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
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...
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| Format: | Article |
| Language: | English |
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Swansea University
2025-01-01
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| Series: | International Journal of Population Data Science |
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| Online Access: | https://ijpds.org/article/view/2466 |
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| author | Naomi Hamm Sharon Bartholomew Yinshan Zhao Sandra Peterson Saeed Al-Azazi Kimberlyn McGrail Lisa Lix |
| author_facet | Naomi Hamm Sharon Bartholomew Yinshan Zhao Sandra Peterson Saeed Al-Azazi Kimberlyn McGrail Lisa Lix |
| author_sort | Naomi Hamm |
| collection | DOAJ |
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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.
Methods
A subcommittee of four individuals with expertise in routinely collected health data, multi-jurisdiction health research, and algorithm development and implementation was formed from Health Data Research Network (HDRN) Canada's Algorithms and Harmonized Data Working Group (AHD-WG). The subcommittee reviewed items within the STROBE and RECORD guidelines and evaluated these items against published feasibility studies. Items to ensure transparent reporting of feasibility studies not contained within STROBE or RECORD guidelines were identified through consensus by subcommittee members using the Nominal Group Technique. The AHD-WG reviewed and approved these additional recommended elements.
Results
Eleven new recommended elements were identified: one element for the title and abstract, one for the introduction, five for the methods, and four for the results sections. Recommended elements primarily addressed reporting jurisdictional data variabilities, data harmonization methods, and algorithm implementation techniques.
Significance
Implementation of these recommended elements, alongside the RECORD guidelines, is intended to encourage consistent publication of methods that support reproducibility, as well as increase comparability of algorithms and their use in national and international studies.
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| format | Article |
| id | doaj-art-94eea8e11fe54ac99cc066aa79901f05 |
| institution | Kabale University |
| issn | 2399-4908 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Swansea University |
| record_format | Article |
| series | International Journal of Population Data Science |
| spelling | doaj-art-94eea8e11fe54ac99cc066aa79901f052025-02-01T10:48:46ZengSwansea UniversityInternational Journal of Population Data Science2399-49082025-01-0110210.23889/ijpds.v10i2.2466Minimum 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 Hamm0Sharon Bartholomew1Yinshan Zhao2Sandra Peterson3Saeed Al-Azazi4Kimberlyn McGrail 5Lisa Lix6Department of Community Health Sciences, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, CanadaCentre for Surveillance and Applied Research, Public Health Agency of Canada, Ottawa, CanadaPopulation Data BC, University of British Columbia, Vancouver, CanadaCentre for Health Services and Policy Research, University of British Columbia, Vancouver, CanadaGeorge and Fay Yee Centre for Healthcare Innovation, University of Manitoba, Winnipeg, CanadaCentre for Health Services and Policy Research, University of British Columbia, Vancouver, CanadaDepartment of Community Health Sciences, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Canada 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. Methods A subcommittee of four individuals with expertise in routinely collected health data, multi-jurisdiction health research, and algorithm development and implementation was formed from Health Data Research Network (HDRN) Canada's Algorithms and Harmonized Data Working Group (AHD-WG). The subcommittee reviewed items within the STROBE and RECORD guidelines and evaluated these items against published feasibility studies. Items to ensure transparent reporting of feasibility studies not contained within STROBE or RECORD guidelines were identified through consensus by subcommittee members using the Nominal Group Technique. The AHD-WG reviewed and approved these additional recommended elements. Results Eleven new recommended elements were identified: one element for the title and abstract, one for the introduction, five for the methods, and four for the results sections. Recommended elements primarily addressed reporting jurisdictional data variabilities, data harmonization methods, and algorithm implementation techniques. Significance Implementation of these recommended elements, alongside the RECORD guidelines, is intended to encourage consistent publication of methods that support reproducibility, as well as increase comparability of algorithms and their use in national and international studies. https://ijpds.org/article/view/2466Algorithmsfeasibility studiesAdministrative DataTransparency |
| spellingShingle | Naomi Hamm Sharon Bartholomew Yinshan Zhao Sandra Peterson Saeed Al-Azazi Kimberlyn McGrail Lisa Lix 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 Algorithms feasibility studies Administrative Data Transparency |
| title | 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 |
| title_full | 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 |
| title_fullStr | 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 |
| title_full_unstemmed | 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 |
| title_short | 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 |
| title_sort | 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 |
| topic | Algorithms feasibility studies Administrative Data Transparency |
| url | https://ijpds.org/article/view/2466 |
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