Demo Health System

What happened: Endocrinology Clinic has a room utilization of 41.7%.

Likely driver: A combination of below-target booking density, idle gaps between visits, and elevated no-shows.

Impact: 77,137 min of available room time went unused in the selected period.

Suggested next action: Tighten scheduling templates, backfill cancellations, and review whether room supply exceeds demand for this specialty.

What happened: Baseline no-show rate is 12.0%, but 2 days spiked as high as 31.5%.

Likely driver: Clustered no-shows, consistent with reminder gaps or external factors (weather, holidays) on specific dates.

Impact: Each no-show leaves a fully-staffed room idle for the scheduled duration, directly lowering utilization.

Suggested next action: Enable targeted reminders for high-risk slots and consider controlled overbooking on historically high-no-show days.

What happened: Average room turnover in Endocrinology Clinic is 23.9 minutes, well above a lean target.

Likely driver: Procedure-heavy room cleaning, supply restocking, or staff availability for turnover.

Impact: Excess turnover is non-bookable time; trimming it directly frees capacity for additional visits.

Suggested next action: Pre-stage rooms, parallelise cleaning with documentation, and right-size turnover buffers by appointment type.

What happened: 188 schedule records (9.3%) do not match between the EHR and Finance system feeds; the most common issue is "missing_in_finance".

Likely driver: Point differences in time, room, and duration between the two systems even though both feeds are current.

Impact: Reconciliation gaps undermine trust in capacity numbers and can double-count or miss visits.

Suggested next action: Resolve time/room mismatches starting with the most common issue, "missing_in_finance".

What happened: Several providers, led by Provider END05 (52.3% late starts), routinely begin after the scheduled time.

Likely driver: Provider-driven start delays — earlier visits overrunning, late arrivals, or pre-visit documentation time.

Impact: Late starts cascade through the day, compressing later slots and pushing avoidable idle and overtime.

Suggested next action: Share provider-level start-time reports, stagger first-appointment buffers, and protect documentation time.

What happened: 40 room blocks removed 3,870 min from bookable capacity.

Likely driver: Maintenance, training, administrative holds, and a few rooms with mapping issues recorded as unmapped blocks.

Impact: Blocked time reduces the available-minutes denominator; avoidable blocks suppress true capacity.

Suggested next action: Audit recurring blocks, consolidate maintenance into low-demand windows, and resolve unmapped rooms.

What happened: Utilization dips at the start and end of the week relative to Tuesday–Thursday.

Likely driver: Synthetic demand seasonality — typical of elective specialty scheduling patterns.

Impact: Predictable weekly troughs leave recoverable capacity on Mondays and Fridays.

Suggested next action: Shift flexible visit types and outreach toward Monday/Friday to smooth the weekly curve.