Nicholas K. Schiltz1
1Case Western Reserve University, Cleveland, OH, United States
Synopsis
Comparative and
cost-effectiveness approaches can be used to assess the value of MRI, but these
studies have not traditionally been explored in the ISMRM community. This session
will provide an introduction to comparative and cost-effectiveness research (CER), with
particular focus on decision model approaches.
Topics covered include: best practices for setting up a decision tree model, key measures and interpretation including
incremental-cost effectiveness ratio, and the value of information. At the end
of the session, audience members should know how to create an outline of a model for their own
research questions to assess the value of MRI.
TARGET AUDIENCE
All of ISMRM. This session assumes no knowledge of comparative effectiveness, cost-effectiveness, or decision analysis.OUTCOMES/OBJECTIVES
As a result of attending this course, participants should be able to:
- Classify types of comparative effectiveness research (CER) (randomized trial, observational, and decision models) and contrast CER with efficacy research
- Understand the key components of cost-effectiveness analysis using decision modeling
- Assess what makes a good CER / decision analysis research question
- Explain how to set up a decision model to compare multiple clinical approaches
- Interpret results of a cost-effectiveness analysis including the incremental cost-effectiveness ratio (ICER)
- Apply CER/CEA models to their own research to elucidate the value of MRI.
PURPOSE
Measuring value
of MRI is becoming a major goal of the MR community. Comparative effectiveness
approaches allow the realization of this goal, but these studies have not
traditionally been explored in the ISMRM community. This session will provide
an introduction to comparative effectiveness research (CER), with particular
focus on cost-effectiveness analysis using decision model approaches.METHODS
The audience
will be introduced to the difference between efficacy (e.g. randomized
controlled trials) and effectiveness research, and learn about three types of
CER: pragmatic trials, observational studies, and decision analysis models. The
course will focus on this last option – decision analysis models. The audience
will be shown best practices for setting up a decision tree model. We will
discuss Markov models, their properties, and how they can be used to model
health outcomes and events that change overtime. Various methods used in comparative
effectiveness and cost-effectiveness research will be discussed including the
incremental cost-effectiveness ratio (ICER), net health benefits, number of
cases detected and missed, and quality-adjusted life years (QALYs). The audience will be introduced to one-way
sensitivity analysis to model the influence of each parameter in the model, and
probabilistic sensitivity analysis to compare stochastic models. RESULTS
We will discuss
the information and interpretation of the results from decision models,
especially related to the cost-effectiveness outcomes. We will discuss two different
approaches to run the model including the baseline or “rollback” method and
Monte Carlo simulation using probabilistic sampling of model parameters. The
audience will learn about how to interpret the incremental cost-effectiveness
ratio (ICER) and net health benefits (NHB), and quality-adjusted life years
(QALYs). We will also discuss other outcomes that may be of interest in
MRI-related research including sensitivity, specificity, positive predictive
value, negative predictive value, number of cases detected and missed. Finally,
we will discuss how to compare models with multiple outcomes of interest.DISCUSSION
We will discuss
how models can help us identify gaps in knowledge, and value of information. The
audience will learn what makes a good decision analysis question and research
topic: namely that we have at least two viable clinical options to compare, and
there is some uncertainty on what is the best action. We will also discuss: why
having limited data on a topic might actually make a model even more useful; strategies
for handling imperfect information; the advantages/disadvantages of decision
analysis approaches.CONCLUSION
Attendees of
this session will be introduced to the key concepts of comparative and
cost-effectiveness analysis using decision analytic modeling. Audience members
should have an idea of what makes a good decision analysis problem and how to create
an outline of a model for their own research questions. Acknowledgements
Dr. Schiltz received support from the National Institutes of Health/NationalCenter for Advancing Translational Sciences (grant no.KL2TR000440) during some of this research, and the Frances Payne Bolton School of Nursing Case Western Reserve University.References
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