Case Study — Healthcare & Medical Education

London Health Sciences Centre transforms simulation research with Speak AI

London Health Sciences Centre used Speak AI to record and analyze medical simulations at the Michael Gunning Simulation Centre, enabling researchers to quickly identify communication breakdowns and navigate lengthy recordings with interactive transcripts.

Simulation analysis | Communication research | Interactive navigation

The challenge

London Health Sciences Centre (LHSC) is one of Canada’s largest acute-care teaching hospitals, operating the Michael Gunning Simulation Centre where medical professionals train through realistic clinical scenarios. Simulation-based training is critical for developing clinical skills, teamwork, and communication under pressure.

A key area of research at the Simulation Centre focuses on communication breakdowns during medical scenarios. These breakdowns can lead to adverse patient outcomes in real clinical settings, making their identification and analysis essential for improving training protocols. However, analyzing simulation recordings manually is extraordinarily time-consuming. Researchers had to watch entire recordings, often hours long, to find specific communication moments.

  • Lengthy recordings: Medical simulations generate hours of audio and video content. Manually reviewing these recordings to find specific communication events consumed enormous research time.
  • Communication breakdown identification: Researchers needed to identify specific moments where communication failed, which required careful review of every interaction in a simulation.
  • Cost and efficiency: Traditional manual transcription and review was expensive and slow, limiting the volume of simulations that could be analyzed for research purposes.

The solution

With ethics committee approval, London Health Sciences Centre engaged Speak AI to transform how simulation recordings were captured, transcribed, and analyzed.

Automated simulation transcription

Simulation recordings were transcribed automatically through Speak AI, creating text-based representations of every interaction. This eliminated the need for expensive manual transcription and made recordings immediately searchable.

Communication breakdown detection

With searchable transcripts, researchers could quickly identify moments of communication breakdown without watching entire recordings. Keyword search and analysis tools helped surface critical interaction patterns.

Interactive media navigation

Speak AI’s interactive media interface allowed researchers to navigate lengthy recordings by clicking on transcript segments, jumping directly to moments of interest rather than scrubbing through hours of video.

Research-grade analysis

The combination of automated transcription and AI-powered analysis provided researchers with tools to process more simulations, identify patterns across multiple sessions, and generate insights that would have been impractical with manual methods.

“This is a complete paradigm shift for how we do research.”
Trauma Researcher, London Health Sciences Centre

Key takeaways

  • Simulation research can be transformed with automated transcription: Instead of manually reviewing hours of recordings, researchers can search transcripts to find critical moments in seconds, fundamentally changing the research workflow.

  • Communication breakdowns become discoverable: Searchable transcripts make it possible to identify and study communication failures across many simulations, enabling pattern analysis that was previously impractical.

  • Interactive navigation saves research hours: The ability to click on transcript segments and jump directly to the corresponding moment in a recording eliminates the time spent scrubbing through lengthy video files.

  • Healthcare institutions can scale research volume: By reducing the time and cost required to analyze each simulation, institutions can study more scenarios and generate more robust findings to improve patient care.

More customer stories

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