ArticleResearch in health services & regions2022
From data to practice change - exploring new territory for atlases of clinical variation.
Article in Research in health services & regions, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed.
- Revealing the gaps: unwarranted variations and multidisciplinary solutions in Victorian oesophagogastric cancer care - A mixed-methods analysis.BMC health services research · 2026Article
- Article
- What next for the Australian Atlas of Healthcare Variation series? Focusing the system on appropriate and sustainable health care.Research in health services & regions · 2024Review
- Utilization of health-related data in the regional context for health service planning in the Federal State of Brandenburg, Germany-a qualitative study.Research in health services & regions · 2024Article
- Regional variation in access to and quality of acute stroke care: results of Germany's Health System Performance Assessment pilot, 2014-2020.Research in health services & regions · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Despite decades of atlas production and use within multiple healthcare systems, and consistent reporting of geographical differences in the utilisation of services, significant levels of clinical variation persist. Drawing on over forty years of combined experience using atlases of clinical variation, we reflect on why that might be the case and explore the role of atlases have played in efforts to reduce inappropriate overuse, underuse and misuse of healthcare services. We contend that atlases are useful but, on their own, are not enough to drive change in clinical practice and improvement in patient outcomes. Building on four conceptual models we have published since 2017, we argue that atlases, with their focus on measuring healthcare utilisation by residents in different geographies, generally fail to provide sufficient information and statistical analyses to truly assess the nature of the variation and support action for change. They seldom use structures such as hospitals or teams as the unit of analysis to understand variation; they rarely feature the key elements of healthcare performance which underlie variation; they are mostly silent about how to assess whether the variation measured is warranted or truly unwarranted; nor do they identify evidence-based levers for change. This means that a stark choice confronts producers of atlases - to either continue with the current model and more explicitly rely on other players to undertake work to complete the 'data to action' cycle that is necessary to secure improvement; or to refine their offering - including more sophisticated performance measurement approaches, nuanced guides for interpretation of any differences found, support for the selection and application of levers for change that align with local context, and provision of evidence-based options for implementation.
Indexed as
Identifiers
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.