Transparency in the secondary use of health data: Assessing the status quo of guidance and best practices is a research paper (2024). On theSindex it has a DataRank of 0.104. It has been cited 1 time.
We evaluated what guidance exists in the literature to improve the transparency of studies that make secondary use of health data. To find relevant literature, we searched PubMed and Google Scholar and drafted a list of health organizations based on our personal expertise. We quantitatively and qualitatively coded different types of research transparency: registration, methods reporting, results reporting, data sharing, and code sharing. We found 54 documents that provide recommendations to improve the transparency of studies making secondary use of health data, mainly in relation to study registration (n = 27) and methods reporting (n = 39). Only three documents made recommendations on data sharing or code sharing. Recommendations for study registration and methods reporting mainly came in the form of structured documents like registration templates and reporting guidelines. Aside from the recommendations aimed directly at researchers, we found 31 recommendations aimed at the wider research community, typically on how to improve research infrastructure. Limitations or challenges of improving transparency were rarely mentioned, highlighting the need for more nuance in providing transparency guidance for studies that make secondary use of health data.
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Base Score Contribution
0.104
From this paper's citation signal
Citation Network Contribution
0
Citation network not refreshed for this result
This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.
Learn more about DataRank methodology →DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 100% comes from its base citations and 0% from the citation network.
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.