Dataset Information

An Efficient, Noniterative Method of Identifying the Cost-Effectiveness Frontier.

ABSTRACT: Cost-effectiveness analysis aims to identify treatments and policies that maximize benefits subject to resource constraints. However, the conventional process of identifying the efficient frontier (i.e., the set of potentially cost-effective options) can be algorithmically inefficient, especially when considering a policy problem with many alternative options or when performing an extensive suite of sensitivity analyses for which the efficient frontier must be found for each. Here, we describe an alternative one-pass algorithm that is conceptually simple, easier to implement, and potentially faster for situations that challenge the conventional approach. Our algorithm accomplishes this by exploiting the relationship between the net monetary benefit and the cost-effectiveness plane. To facilitate further evaluation and use of this approach, we also provide scripts in R and Matlab that implement our method and can be used to identify efficient frontiers for any decision problem.

SUBMITTER: Suen SC

PROVIDER: S-EPMC4626430 | biostudies-literature | 2016 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

An Efficient, Noniterative Method of Identifying the Cost-Effectiveness Frontier.

Suen Sze-chuan SC Goldhaber-Fiebert Jeremy D JD

Medical decision making : an international journal of the Society for Medical Decision Making 20150429 1

Cost-effectiveness analysis aims to identify treatments and policies that maximize benefits subject to resource constraints. However, the conventional process of identifying the efficient frontier (i.e., the set of potentially cost-effective options) can be algorithmically inefficient, especially when considering a policy problem with many alternative options or when performing an extensive suite of sensitivity analyses for which the efficient frontier must be found for each. Here, we describe a ...[more]

PMID: 25926282

Similar Datasets

Project description:BackgroundThe National Institutes of Health (NIH) is among the world's largest investors in biomedical research, with a mandate to: "…lengthen life, and reduce the burdens of illness and disability." Its funding decisions have been criticized as insufficiently focused on disease burden. We hypothesize that modern portfolio theory can create a closer link between basic research and outcome, and offer insight into basic-science related improvements in public health. We propose portfolio theory as a systematic framework for making biomedical funding allocation decisions-one that is directly tied to the risk/reward trade-off of burden-of-disease outcomes.Methods and findingsUsing data from 1965 to 2007, we provide estimates of the NIH "efficient frontier", the set of funding allocations across 7 groups of disease-oriented NIH institutes that yield the greatest expected return on investment for a given level of risk, where return on investment is measured by subsequent impact on U.S. years of life lost (YLL). The results suggest that NIH may be actively managing its research risk, given that the volatility of its current allocation is 17% less than that of an equal-allocation portfolio with similar expected returns. The estimated efficient frontier suggests that further improvements in expected return (89% to 119% vs. current) or reduction in risk (22% to 35% vs. current) are available holding risk or expected return, respectively, constant, and that 28% to 89% greater decrease in average years-of-life-lost per unit risk may be achievable. However, these results also reflect the imprecision of YLL as a measure of disease burden, the noisy statistical link between basic research and YLL, and other known limitations of portfolio theory itself.ConclusionsOur analysis is intended to serve as a proof-of-concept and starting point for applying quantitative methods to allocating biomedical research funding that are objective, systematic, transparent, repeatable, and expressly designed to reduce the burden of disease. By approaching funding decisions in a more analytical fashion, it may be possible to improve their ultimate outcomes while reducing unintended consequences.

Dataset Information

An Efficient, Noniterative Method of Identifying the Cost-Effectiveness Frontier.

Publications

An Efficient, Noniterative Method of Identifying the Cost-Effectiveness Frontier.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure