There are few experiences more frustrating than trying to understand an instruction manual that is poorly written and unclear. Whether it be furniture assembly, car maintenance, or technology woes, we’ve all been there. It’s no different when it comes to reading population health studies. Lack of transparent reporting can be both frustrating and counterproductive. It leaves the reader unsure if they can trust the results and limits one’s ability to build on previous research, or apply the same methods to their own work. So how does one ensure their publication includes all the necessary details? A team from Health Data Research Network (HDRN) Canada is addressing that head on when it comes to transparent reporting of algorithm feasibility studies.

HDRN Canada is a nonprofit corporation that aims to facilitate the use of multi-jurisdictional electronic health and social data to drive improvements in health and health equity. These electronic data often rely on algorithms, the definitions or rules, that are applied to the data to identify concepts of interest, such as comorbid health conditions. Methods to develop high quality (i.e. accurate) algorithms are rigorous, particularly when the algorithm must be applied to different data environments. When using data from multiple jurisdictions or data environments, feasibility studies are a methodological cornerstone.

Feasibility studies assess algorithm effectiveness, the availability of data elements, and potential utility of the algorithm across different settings. They can be used in the absence of a reference standard to assess algorithm validity. However, few algorithm feasibility studies are published, resulting in information silos that may result in limited sharing and reuse of algorithms. With this work, HDRN Canada hopes to provide guidance for feasibility study reporting in support of reproducibility and transparency of algorithms across different contexts.

HDRN Canada’s Algorithms and Harmonized Data Working Group, which is comprised of experts in algorithm development across Canada, collaborated to identify the minimum elements needed to ensure transparent reporting of feasibility studies. These minimum elements were compared to the elements found in existing reporting guidelines. The result is a comprehensive set of elements required to ensure transparent reporting of feasibility studies, along with explanations for each element and examples of previously published feasibility studies. By providing these recommended minimum elements for transparent reporting, HDRN Canada has improved the environment for transparent reporting and publication of feasibility studies.

As a researcher, it can be easy to overlook all the little details that need to be included in publications to make our work reproducible. What seems obvious to me, may not be clear to the next person. This is what makes reporting guidelines and recommendations such an essential tool when publishing. Having a clear guide on what the bare minimum is so helpful as both an author and reviewer!” – Naomi Hamm, PhD

 

Click here to view the full article

Naomi Hamm PhD, Department of Community Health Sciences, University of Manitoba, Canada

Hamm, N., Bartholomew, S., Zhao, Y., Peterson, S., Al-Azazi, S., McGrail , K. and Lix, L. (2025) “Minimum elements for reporting a feasibility assessment of algorithms based on routinely collected health data for multi-jurisdiction use: Health Data Research Network Canada recommendations ”, International Journal of Population Data Science, 10(2). doi: 10.23889/ijpds.v10i2.2466.