AI-driven schedule optimization reduces Cardiovascular Procedure scheduling errors by 50%

Opmed.ai predicts procedure duration more accurately than clinician estimates — reducing average error from 68 minutes to 34 minutes.

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Bar chart comparing average prediction errors showing AI prediction at 34 minutes and clinician estimate at 68 minutes.
ACC.26 Accepted Research
Mayo Clinic Collaboration
7,544 Procedures Trained
643 Prospective Cases Validated

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Your schedule is only as reliable as your next estimate

Most cardiac procedure schedules are built on historical averages. The result: overruns, idle time, cascading delays, and frustrated staff. For a busy cardiac program, even a 30-minute scheduling error compounds across dozens of cases per week.

Overruns cascade

One procedure runs long. Everything behind it pays the price - patients waiting, staff in overtime, cases that never make it to the table.

Idle time is wasted revenue

Every minute a procedure room sits empty between cases represents direct revenue loss. The overhead does not pause while the room does.

Complex cases are hardest to predict

Complex procedures are the hardest to estimate and the costliest to mistime. The difficulty and the consequence arrive together.

Opmed.ai’s Solution: An AI-Driven Approach

Opmed.ai has pioneered an AI model that delivers precise predictions of case durations, customized for the specific demands of cardiovascular procedures at Mayo Clinic.

01

Forecast

Forecast operational needs and outcomes with precision.

02

Allocate

Optimize resource allocation across workflows.

03

Adjust

Ensure resilience through real-time adaptability.

No disruption to existing workflows.
Certified, seamless integration with Epic & Oracle Cerner.
Timeline schedule with color-coded steps for Create, Review, and Deliver phases spanning weeks 1 to 6 on a grid background.3D grid layout with four colored rectangular blocks in orange, green, purple, and blue, positioned in a staggered manner on a black background.
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What 50% fewer scheduling errors actually means for your program

Every minute of scheduling error has an operational cost. Here's what the data translates to in real cath lab terms.

~34 min
More Accurate Estimates

Average reduction in time estimation error per case vs. ~68 min with clinician estimates.

566 hrs
Potential Capacity Per Year

At 1,000 annual cases – up to ~71 additional procedure days of capacity, assuming improved scheduling accuracy.

2.3×
Better Predictions

Opmed's R² of 0.72 vs. 0.31 for clinicians — explaining the real variation in how long cases take.

Potential Capacity Opportunity by Annual Procedure Volume

Based on ~34 min reduction in estimation error per case

Annual Cases
Hours Recovered
Suite Days Back
Est. Value*
500 cases
283 hrs
35 days
$0.7M - $1.3M
1,000 cases
566 hrs
71 days
$1.4M - $2.5M
1,500 cases
849 hrs
106 days
$2.1M - $3.8M
2,000 cases
1,132 hrs
142 days
$2.8M - $5.1M
Annual Cases
500 cases
Hours Recovered
283 hrs
Suite Days Back
35 days
Est. Value*
$0.7M - $1.3M
Annual Cases
1,000 cases
Hours Recovered
566 hrs
Suite Days Back
71 days
Est. Value*
$1.4M - $2.5M
Annual Cases
1,500 cases
Hours Recovered
849 hrs
Suite Days Back
106 days
Est. Value*
$2.1M - $3.8M
Annual Cases
2,000 cases
Hours Recovered
1,132 hrs
Suite Days Back
142 days
Est. Value*
$2.8M - $5.1M
* Based on published cath lab cost range $2,500-$4,500/hr (industry benchmark, not from study data).
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