Abstract
ObjectivesValue 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.MethodsThe 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.ResultsThe 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.ConclusionsResults 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.
Highlights
Economic evaluation, or cost-effectiveness analysis, resorts to modeling in order to analyze costs and outcomes of technology implementation in healthcare, synthesize different types of data, and extrapolate short term trial results to longer term
Results of our Value of Information (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
Results of the Individual expected value of perfect information (EVPI) analysis (Fig 5) show that where there is more uncertainty, the probability of error will increase and expected opportunity loss and EVPI will be higher. This is because the variance of net monetary benefits increases with the increase of WTP threshold, and as we compare three options (i.e., Home Telemonitoring (HTM), Nurse Telephone Support (NTS), and UC) the variability and uncertainty are greater than when comparing two alternatives
Summary
Cost-effectiveness analysis, resorts to modeling in order to analyze costs and outcomes of technology implementation in healthcare, synthesize different types of data, and extrapolate short term trial results to longer term. Those analytical models were deterministic only, but due to irrelevance of p-values and inference in medical decision making [1], the probabilistic models were developed and the Probabilistic Sensitivity Analysis (PSA) emerged to represent parameter uncertainty. The Value of Information (VOI) analysis gained traction in economic evaluation in healthcare [6,7,8]
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