Cost-effectiveness of automated telephone outreach in patients with lung disease

描述（由申请人提供）： PEANUT（关于新疗法或未充分使用疗法的电话教育）试验是一项正在进行的NHLBI资助的随机、对照、有效性研究，使用交互式语音电话应答（IVR）技术作为低成本干预措施，以提高治疗依从性。超过14，000名受试者的初步证据表明IVR干预的积极作用，因此我们现在的目标是通过使用试验数据和参与者的进一步纵向随访数据对干预进行全面的经济评估来扩展这项母研究。对这一干预措施的成本和相对资金价值进行正式和严格的分析，对于将调查结果明智地转化为其他环境至关重要。母研究（PEANUT）包括一项成本分析，该分析将提供关于在其他研究中心开发、实施和复制IVR干预措施的成本的良好信息。我们使用这些辅助资金的主要具体目的是开发和完善一个决策模型，该模型可用于估计母试验的成本和收益。此外，我们的目标是估计IVR技术的投资回报率（即成本补偿），估计和价值的生活质量和公用事业的变化，生产力的变化，和提供商的负担使用的信息框架的价值。我们的分析将从付款人的角度进行。我们将建立一个决策模型（马尔可夫模型）。决策模型将主要从母试验中获得的估计值填充，但也将包括从患者调查中获得的进一步数据，以及来自文献的事件发生率估计值和对KPNW哮喘和COPD成员的额外数据分析。我们将对母研究中包含的约12，000人进行调查;这些调查结果将为决策模型提供转移概率，并将提供与干预相关的生活质量估计（效用）和生产力变化。我们的研究结果将使决策者能够获得关键信息，这些信息明确详细说明了实施IVR系统所带来的权衡，方法是将结果纳入一个在疾病状态和干预措施之间具有可比性的指标（成本/QALY）。在卫生保健预算有限的时代，这种疾病状态之间的比较很重要;如果钱花在一种干预措施上，它们就不能用于其他（可能更有效的）用途。投资回报率将使决策者能够评估干预措施的可承受性。我们的研究将与母研究平行进行，并将利用项目管理、数据分析师和研究者工作的可观规模经济。我们计划在18个月内完成研究，与母试验同时进行。公共卫生相关性：这项研究是一项随机研究的延伸，该研究正在测试自动交互式电话对哮喘和其他肺部疾病患者增加药物依从性的影响。我们将对自动电话的成本效益（效率）进行评估。(End摘要）

DESCRIPTION (provided by applicant): The PEANUT (Phone Education About New or Underused Therapies) Trial is an ongoing, NHLBI-funded randomized, controlled, effectiveness study that uses interactive voice-telephone response (IVR) technology as a low-cost intervention to enhance therapeutic adherence. Preliminary evidence in more than 14,000 subjects suggests a positive effect of the IVR intervention, so we now aim to extend this parent study by performing a full economic evaluation of the intervention using data from the trial and further longitudinal follow-up data on the participants. A formal and rigorous analysis of the costs and relative value for money of this intervention is crucial to the informed translation of findings to other settings. The parent study (PEANUT) includes a cost analysis that will provide good information on the costs of developing, implementing and replicating the IVR intervention at other sites. Our primary specific aim with these ancillary funds is to develop and refine a decision model that can be used to estimate the costs and benefits from the parent trial. Additionally, we aim to estimate the return-on-investment of IVR technology (i.e. cost-offsets), estimate and value quality of life and utility changes, productivity changes, and provider burden using a value of information framework. Our analysis will take the payer perspective. We will construct a decision model (Markov model). The decision model will be populated largely from estimates gained from the parent trial, but will also include further data gained from patient survey, and event rate estimates from the literature and additional data analysis on KPNW members with asthma and COPD. We will conduct a survey of about 12,000 individuals included in the parent study; these survey results will inform transition probabilities for the decision model, and will provide quality of life estimates (utilities) and productivity changes associated with the intervention. Our results will allow decision makers access to critical information that explicitly detail the trade-offs that come with implementing the IVR system by putting the results into a metric (cost/QALY) that is comparable across disease sates and interventions. This comparison across disease states is important in the era of constrained budgets in health care; if monies are spent on one intervention, they are not available for other (potentially more efficient) uses. The return-on-investment will allow decision makers to assess the affordability of the intervention. Our study will be carried out in parallel to the parent study, and will take advantage of the considerable economies of scale that exist with project management, data analyst, and investigator effort. We plan to complete the study within an 18-month period, to run concurrently with the parent trial. PUBLIC HEALTH RELEVANCE: This study is an extension of a randomized study that is testing the effect of automated, interactive telephone calls on increasing medication adherence in patients with asthma and other lung diseases. We will carry out an evaluation of the cost-effectiveness (efficiency) of the automated phone calls. (End of Abstract)