaviors are essential determinants of the value of treatments and that patient factors in particular may have large effects on the value of treatments and the need for interventions to improve decision making. These comments suggest three major areas of opportunity for economic analyses of personalized medicine: (1) traditional clinical approaches to personalized medicine, (2) multi-perspective studies of the benefits and costs of personalized medicine, and (3) the role of behavior in the value of personalized medicine.","PeriodicalId":38039,"journal":{"name":"Forum for Health Economics and Policy","volume":"22 1","pages":"S13 - S22"},"PeriodicalIF":0.0,"publicationDate":"2013-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83254126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
The Value of Diagnostic Testing in Personalized Medicine 诊断测试在个体化医疗中的价值
Q3 Economics, Econometrics and Finance Pub Date : 2013-09-01 DOI: 10.1515/fhep-2013-0023
D. Goldman, Charu N. Gupta, E. Vasudeva, K. Trakas, R. Riley, D. Lakdawalla, D. Agus, N. Sood, A. Jena, T. Philipson
Abstract Personalized medicine – the targeting of therapies to individuals on the basis of their biological, clinical, or genetic characteristics – is thought to have the potential to transform health care. While much emphasis has been placed on the value of personalized therapies, less attention has been paid to the value generated by the diagnostic tests that direct patients to those targeted treatments. This paper presents a framework derived from information economics for assessing the value of diagnostics. We demonstrate, via a case study, that the social value of such diagnostics can be very large, both by avoiding unnecessary treatment and by identifying patients who otherwise would not get treated. Despite the potential social benefits, diagnostic development has been discouraged by cost-based, rather than value-based, reimbursement.
个性化医疗——根据个体的生物学、临床或遗传特征对其进行靶向治疗——被认为具有改变医疗保健的潜力。虽然很多人强调个性化治疗的价值,但很少有人关注引导患者接受这些针对性治疗的诊断测试所产生的价值。本文提出了一个源自信息经济学的框架,用于评估诊断的价值。我们通过一个案例研究证明,这种诊断的社会价值可以非常大,既可以避免不必要的治疗,也可以识别出本来不会得到治疗的患者。尽管有潜在的社会效益,但基于成本而不是基于价值的报销阻碍了诊断的发展。
{"title":"The Value of Diagnostic Testing in Personalized Medicine","authors":"D. Goldman, Charu N. Gupta, E. Vasudeva, K. Trakas, R. Riley, D. Lakdawalla, D. Agus, N. Sood, A. Jena, T. Philipson","doi":"10.1515/fhep-2013-0023","DOIUrl":"https://doi.org/10.1515/fhep-2013-0023","url":null,"abstract":"Abstract Personalized medicine – the targeting of therapies to individuals on the basis of their biological, clinical, or genetic characteristics – is thought to have the potential to transform health care. While much emphasis has been placed on the value of personalized therapies, less attention has been paid to the value generated by the diagnostic tests that direct patients to those targeted treatments. This paper presents a framework derived from information economics for assessing the value of diagnostics. We demonstrate, via a case study, that the social value of such diagnostics can be very large, both by avoiding unnecessary treatment and by identifying patients who otherwise would not get treated. Despite the potential social benefits, diagnostic development has been discouraged by cost-based, rather than value-based, reimbursement.","PeriodicalId":38039,"journal":{"name":"Forum for Health Economics and Policy","volume":"16 1","pages":"S87 - S99"},"PeriodicalIF":0.0,"publicationDate":"2013-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88608162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 21
Personalized Medicine in the Context of Comparative Effectiveness Research 比较有效性研究背景下的个体化医疗
Q3 Economics, Econometrics and Finance Pub Date : 2013-09-01 DOI: 10.1515/fhep-2013-0009
A. Basu
Abstract The world of patient-centered outcomes research (PCOR) seems to bridge the previously disjointed worlds of comparative effectiveness research (CER) and personalized medicine (PM). Indeed, theoretical reasoning on how information on medical quality should inform decision making, both at the individual and the policy level, reveals that personalized information on the value of medical products is critical for improving decision making at all levels. However, challenges to generating, evaluating and translating evidence that might lead to personalization need to be critically assessed. In this paper, I discuss two different concepts of personalized medicine – passive personalization (PPM) and active personalization (APM) that are important to distinguish in order to invest efficiently in PCOR and develop objective evidence on the value of personalization that will aid in its translation. APM constitutes the process of actively seeking identifiers, which can be genotypical, phenotypical or even environmental, that can be used to differentiate between the marginal benefits of treatment across patients. In contrast, PPM involves a passive approach to personalization where, in the absence of explicit research to discover identifiers, patients and physicians “learn by doing” mostly due to the repeated use of similar products on similar patients. Benchmarking the current state of PPM sets the bar to which the expected value of any new APM agenda should be evaluated. Exploring processes that enable PPM in practice can help discover new APM agendas, such as those based on developing predictive algorithms based on clinical, phenotypical and preference data, which may be more efficient that trying to develop expensive genetic tests. It can also identify scenarios or subgroups of patients where genomic research would be most valuable since alternative prediction algorithms were difficult to develop in those settings. Two clinical scenarios are discussed where PPM was explored through novel econometric methods. Related discussions around exploring PPM processes, multi-dimensionality of outcomes, and a balanced agenda for future research on personalization follow.
