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"There's too much power in this number. It's freaking the whole response out": the views of key informants on evidence and targets to achieve hepatitis C elimination goals in Australia.

Carla TreloarJake RanceJoanne BryantLise Lafferty
Published in: Journal of viral hepatitis (2023)
Background Enumeration of disease is a key management tool. Setting of targets, like for hepatitis C elimination, have deep meaning and effect. We use the case of elimination in New South Wales (NSW) Australia to examine key informants' understandings of the use of targets, and the evidence that informs them, to drive action in elimination. 28 key informants working in NSW, elsewhere in Australia and internationally in high income countries participated in a semi-structured qualitative interview in 2022. Analysis was informed by scholarship calling for examination of the ways in which science constructs what is thought possible in action. Participants pointed to the power of quantified evidence and targets and their complex effects, and questioned the usefulness and certainty derived from these at the "pointy end" of elimination. Although a range of targets exist in global and local strategies, reaching testing targets was the assumed solution to achieving elimination. Achieving elimination was thought to require "off piste" and experimental approaches that went beyond available evidence. The different types of work that participants felt necessary for late-stage elimination may require additional metrics to explain return on investment ratios. What threshold would be used to reduce efforts in elimination was a major concern. These data indicate that understandings of the evidence underpinning elimination targets and how to achieve them are far from settled. At this point, elimination efforts may need to rely on locally produced and community-driven evidence and shift from evidence-based to evidence-making paradigm.
Keyphrases
  • healthcare
  • mental health
  • systematic review
  • physical activity
  • machine learning
  • quality improvement
  • artificial intelligence