RAND Corporation, Santa Monica, CA.
Center for the Evaluation of Value and Risk in Health, Institute of Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, MA.
Spine (Phila Pa 1976). 2019 Oct 15;44(20):1456-1464. doi: 10.1097/BRS.0000000000003097.
Markov model.
Examine the 1-year effectiveness and cost-effectiveness (societal and payer perspectives) of adding nonpharmacologic interventions for chronic low back pain (CLBP) to usual care using a decision analytic model-based approach.
Treatment guidelines now recommend many safe and effective nonpharmacologic interventions for CLBP. However, little is known regarding their effectiveness in subpopulations (e.g., high-impact chronic pain patients), nor about their cost-effectiveness.
The model included four health states: high-impact chronic pain (substantial activity limitations); no pain; and two others without activity limitations, but with higher (moderate-impact) or lower (low-impact) pain. We estimated intervention-specific transition probabilities for these health states using individual patient-level data from 10 large randomized trials covering 17 nonpharmacologic therapies. The model was run for nine 6-week cycles to approximate a 1-year time horizon. Quality-adjusted life-year weights were based on six-dimensional health state short form scores; healthcare costs were based on 2003 to 2015 Medical Expenditure Panel Survey data; and lost productivity costs used in the societal perspective were based on reported absenteeism. Results were generated for two target populations: (1) a typical baseline mix of patients with CLBP (25% low-impact, 35% moderate-impact, and 40% high-impact chronic pain) and (2) high-impact chronic pain patients.
From the societal perspective, all but two of the therapies were cost effective (<$50,000/quality-adjusted life-year) for a typical patient mix and most were cost saving. From the payer perspective fewer were cost saving, but the same number was cost-effective. Assuming all patients in the model have high-impact chronic pain increases the effectiveness and cost-effectiveness of most, but not all, therapies indicating that substantial benefits are possible in this subpopulation.
Modeling leverages the evidence produced from clinical trials to provide more information than is available in the published studies. We recommend modeling for all existing studies of nonpharmacologic interventions for CLBP.
马尔可夫模型。
采用基于决策分析模型的方法,考察在常规护理基础上增加慢性下背痛(CLBP)非药物干预措施的 1 年效果和成本效益(社会和支付方视角)。
治疗指南现在推荐了许多安全有效的非药物干预措施用于治疗 CLBP。然而,对于这些干预措施在亚人群中的有效性(例如,高影响慢性疼痛患者)以及它们的成本效益知之甚少。
该模型包括四个健康状态:高影响慢性疼痛(严重活动受限);无疼痛;以及另外两个没有活动限制,但疼痛程度较高(中度影响)或较低(低度影响)。我们使用来自 10 项大型随机试验的个体患者水平数据来估计这些健康状态的特定干预过渡概率,这些试验涵盖了 17 种非药物治疗方法。模型运行了九个 6 周的周期,以近似 1 年的时间范围。质量调整生命年权重基于六维度健康状态简表评分;医疗保健成本基于 2003 年至 2015 年医疗支出面板调查数据;社会视角下使用的生产力损失成本基于报告的旷工。结果是针对两个目标人群生成的:(1)具有 CLBP 的典型基线混合患者(25%低度影响,35%中度影响,40%高度影响慢性疼痛);(2)高度影响慢性疼痛患者。
从社会角度来看,对于典型的患者组合,除了两种疗法之外,所有疗法的成本效益都在 50,000 美元/质量调整生命年以下,并且大多数都是成本节约的。从支付方的角度来看,虽然成本节约的疗法较少,但同样数量的疗法具有成本效益。假设模型中的所有患者都患有高度影响的慢性疼痛,这会增加大多数但不是所有疗法的有效性和成本效益,表明在这个亚人群中可能会有实质性的收益。
建模利用从临床试验中产生的证据提供了比已发表研究中更多的信息。我们建议对所有现有的慢性下背痛非药物干预研究进行建模。
4 级。