以患者为中心的结果研究(PCOR)的世界似乎连接了以前脱节的比较有效性研究(CER)和个性化医疗(PM)的世界。事实上,关于医疗质量信息应如何在个人和政策层面为决策提供信息的理论推理表明,关于医疗产品价值的个性化信息对于改善各级决策至关重要。然而,需要对可能导致个性化的证据的生成、评估和翻译所面临的挑战进行批判性评估。在本文中,我讨论了个性化医疗的两个不同概念-被动个性化(PPM)和主动个性化(APM),这对于区分有效地投资于PCOR和开发个性化价值的客观证据非常重要,这将有助于其翻译。APM构成了积极寻找标识符的过程,这些标识符可以是基因型的、表型的,甚至是环境的,可以用来区分不同患者治疗的边际效益。相比之下,PPM涉及一种被动的个性化方法,在缺乏明确的研究来发现标识符的情况下,患者和医生“边做边学”,主要是因为在类似的患者身上重复使用类似的产品。对PPM的当前状态进行基准测试为任何新的APM议程的期望值设定了标准。探索在实践中实现PPM的流程可以帮助发现新的APM议程,例如基于临床、表型和偏好数据开发预测算法的议程,这可能比开发昂贵的基因测试更有效。它还可以确定基因组研究最有价值的情景或患者亚组,因为在这些情况下很难开发替代预测算法。讨论了两种临床情况,其中PPM通过新颖的计量经济学方法进行了探索。接下来将围绕探索PPM过程、结果的多维性以及个性化未来研究的平衡议程进行相关讨论。
{"title":"Personalized Medicine in the Context of Comparative Effectiveness Research","authors":"A. Basu","doi":"10.1515/fhep-2013-0009","DOIUrl":"https://doi.org/10.1515/fhep-2013-0009","url":null,"abstract":"Abstract The world of patient-centered outcomes research (PCOR) seems to bridge the previously disjointed worlds of comparative effectiveness research (CER) and personalized medicine (PM). Indeed, theoretical reasoning on how information on medical quality should inform decision making, both at the individual and the policy level, reveals that personalized information on the value of medical products is critical for improving decision making at all levels. However, challenges to generating, evaluating and translating evidence that might lead to personalization need to be critically assessed. In this paper, I discuss two different concepts of personalized medicine – passive personalization (PPM) and active personalization (APM) that are important to distinguish in order to invest efficiently in PCOR and develop objective evidence on the value of personalization that will aid in its translation. APM constitutes the process of actively seeking identifiers, which can be genotypical, phenotypical or even environmental, that can be used to differentiate between the marginal benefits of treatment across patients. In contrast, PPM involves a passive approach to personalization where, in the absence of explicit research to discover identifiers, patients and physicians “learn by doing” mostly due to the repeated use of similar products on similar patients. Benchmarking the current state of PPM sets the bar to which the expected value of any new APM agenda should be evaluated. Exploring processes that enable PPM in practice can help discover new APM agendas, such as those based on developing predictive algorithms based on clinical, phenotypical and preference data, which may be more efficient that trying to develop expensive genetic tests. It can also identify scenarios or subgroups of patients where genomic research would be most valuable since alternative prediction algorithms were difficult to develop in those settings. Two clinical scenarios are discussed where PPM was explored through novel econometric methods. Related discussions around exploring PPM processes, multi-dimensionality of outcomes, and a balanced agenda for future research on personalization follow.","PeriodicalId":38039,"journal":{"name":"Forum for Health Economics and Policy","volume":"85 1","pages":"S73 - S86"},"PeriodicalIF":0.0,"publicationDate":"2013-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78940140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
The Economics of Personalization in Prevention and Public Health 预防和公共卫生中的个性化经济学
Q3 Economics, Econometrics and Finance Pub Date : 2013-09-01 DOI: 10.1515/fhep-2013-0011
D. Kenkel, Hua Wang
