AIML and the real bottleneck in Holter monitoring

This chart highlights a structural issue in Holter monitoring across the U.S. and Canada. Reimbursement is already established. Holter reports typically generate **$100–$180 USD in the U.S.** and **$120–$300 CAD in Canada**, depending on payer and setting. Pricing is not the challenge. Throughput is. Mid-sized clinics often run **3,000–8,000 Holters per year**, while hospital systems can exceed **20,000 annually**. Yet a cardiologist can realistically review only **15–25 reports per day**, creating a capacity ceiling that limits growth and delays reporting. This is where **AI/ML Innovations (AIML)** fits. AIML uses AI-driven pre-analysis and triage so cardiologists focus on flagged events. Physicians remain in control, while the same staff can handle **two to four times more volume** without added headcount. From an investor perspective, this matters. Reimbursement per test stays the same, but higher throughput directly lifts realized revenue. Even modest efficiency gains can materially improve clinic economics and reduce hospital backlogs. Key point: AI does not change the value of a Holter test. It increases system capacity. **Thoughts on workflow-focused healthcare AI versus replacement-style models?** https://preview.redd.it/wk1hfk62nkbg1.jpg?width=1600&format=pjpg&auto=webp&s=f313cfd8b6fbc43584cede6f74407bba74a46ca6