Audit

Scheduling & Capacity Audit Workbook

A hands-on, interactive audit workbook that captures appointment types, arrival patterns, no-show rates, staffing rosters, room availability, utilization estimates, and guided analysis. Built to record observations, score candidate interventions, and produce prioritized next steps the team can act on.

Interactive Tool

Scheduling & Capacity Audit Workbook

What this audit helps you do

This workbook collects practical, comparable observations about appointments, patient arrivals, no-shows, staffing, and rooms so teams can see where schedules, staff, and space mismatch demand. Use it during a focused analysis day or over a representative week. Save one submission per clinic/day/period to build an evidence base.

Helpful: gather a sample schedule, appointment-level data, historic no-show stats, observed arrival timestamps (or sample), staff rosters, and room lists before you begin.

Name of the site, department, or clinic where this audit is performed.
Date or date range for the observations (e.g., 2026-04-21 or Apr 20–24, 2026).
Name and role of the person capturing the data.
Paste one line per appointment type using CSV columns: Type,AvgDuration(min),SlotsPerClinic,ObservedNoShowRate(%),TypicalArrivalPattern. Example: NewPatient,30,12,15,early. This helps capture variation by visit type.
Total appointments scheduled per day on the observed day(s).
Count of scheduled appointments that fall into the busiest hour.
Percent of appointments not completed (no-shows + late cancellations) during the observed period.
Positive if patients on average arrive late; negative if early. Useful to estimate waiting and flow effects.
Standard deviation of arrival offsets; higher values indicate more variability and greater scheduling mismatch.
Total hours the clinic operates on an observed day (e.g., 8).
Count only rooms routinely used for the visit types included in this audit.
Rough percent of available room time used for scheduled visits during clinic hours. Use 0–100.
Count clinicians (MD/NP/PA/therapist) typically scheduled during the observed period.
Front desk, MA, techs — who materially affect throughput.
Average time from arrival to rooming or clinician contact based on observation or sample.
Enter as a percent (0–100).
Yes if most volume is concentrated in particular hours or days causing peaks.
1 = very little variation, 5 = highly variable (frequent overruns and underruns)
1.0 10.0
Rate the operational ability to change appointment templates (1 = very hard, 5 = very easy).
1.0 10.0
Free text: e.g., check-in delays, insufficient exam rooms, clinician backlog, long intake forms, equipment constraints. Note evidence for each observation.
Select candidate fixes to score below. Use this checklist to focus the team on realistic options.
If you selected this intervention, score likely impact on waits/outcomes (1 low — 5 high).
1.0 10.0
Estimate effort/cost to implement (1 = minimal, 5 = major).
1.0 10.0
Score likely impact if reminders implemented or improved.
1.0 10.0
Estimate effort/cost to implement or scale.
1.0 10.0
Score likely impact of interventions to smooth arrivals.
1.0 10.0
Estimate effort to change patient flow and communications.
1.0 10.0
Score expected impact of adding flexible staffing.
1.0 10.0
Estimate cost/complexity of hiring/redeploying.
1.0 10.0
Score expected impact of improving room availability.
1.0 10.0
Estimate effort and regulatory/workflow constraints.
1.0 10.0
Score expected impact of extending clinic hours or staggering sessions.
1.0 10.0
Estimate operational and staffing costs.
1.0 10.0
Score likely impact of shifting follow-ups to telehealth.
1.0 10.0
Estimate setup, training, and patient-eligibility effort.
1.0 10.0
Score likely impact if an overbooking strategy is used for predictable no-show rates.
1.0 10.0
Estimate operational risk and monitoring effort.
1.0 10.0
Use a simple formula (team suggestion: Priority = Impact*2 - Effort) or your own approach. Enter the resulting numeric score for the top candidate.
Name the intervention your team will prioritize based on this audit.
List concrete actions, who will own them, and how you will measure improvement (e.g., reduce average wait by X min, lower percent waiting >30 min to Y%).
Person accountable for moving the recommended intervention forward.
Date for the first review of progress (e.g., 2026-05-15).
Paste URLs to spreadsheets, attach references, or note where raw data lives.
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