Erasmus School of Health Policy & Management, Erasmus University Rotterdam, Rotterdam, the Netherlands.
Professional Health Solutions & Services Department, Philips Research, Eindhoven, the Netherlands.
PLoS One. 2019 Jun 20;14(6):e0218083. doi: 10.1371/journal.pone.0218083. eCollection 2019.
Value of information (VOI) analysis provides information on opportunity cost of a decision in healthcare by estimating the cost of reducing parametric uncertainty and quantifying the value of generating additional evidence. This study is an application of the VOI methodology to the problem of choosing between home telemonitoring and nurse telephone support over usual care in chronic heart failure management in the Netherlands.
The expected value of perfect information (EVPI) and the expected value of partially perfect information (EVPPI) analyses were based on an informal threshold of €20K per quality-adjusted life-year. These VOI-analyses were applied to a probabilistic Markov model comparing the 20-year costs and effects in three interventions. The EVPPI explored the value of decision uncertainty caused by the following group of parameters: treatment-specific transition probabilities between New York Heart Association (NYHA) defined disease states, utilities associated with the disease states, number of hospitalizations and ER visits, health state specific costs, and the distribution of patients per NYHA group. We performed the analysis for two population sizes in the Netherlands-patients in all NYHA classes of severity, and patients in NYHA IV class only.
The population EVPI for an effective population of 2,841,567 CHF patients in All NYHA classes of severity over the next 20 years is more than €4.5B, implying that further research is highly cost-effective. In the NYHA IV only analysis, for the effective population of 208,003 patients over next 20 years, the population EVPI at the same informal threshold is approx. €590M. The EVPPI analysis showed that the only relevant group of parameters that contribute to the overall decision uncertainty are transition probabilities, in both All NYHA and NYHA IV analyses.
Results of our VOI exercise show that the cost of uncertainty regarding the decision on reimbursement of telehealth interventions for chronic heart failure patients is high in the Netherlands, and that future research is needed, mainly on the transition probabilities.
价值信息（VOI）分析通过估计减少参数不确定性的成本和量化产生额外证据的价值，为医疗保健中的决策机会成本提供信息。本研究将 VOI 方法应用于荷兰慢性心力衰竭管理中家庭远程监测与护士电话支持相对于常规护理选择的问题。
完全信息的期望价值（EVPI）和部分完美信息的期望价值（EVPPI）分析基于每质量调整生命年 20 千欧元的非正式阈值。这些 VOI 分析应用于比较三种干预措施 20 年成本和效果的概率马尔可夫模型。EVPPI 探讨了由以下参数组引起的决策不确定性的价值：纽约心脏协会（NYHA）定义的疾病状态之间的特定治疗转移概率、与疾病状态相关的效用、住院和急诊就诊次数、特定健康状态的成本以及 NYHA 组的患者分布。我们为荷兰的两个人群大小执行了分析 - 所有 NYHA 严重程度的患者和仅 NYHA IV 类的患者。
对于未来 20 年所有 NYHA 严重程度的 2841567 例心力衰竭患者的有效人群，超过 45 亿欧元的人群 EVPI 表明进一步研究具有高度成本效益。在仅 NYHA IV 分析中，对于未来 20 年的 208003 名有效患者，相同非正式阈值的人群 EVPI 约为 5900 万欧元。EVPPI 分析表明，仅在所有 NYHA 和 NYHA IV 分析中，导致整体决策不确定性的相关参数组是转移概率。
我们的 VOI 研究结果表明，荷兰对远程医疗干预治疗慢性心力衰竭患者的报销决策的不确定性成本很高，需要开展更多研究，主要是关于转移概率。