Abstract Personalized prevention uses family history and predictive genetic testing to identify people at high risk of serious diseases. The availability of predictive genetic tests is a newer and still-developing phenomenon. Many observers see tremendous potential for personalized prevention to improve public health. At the same time, the emergence of these new markets raises familiar health policy concerns about costs, cost-effectiveness, and health disparities. This paper first discusses an economic framework for the analysis of personalized prevention. On the demand side, consumers use personalized prevention as a form of information that allows them to make better choices about prevention, including medical care and health behaviors like diet and exercise. On the supply side, an interplay of complex market forces and regulations will determine the prices, advertising, and insurance coverage of predictive genetic tests. Beyond the question of whether health insurance will cover the costs of predictive genetic tests, there is a great deal of concern about whether consumers’ use of genetic tests might place them at risk of genetic discrimination or might lead to adverse selection. The paper also reports descriptive analysis of data from the 2000, 2005, and 2010 National Health Interview Surveys on the use of predictive genetic tests. The empirical analysis documents large socioeconomic status-related disparities in consumers having heard of genetic tests: for example, consumers with less schooling, Blacks, and Hispanics were substantially less likely to have heard of genetic tests. Evidence from other empirical studies provides little evidence that genetic testing leads to genetic discrimination in insurance markets. There is more evidence suggesting adverse selection, where genetic testing leads consumers to purchase long-term care insurance. The paper concludes with some preliminary thoughts about important directions for future research. The goal of the paper is to review relevant research to help develop an economic approach and social science research agenda into the determinants and consequences of genetic tests for prevention.
个性化预防利用家族史和预测性基因检测来识别严重疾病的高危人群。预测性基因测试的可用性是一个较新的和仍在发展的现象。许多观察人士看到了个性化预防改善公共卫生的巨大潜力。与此同时,这些新市场的出现引起了人们对成本、成本效益和卫生差距的熟悉的卫生政策关切。本文首先讨论了个性化预防分析的经济框架。在需求方,消费者使用个性化预防作为一种信息形式,使他们能够更好地选择预防,包括医疗保健和健康行为,如饮食和锻炼。在供应方面,复杂的市场力量和法规的相互作用将决定预测性基因测试的价格、广告和保险范围。除了健康保险是否会支付预测性基因检测费用的问题之外,人们还非常关注消费者使用基因检测是否会使他们面临基因歧视的风险或可能导致逆向选择。该论文还报告了对2000年、2005年和2010年全国健康访谈调查中使用预测性基因测试的数据的描述性分析。实证分析表明,在听说过基因检测的消费者中,与社会经济地位相关的巨大差异:例如,受教育程度较低的消费者、黑人和西班牙裔人听说过基因检测的可能性大大降低。来自其他实证研究的证据几乎没有证明基因检测导致保险市场的基因歧视。有更多的证据表明存在逆向选择,基因检测导致消费者购买长期护理保险。最后,对今后的重要研究方向提出了一些初步的思考。这篇论文的目标是回顾相关的研究,以帮助制定一种经济方法和社会科学研究议程,以研究基因检测用于预防的决定因素和后果。
{"title":"The Economics of Personalization in Prevention and Public Health","authors":"D. Kenkel, Hua Wang","doi":"10.1515/fhep-2013-0011","DOIUrl":"https://doi.org/10.1515/fhep-2013-0011","url":null,"abstract":"Abstract Personalized prevention uses family history and predictive genetic testing to identify people at high risk of serious diseases. The availability of predictive genetic tests is a newer and still-developing phenomenon. Many observers see tremendous potential for personalized prevention to improve public health. At the same time, the emergence of these new markets raises familiar health policy concerns about costs, cost-effectiveness, and health disparities. This paper first discusses an economic framework for the analysis of personalized prevention. On the demand side, consumers use personalized prevention as a form of information that allows them to make better choices about prevention, including medical care and health behaviors like diet and exercise. On the supply side, an interplay of complex market forces and regulations will determine the prices, advertising, and insurance coverage of predictive genetic tests. Beyond the question of whether health insurance will cover the costs of predictive genetic tests, there is a great deal of concern about whether consumers’ use of genetic tests might place them at risk