收益时间表示对干预措施的收益何时超过成本的估计。对于具有递延收益但前期危害的干预措施,它对于利益-损害决策特别有用。这项研究的目的是扩大收益时间的应用范围,并提供一个在决策分析模型中使用的示例。
根据估计的10年心血管风险的不同水平,三个临床相关的患者小插曲(10%,15%,20%)被开发。采用健康服务观点和生命周期的现有状态转移马尔可夫模型进行了调整,以包括与持续使用他汀类药物相关的3个直接治疗无效性(DTD)水平:0.005、0.01和0.015。对于每个小插图和DTD,我们计算了一系列输出,包括包含和不包括医疗保健成本的支付时间。
对于10%的10年心血管风险(插图1)与低水平的DTD(0.005),不包括成本时的收益时间为8.5年,包括成本时的收益时间为16年。随着心血管疾病的基线风险增加,支付时间缩短。对于15%的心血管风险(插图2)和低水平的DTD,回报时间是5.5年和9.5年,分别。对于20%的心血管风险(插图3),回报时间为4.2年和7.2年,分别。对于每个小插图的更高水平的DTD,回报时间延长了,在某些情况下,干预从未得到回报,导致患者预期的净伤害。
这项研究显示了如何将收益时间应用于现有的决策分析模型,并用于补充现有措施以指导医疗保健决策。
The payoff time represents an estimate of when the benefits of an intervention outweigh the costs. It is particularly useful for benefit-harm decision making for interventions that have deferred benefits but upfront harms. The aim of this study was to expand the application of the payoff time and provide an example of its use within a decision-analytic model.
Three clinically relevant patient vignettes based on varying levels of estimated 10-year cardiovascular risk (10%, 15%, 20%) were developed. An existing state-transition Markov model taking a health service perspective and a life-time horizon was adapted to include 3 levels of direct treatment disutility (DTD) associated with ongoing statin use: 0.005, 0.01, and 0.015. For each vignette and DTD we calculated a range of outputs including the payoff time inclusive and exclusive of healthcare costs.
For a 10% 10-year cardiovascular risk (vignette 1) with low-levels of DTD (0.005), the payoff time was 8.5 years when costs were excluded and 16 years when costs were included. As the baseline risk of cardiovascular increased, the payoff time shortened. For a 15% cardiovascular risk (vignette 2) and for a low-level of DTD, the payoff time was 5.5 years and 9.5 years, respectively. For a 20% cardiovascular risk (vignette 3), the payoff time was 4.2 and 7.2 years, respectively. For higher levels of DTDs for each vignette, the payoff time lengthened, and in some instances the intervention never paid off, leading to an expected net harm for patients.
This study has shown how the payoff time can be readily applied to an existing decision-analytic model and be used to complement existing measures to guide healthcare decision making.