ArticlePharmacoEconomics2013
Navigating time and uncertainty in health technology appraisal: would a map help?
Article in PharmacoEconomics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- The 'Switch' study protocol: a randomised-controlled trial of switching to an alternative tumour-necrosis factor (TNF)-inhibitor drug or abatacept or rituximab in patients with rheumatoid arthritis who have failed an initial TNF-inhibitor drug.BMC musculoskeletal disorders · 2014Trial
- A Modern Approach for Constructing Decision Analytic Models in Microsoft Excel.PharmacoEconomics · 2026Review
- Bayesian Hierarchical Models for Meta-Analysis of Quality-of-Life Outcomes: An Application in Multimorbidity.PharmacoEconomics · 2020Article
- Using the Payoff Time in Decision-Analytic Models: A Case Study for Using Statins in Primary Prevention.Medical decision making : an international journal of the Society for Medical Decision Making · 2017Article
- Cost effectiveness and value of information analyses of islet cell transplantation in the management of 'unstable' type 1 diabetes mellitus.BMC endocrine disorders · 2016Article
- The value of innovation under value-based pricing.Journal of market access & health policy · 2016Article
- Dealing with Time in Health Economic Evaluation: Methodological Issues and Recommendations for Practice.PharmacoEconomics · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Healthcare systems are increasingly under pressure to provide funding for innovative technologies. These technologies tend to be characterized by their potential to make valued contributions to patient health in areas of relative unmet need, and have high acquisition costs and uncertainty within the evidence base on their actual impact on health. Decision makers are increasingly interested in linking reimbursement strategies to the degree of uncertainty in the evidence base and, as a result, reimbursement for innovative technologies is frequently linked to some form of patient access or risk-sharing scheme. As the dominant methods of economic evaluation report final outcomes only at the time horizon of the analysis, they present only aggregated information. This omits much of the information available on how net benefit is distributed within the time horizon. In this article, we introduce the Net Benefit Probability Map (NBPM), which maps net health benefit versus time to identify how certain decision makers can be about the benefit of technologies at multiple time points. Using an illustrative example, we show how the NBPM can inform decision makers about how long it will take for innovative technologies to 'pay off', how methodological choices on discount rates affect results and how alternative payment mechanisms can reduce the risk for decision makers facing innovative technologies.
Indexed as
Identifiers
23877738What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.