Developing a Health Data Analytic Service to Serve the Private Sector for Public Benefit

ObjectivesOur Organization, a pan-Canadian network that facilitates publicly-funded multi-regional health research, is developing a process to undertake multi-jurisdictional data analytic services with private sector entities. We describe experiences and approaches to working with the private sector across Organization member sites, and concerns raised by our Public Advisory Committee. MethodsWe administered a survey with categorical and open-ended questions about work with the private sector including project volume, timelines, and differences from publicly-funded projects in terms of review and approval, fee structure, limitations on data access, and additional safeguards. It was distributed to 10 provincial and two pan-Canadian member sites holding linked health administrative data. Findings were organized using the Five Safes framework, a tool for evaluating access to privacy-sensitive data across five dimensions, and were presented at a quarterly PAC meeting to the group of ~15 members from diverse backgrounds. Key discussion and questions points were recorded. ResultsAmong 12 sites surveyed, 10 worked with the private sector in some capacity and 2 planned to in future. Common themes identified, though with variation across sites, included: safe data - some datasets are restricted from private sector use; safe projects - require public benefit and exclude market research, require research ethics board approval, monitor projects to ensure public benefit through milestone reporting; safe people and settings - no access to individual level data, require use of the site’s analytic services; safe outputs - require project summary/results be made public and shared with decision-makers, exclusion of site staff from authorship on publications. Other safeguards included dedicated access pathways to ensure publicly-funded work is not displaced. Most sites had higher project fees for the private sector. ConclusionGiven growing private sector demand for pan-Canadian, population-level, data analytic services to demonstrate product value and support adoption decisions, it is essential to set policies and practices that ensure public benefit. These results are supporting the launch of a pilot multi-site use case with a private sector organization.

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Publication Details

Journal
International Journal for Population Data Science
Published
2025-08-28
DOI
https://doi.org/10.23889/ijpds.v10i4.3114
Primary Topic
Artificial Intelligence in Healthcare
Type
article
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article

Developing a Health Data Analytic Service to Serve the Private Sector for Public Benefit

Jodi M. Gatley, Anne Hayes, Kimberlyn McGrail, Ted McDonald
International Journal for Population Data Science
Artificial Intelligence in Healthcare
article

Developing a Health Data Analytic Service to Serve the Private Sector for Public Benefit

Jodi M. Gatley, Anne Hayes, Kimberlyn McGrail, Ted McDonald
article en

Abstract

ObjectivesOur Organization, a pan-Canadian network that facilitates publicly-funded multi-regional health research, is developing a process to undertake multi-jurisdictional data analytic services with private sector entities. We describe experiences and approaches to working with the private sector across Organization member sites, and concerns raised by our Public Advisory Committee. MethodsWe administered a survey with categorical and open-ended questions about work with the private sector including project volume, timelines, and differences from publicly-funded projects in terms of review and approval, fee structure, limitations on data access, and additional safeguards. It was distributed to 10 provincial and two pan-Canadian member sites holding linked health administrative data. Findings were organized using the Five Safes framework, a tool for evaluating access to privacy-sensitive data across five dimensions, and were presented at a quarterly PAC meeting to the group of ~15 members from diverse backgrounds. Key discussion and questions points were recorded. ResultsAmong 12 sites surveyed, 10 worked with the private sector in some capacity and 2 planned to in future. Common themes identified, though with variation across sites, included: safe data - some datasets are restricted from private sector use; safe projects - require public benefit and exclude market research, require research ethics board approval, monitor projects to ensure public benefit through milestone reporting; safe people and settings - no access to individual level data, require use of the site’s analytic services; safe outputs - require project summary/results be made public and shared with decision-makers, exclusion of site staff from authorship on publications. Other safeguards included dedicated access pathways to ensure publicly-funded work is not displaced. Most sites had higher project fees for the private sector. ConclusionGiven growing private sector demand for pan-Canadian, population-level, data analytic services to demonstrate product value and support adoption decisions, it is essential to set policies and practices that ensure public benefit. These results are supporting the launch of a pilot multi-site use case with a private sector organization.

International Journal for Population Data ScienceVol. 10(4)
University of New Brunswick (CA), University Health Network (CA), University of British Columbia (CA)
Openalex Percentile: Top 75%
Artificial Intelligence in Healthcare
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