Telus Health sees AI easing Canada's medical record gaps
TELUS Health has published a discussion paper on the use of agentic artificial intelligence in electronic medical records, arguing that the technology could help address persistent data-sharing problems in Canadian healthcare.
The paper focuses on a longstanding operational weakness in the sector: patient information often remains fragmented across clinicians, pharmacies, virtual care services and health authorities. That limits care coordination and adds to the administrative burden on doctors and other frontline staff.
To illustrate the scale of that burden, the paper cites a figure showing that 71% of physicians say interoperability across data and records would significantly reduce administrative workload.
Electronic medical record systems are widely used across Canadian healthcare, but the paper argues that many still function mainly as repositories for information rather than tools that actively support coordination between care settings. In practice, clinicians may still need to assemble patient histories manually from separate systems and records.
Data gaps
The discussion centres on AI-enabled medical records that can connect information from multiple parts of the healthcare system and present it in a more usable form. According to the paper, such systems could help clinicians follow longitudinal patient records, identify relevant information more quickly and improve coordination among care teams.
That is particularly relevant for physicians and other clinicians responsible for large patient populations. Better system support could help them identify gaps in care, monitor changes over time and reduce the manual effort required to track fragmented medical histories.
The argument reflects a broader shift in healthcare technology, as suppliers and providers look beyond digitisation alone toward software that can interpret, organise and prioritise information. For hospitals, clinics and primary care practices, the issue is not only whether records are stored electronically, but whether they can move between settings in ways that improve day-to-day clinical work.
Privacy rules
The paper also addresses regulatory constraints on AI use in healthcare, a key issue in Canada's tightly governed health data environment. These systems are intended to operate within frameworks set by legislation including the Personal Health Information Protection Act and the Personal Information Protection and Electronic Documents Act.
That emphasis on compliance is likely to be central to any wider adoption of AI in patient record systems. Healthcare organisations face strict obligations around consent, storage, access and disclosure of personal health information, and any new layer of automation is likely to be assessed against those standards.
The discussion also reflects a practical concern among providers: AI in record systems will be judged less by its abstract promise than by whether it removes tasks from clinicians without creating new risks or workflow disruptions. In primary care in particular, administrative strain has become a persistent pressure point, as doctors balance patient demand against documentation, referrals and follow-up requirements.
Against that backdrop, interoperability remains a recurring theme in Canadian healthcare policy and technology planning. Digital records have expanded over time, but the ability of separate systems to exchange and use information consistently has often lagged behind. The result can be duplication, delays and incomplete visibility into a patient's treatment history.
TELUS Health's paper argues that AI could help close that gap by moving record systems beyond storage and retrieval. Its central claim is that better-connected, more responsive medical record platforms could provide a more complete view of patients while easing the administrative burden that clinicians say continues to weigh on care delivery.