A Comprehensive Probabilistic-Micro-Simulation Model to Assess Cost-Effectiveness

描述（由申请人提供）：精神分裂症影响约1.3%的人口，但每年造成280亿美元的卫生保健费用。精神分裂症给患者、家属和社会带来了巨大的负担。抗精神病药物是治疗精神分裂症的第一线药物，已经帮助一些患有这种疾病的患者过上了富有成效和充实的生活。随着第二代抗精神病药物的出现，这些药物通常比第一代抗精神病药物昂贵得多，这些患者的医疗支出稳步增长，这使得新的第二代抗精神病药物（非典型药物）相对于老一代抗精神病药物的边际价值受到质疑。关于药物支出是否可以抵消这些患者昂贵的住院治疗，也有模棱两可的证据。因此，关于使用这些更新和更昂贵的药物的争议越来越多，特别是当其中一些药物最近有证据表明这些已经脆弱的人群心血管风险增加时。NIMH资助的CATIE研究最近发表的结果进一步加剧了这一争论，该研究报告了随机接受第一代抗精神病药物和非典型抗精神病药物的患者之间的持续率相等。在存在这样的争议的情况下，仍然有一些关键的问题需要回答。这些问题涉及当前和未来的各种政策，影响广泛的利益相关者，主要关注非典型药物与神经抑制药的比较有效性、成本和成本效益。这些问题只能通过仔细研究评估精神分裂症的治疗方案和确定该领域的研究重点来回答。本提案试图用经济学、统计学和决策科学的创新方法来解决这些问题。在这项工作中，我们建议开发和应用精神分裂症的综合概率微观模拟模型，以提供有关药物治疗和治疗算法的人口水平成本，有效性和成本效益的信息。这里提出的工作是重要的方法和临床。提出的方法上的进步将在卫生保健的许多领域对技术评估有重要应用，并希望为其在许多其他情况下的潜在应用提供有价值的见解。在临床上，我们的发现有可能对精神分裂症的治疗产生重要影响，为医生和他们的患者提供丰富的治疗结果分布信息，帮助他们做出更明智的治疗选择。此外，资料分析的拟议价值将指导这一领域今后的研究和资源，办法是确定对那些最有价值的更精确估计的参数的研究优先次序。精神分裂症患者使用第二代抗精神病药物与第一代抗精神病药物的争议越来越多，因为成本不断上升，而且关于新药的益处证据不明确。在替代药物之间频繁切换表明没有一种药物可能对患者是最佳的。目前对治疗效果的估计存在巨大的不确定性，这意味着该领域未来研究的价值可能是巨大的。为了解决这些问题，本研究旨在建立一个全面的微观模拟模型，以评估精神分裂症替代药物治疗算法的成本、有效性和成本效益，并对该领域的信息价值和未来研究价值进行分析。

DESCRIPTION (provided by applicant): Schizophrenia affects about 1.3% of the population and yet is responsible for US$28 billion in annual health care costs. The burden of schizophrenia to the patients, their family members and to the society is large. Antipsychotic drugs are the first line of treatment of schizophrenia and have helped some patients with this disease to lead productive and fulfilling lives. With the advent of the second-generation of antipsychotic drugs, which are typically much more expensive than first generation antipsychotics, the growth in medical expenditures among these patients have risen steadily, calling into question the marginal value of the newer second-generation antipsychotic drugs (atypicals) over the older generation neuroleptics. There is also ambiguous evidence on whether pharmaceutical expenditures can offset the expensive inpatient care for these patients. Consequently, controversies are growing regarding the use of these newer and more expensive drugs, especially when some of them have recently documented evidence of increasing cardiovascular risks in this already vulnerable population. This debate is further fueled by the recently published results from the NIMH funded CATIE study that reported equivalence of continuation rates between patient randomized to receiving first-generation versus atypical antipsychotic drugs. In the presence of such controversy, there remain crucial questions to be answered. These questions span a variety of policies, both present and future, influence a wide range of stake-holders, and primarily focus on the comparative effectiveness, costs and cost-effectiveness of the atypicals versus the neuroleptics. They can only be answered with careful research on evaluating treatment options in schizophrenia and identifying research priorities in this field. This proposal attempts to address these questions using innovative methods in economics, statistics and decision sciences. In this work, we propose to develop and apply a comprehensive probabilistic micro-simulation model in schizophrenia to provide information about population level costs, effectiveness and cost-effectiveness of pharmacological treatments and treatment algorithms. The work proposed here is important methodologically and clinically. The methodological advancements that are proposed will have major applications for technology assessment in many domains in health care and hope to provide valuable insights for their potential application in many other contexts. Clinically, our findings have the potential to have important implications for the treatment of schizophrenia by providing physicians and their patients with rich information on the distribution of outcomes of treatments that can help guide them in making more informed treatment choices. Furthermore, the proposed value of information analyses will direct future research and resources in this field by identifying research priorities on those parameters where more precise estimates would be most valuable. Controversies are growing regarding the use of second generation versus the first generation antipsychotics by patients with schizophrenia in the face of rising costs and ambiguous evidence on the benefits of the newer drugs. Frequent switching between alternative drugs indicates that no one drug may be optimal for a patient. Enormous uncertainties in current estimates of treatment effect imply that the value of future research in this filed may be substantial. In order to address these questions, the proposed work aims to develop a comprehensive micro-simulation model to assess the costs, effectiveness, cost-effectiveness of alternative pharmacological treatment algorithms in schizophrenia and to conduct value of information and value of future research analyses in this field.