of genetic discrimination or might lead to adverse selection. The paper also reports descriptive analysis of data from the 2000, 2005, and 2010 National Health Interview Surveys on the use of predictive genetic tests. The empirical analysis documents large socioeconomic status-related disparities in consumers having heard of genetic tests: for example, consumers with less schooling, Blacks, and Hispanics were substantially less likely to have heard of genetic tests. Evidence from other empirical studies provides little evidence that genetic testing leads to genetic discrimination in insurance markets. There is more evidence suggesting adverse selection, where genetic testing leads consumers to purchase long-term care insurance. The paper concludes with some preliminary thoughts about important directions for future research. The goal of the paper is to review relevant research to help develop an economic approach and social science research agenda into the determinants and consequences of genetic tests for prevention.","PeriodicalId":38039,"journal":{"name":"Forum for Health Economics and Policy","volume":"75 1","pages":"S53 - S71"},"PeriodicalIF":0.0,"publicationDate":"2013-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80107589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Economics of Personalized Health Care and Prevention: Introduction 个性化卫生保健和预防经济学:导论
Q3 Economics, Econometrics and Finance Pub Date : 2013-09-01 DOI: 10.1515/fhep-2013-0018
Gregory Bloss, J. Haaga
{"title":"Economics of Personalized Health Care and Prevention: Introduction","authors":"Gregory Bloss, J. Haaga","doi":"10.1515/fhep-2013-0018","DOIUrl":"https://doi.org/10.1515/fhep-2013-0018","url":null,"abstract":"","PeriodicalId":38039,"journal":{"name":"Forum for Health Economics and Policy","volume":"90 1","pages":"S1 - S11"},"PeriodicalIF":0.0,"publicationDate":"2013-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78543040","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
期刊
Forum for Health Economics and Policy
全部 Acc. Chem. Res. ACS Applied Bio Materials ACS Appl. Electron. Mater. ACS Appl. Energy Mater. ACS Appl. Mater. Interfaces ACS Appl. Nano Mater. ACS Appl. Polym. Mater. ACS BIOMATER-SCI ENG ACS Catal. ACS Cent. Sci. ACS Chem. Biol. ACS Chemical Health & Safety ACS Chem. Neurosci. ACS Comb. Sci. ACS Earth Space Chem. ACS Energy Lett. ACS Infect. Dis. ACS Macro Lett. ACS Mater. Lett. ACS Med. Chem. Lett. ACS Nano ACS Omega ACS Photonics ACS Sens. ACS Sustainable Chem. Eng. ACS Synth. Biol. Anal. Chem. BIOCHEMISTRY-US Bioconjugate Chem. BIOMACROMOLECULES Chem. Res. Toxicol. Chem. Rev. Chem. Mater. CRYST GROWTH DES ENERG FUEL Environ. Sci. Technol. Environ. Sci. Technol. Lett. Eur. J. Inorg. Chem. IND ENG CHEM RES Inorg. Chem. J. Agric. Food. Chem. J. Chem. Eng. Data J. Chem. Educ. J. Chem. Inf. Model. J. Chem. Theory Comput. J. Med. Chem. J. Nat. Prod. J PROTEOME RES J. Am. Chem. Soc. LANGMUIR MACROMOLECULES Mol. Pharmaceutics Nano Lett. Org. Lett. ORG PROCESS RES DEV ORGANOMETALLICS J. Org. Chem. J. Phys. Chem. J. Phys. Chem. A J. Phys. Chem. B J. Phys. Chem. C J. Phys. Chem. Lett. Analyst Anal. Methods Biomater. Sci. Catal. Sci. Technol. Chem. Commun. Chem. Soc. Rev. CHEM EDUC RES PRACT CRYSTENGCOMM Dalton Trans. Energy Environ. Sci. ENVIRON SCI-NANO ENVIRON SCI-PROC IMP ENVIRON SCI-WAT RES Faraday Discuss. Food Funct. Green Chem. Inorg. Chem. Front. Integr. Biol. J. Anal. At. Spectrom. J. Mater. Chem. A J. Mater. Chem. B J. Mater. Chem. C Lab Chip Mater. Chem. Front. Mater. Horiz. MEDCHEMCOMM Metallomics Mol. Biosyst. Mol. Syst. Des. Eng. Nanoscale Nanoscale Horiz. Nat. Prod. Rep. New J. Chem. Org. Biomol. Chem. Org. Chem. Front. PHOTOCH PHOTOBIO SCI PCCP Polym. Chem.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1