ArticleHealth research policy and systems2023
Prioritising and incentivising productivity within indicator-based approaches to Research Impact Assessment: a commentary.
Article in Health research policy and systems, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- On the potential value of eHTA: a commentary on "Defining Early Health Technology Assessment: Building Consensus Using Delphi Technique".International journal of technology assessment in health care · 2025Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Research Impact Assessment (RIA) represents one of a suite of policies intended to improve the impact generated from investment in health and medical research (HMR). Positivist indicator-based approaches to RIA are widely implemented but increasingly criticised as theoretically problematic, unfair, and burdensome. This commentary proposes there are useful outcomes that emerge from the process of applying an indicator-based RIA framework, separate from those encapsulated in the metrics themselves. The aim for this commentary is to demonstrate how the act of conducting an indicator-based approach to RIA can serve to optimise the productive gains from the investment in HMR. Prior research found that the issues regarding RIA are less about the choice of indicators/metrics, and more about the discussions prompted and activities incentivised by the process. This insight provides an opportunity to utilise indicator-based methods to purposely optimise the research impact. An indicator-based RIA framework specifically designed to optimise research impacts should: focus on researchers and the research process, rather than institution-level measures; utilise a project level unit of analysis that provides control to researchers and supports collaboration and accountability; provide for prospective implementation of RIA and the prospective orientation of research; establish a line of sight to the ultimate anticipated beneficiaries and impacts; Include process metrics/indicators to acknowledge interim steps on the pathway to final impacts; integrate 'next' users and prioritise the utilisation of research outputs as a critical measure; Integrate and align the incentives for researchers/research projects arising from RIA, with those existing within the prevailing research system; integrate with existing peer-review processes; and, adopt a system-wide approach where incremental improvements in the probability of translation from individual research projects, yields higher impact across the whole funding portfolio.Optimisation of the impacts from HMR investment represents the primary purpose of Research Impact policy. The process of conducting an indicator-based approach to RIA, which engages the researcher during the inception and planning phase, can directly contribute to this goal through improvements in the probability that an individual project will generate interim impacts. The research project funding process represents a promising forum to integrate this approach within the existing research system.
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What 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.