AI That Helps ECS Build Smarter Schedules, Faster
Eliminate manual spreadsheet work while optimizing schedules for provider satisfaction, fairness, coverage, and cost.
Describe
Humans Have Optimized What They Can
Provider-First Culture
Strong Operational Foundation
ECS already uses time studies and site-level workload patterns to shape staffing.
Too Many Variables to Optimize Manually
ECS has a strong scheduling process, but maintaining high-quality schedules across 12 sites and ~300 providers requires a lot of manual work.
- —Preferences, nights, weekends, recovery time, and other metrics are updated and tracked manually.
- —Fairness/shift reports are maintained across many spreadsheets.
- —Qgenda auto-generation requires substantial manual correction to resolve coverage gaps and undesirable shift patterns.
- —Medical directors must constantly review volume data to identify overstaffing, understaffing, and opportunities to adjust coverage.
Scheduling
Team
Human schedulers cannot manually hold every variable at once.
AI-powered Scheduling for ECS
Describe analyzes ECS's operational data, preferences, and fairness rules to auto-generate schedules that balance coverage, workload, provider satisfaction, and cost.
Site-specific models trained on ECS' historic demand that deliver hourly volume forecasts.
Predict Patient Demand Before It Happens
Describe minimizes cost by using custom-trained AI to predict patient arrivals and staff to volume, by zone.
Key takeaway
Scheduling more efficiently means matching provider coverage to actual demand — so ECS can reduce waste, protect patient care, and give providers more time off.
AI-optimized scheduling keeps coverage closer to actual arrivals.
ECS-Specific AI Use Cases
Automate Fairness Reporting
ECS currently tracks fairness, nights, weekends, shifts, call-outs, and over/under hours using Excel spreadsheets. Describe auto-tracks these metrics, allowing schedulers to focus on higher-value decisions.
Productivity-Aware Provider Pairing
Describe avoids risky pairings — never two historically slower providers during peak — and pairs newer physicians with faster, experienced ones to support onboarding. Describe helps pair providers who work well together.
Operational Intelligence for Medical Directors
Describe continuously monitors staffing, patient demand, provider workload, and scheduling patterns to surface actionable recommendations and anomalies.
Patient volume projected 18% above scheduled coverage
Recommendation: Add APP coverage from 2 PM–8 PM
One APP is averaging 32% more workload than the site average
Recommendation: Review staffing mix
Projected shortage of 8 APP shifts (based on SurveyMonkey responses and volume forecast)
Recommendation: Begin recruiting or adjust availability
Automatically Update Preferences
ECS surveys providers for preferences, but manually updating them is too time-consuming, so some sites are scheduled manually. Describe updates preferences automatically so every site can use auto-generation consistently.
An In-Person Implementation Approach
Describe's 2-month scheduling pilot pairs ECS with a dedicated, in-person Implementation Engineer who will help run a side-by-side comparison of Describe vs. your current process.
Discovery & Data Setup
Gather roster, templates, contracts, rules, preferences, holiday logic, and historical volume. Capture what lives in schedulers' heads.
AI Scheduler Configuration
Configure Describe around ECS's goals: provider satisfaction, fairness, and optimal staffing.
Month 1 Schedule Generation
MONTH 1 VALUEDescribe generates real schedules in Month 1 so ECS can compare it against the manual process.
Weekly Feedback
Meet weekly with ECS' core team to review progress and gather feedback.
Schedules That Improve Margins
Scheduling Optimization Plugin
AI Intelligence Layer that works on top of QGenda
Describe pays for itself by removing just ~5 unnecessary shifts per month.
Proof from Baptist Health
5-site ED group using Describe scheduling.