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 - Naomi Hamm; Sharon Bartholomew; Yinshan Zhao; Sandra Peterson; Saeed Al-Azazi; Kimberlyn McGrail; Lisa Lix (International Journal of Population Data Science)
Background Research and surveillance using routinely collected health data rely on algorithms or definitions to ascertain disease cases or health measures. Whenever algorithm validation studies are not possible due to the unavailability of a reference standard, algorithm feasibility studies can be used to create and assess algorithms for use in more than one population or jurisdiction. Publication of the methods used to conduct feasibility studies is critical for reproducibility and transparency. Existing guidelines applicable to feasibility studies include the STrengthening the Reporting of OBservational studies in Epidemiology (STROBE) and REporting of studies Conducted using Observational Routinely collected health Data (RECORD) guidelines. These guidelines may benefit from additional elements that capture aspects particular to multi-jurisdiction algorithm feasibility studies and ensure their reproducibility. The aim of this paper is to identify the minimum elements for reporting feasibility studies to ensure reproducibility and transparency.