Laborie - High-Resolution Anorectal Manometry Clinical Training
Laborie Medical Technologies
Summary
Live clinical training video documenting an HRAM procedure, setup, cleanup, and interpretation for internal and external education.
Challenge
High-resolution anorectal manometry is a sensitive procedure that many sales and clinical support teams rarely get to observe firsthand. Laborie needed a realistic training asset that documented the workflow clearly while preserving patient privacy and staying inside compliance boundaries.
Objectives & Outcomes
Objective
Provide a privacy-compliant, workflow-accurate HRAM training asset for internal teams and clinicians.
Outcome
Laborie's training team reported stronger understanding of the HRAM procedure and greater confidence among internal audiences who previously had little exposure to the workflow. The success of the project led to budgeting for two more clinical training videos.
Approach
Clinical Considerations
Clinical accuracy and workflow understanding informed every production decision.
Production Strategy
J2 Media captured a fully live HRAM procedure at a physician-owned endoscopy practice using multiple mirrorless cinema cameras, synchronized software screen capture, and carefully managed audio. Post-production emphasized privacy safeguards, PHI redaction, and supportive graphics that could clarify the procedure without interrupting the clinical narrative.
Execution
Environment
Professional studio or on-site production environment
Content Scope
Outcomes
How Content is Used
The video supports internal clinical training for capital sales and clinical support teams, with additional external training use possible when approved.
What Problem it Solved
Laborie's training team reported stronger understanding of the HRAM procedure and greater confidence among internal audiences who previously had little exposure to the workflow. The success of the project led to budgeting for two more clinical training videos.
Additional Notes
Projects like this benefit from structured schemas because privacy controls, workflow details, and distribution limits all matter. Keeping those details in source content makes it much easier to maintain the case study without risking template-level regressions.
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