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，但每年的医疗保健费用为280亿美元。精神分裂症给患者、家属和社会带来的负担是巨大的。抗精神病药物是治疗精神分裂症的第一线，并帮助一些患有这种疾病的患者过上富有成效和充实的生活。随着第二代抗精神病药物（通常比第一代抗精神病药物贵得多）的出现，这些患者的医疗支出增长稳步上升，令人质疑较新的第二代抗精神病药物相对于老一代抗精神病药物的边际价值。关于药品支出是否可以抵消这些患者昂贵的住院治疗费用，也有模糊的证据。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记录了这一已经脆弱的人群心血管风险增加的证据时。最近发表的NIMH资助的CATIE研究结果进一步推动了这一争论，该研究报告了随机接受第一代抗精神病药物与非典型抗精神病药物的患者之间的持续率等效性。在这种争议面前，仍然有一些关键问题需要回答。这些问题跨越了各种政策，包括现在和未来，影响了范围广泛的药物持有者，主要集中在药物与精神抑制剂的比较有效性，成本和成本效益。只有通过对精神分裂症治疗方案的评估和确定该领域的研究重点进行仔细研究，才能回答这些问题。该提案试图利用经济学、统计学和决策科学中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一个全面的概率微观模拟模型，在精神分裂症提供有关人口水平的成本，有效性和成本效益的药物治疗和治疗算法的信息。这里提出的工作是重要的方法和临床。所提出的方法的进步，将在医疗保健的许多领域的技术评估的主要应用，并希望在许多其他情况下，其潜在的应用提供有价值的见解。临床上，我们的研究结果有可能对精神分裂症的治疗产生重要影响，为医生和患者提供有关治疗结果分布的丰富信息，有助于指导他们做出更明智的治疗选择。此外，信息分析的拟议价值将指导这一领域今后的研究和资源，确定对那些参数的研究优先次序，因为更精确的估计将是最有价值的。面对不断上升的成本和关于新药益处的模糊证据，关于精神分裂症患者使用第二代与第一代抗精神病药物的争议越来越大。在替代药物之间频繁切换表明，没有一种药物可能是最适合患者的。目前对治疗效果的估计存在巨大的不确定性，这意味着未来在这一领域的研究价值可能是巨大的。为了解决这些问题，拟议的工作旨在开发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，并在该领域进行信息价值和未来研究分析的价值。

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.