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Value of information analysis in telehealth for chronic heart failure management

OBJECTIVES: 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 probl...

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Autores principales: Grustam, Andrija S., Buyukkaramikli, Nasuh, Koymans, Ron, Vrijhoef, Hubertus J. M., Severens, Johan L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6586290/
https://www.ncbi.nlm.nih.gov/pubmed/31220101
http://dx.doi.org/10.1371/journal.pone.0218083
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author Grustam, Andrija S.
Buyukkaramikli, Nasuh
Koymans, Ron
Vrijhoef, Hubertus J. M.
Severens, Johan L.
author_facet Grustam, Andrija S.
Buyukkaramikli, Nasuh
Koymans, Ron
Vrijhoef, Hubertus J. M.
Severens, Johan L.
author_sort Grustam, Andrija S.
collection PubMed
description OBJECTIVES: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.
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spelling pubmed-65862902019-06-28 Value of information analysis in telehealth for chronic heart failure management Grustam, Andrija S. Buyukkaramikli, Nasuh Koymans, Ron Vrijhoef, Hubertus J. M. Severens, Johan L. PLoS One Research Article OBJECTIVES: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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. Public Library of Science 2019-06-20 /pmc/articles/PMC6586290/ /pubmed/31220101 http://dx.doi.org/10.1371/journal.pone.0218083 Text en © 2019 Grustam et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Grustam, Andrija S.
Buyukkaramikli, Nasuh
Koymans, Ron
Vrijhoef, Hubertus J. M.
Severens, Johan L.
Value of information analysis in telehealth for chronic heart failure management
title Value of information analysis in telehealth for chronic heart failure management
title_full Value of information analysis in telehealth for chronic heart failure management
title_fullStr Value of information analysis in telehealth for chronic heart failure management
title_full_unstemmed Value of information analysis in telehealth for chronic heart failure management
title_short Value of information analysis in telehealth for chronic heart failure management
title_sort value of information analysis in telehealth for chronic heart failure management
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6586290/
https://www.ncbi.nlm.nih.gov/pubmed/31220101
http://dx.doi.org/10.1371/journal.pone.0218083
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