Audit

Scheduling & Capacity Audit: Patient Waits Root‑Cause Workbook

Interactive, reproducible audit form to map appointments, arrivals, staffing, and throughput; collect coded delay causes; prioritize interventions; and capture action plans and quick-tests.

Interactive Tool

Scheduling & Capacity Audit — Patient Waits Root-Cause Workbook

Welcome

This interactive audit captures the practical, observable facts your team needs to find where schedule, staffing, and space mismatch demand and create unnecessary waits. Use this form during a dedicated sampling period (a day, several clinic sessions, or a purpose-built observation window). The form collects a reproducible data collection plan, queue mapping notes, coded delay causes, a prioritization snapshot, and an action plan for quick-tests.

Tips: sample a representative mix of appointment types, record at least 30–50 patient events if possible, and pair this audit with schedule and staffing rosters for the sampled period. If you plan to repeat the audit, keep the same sampling rules so comparisons are meaningful.

Date of the observation or sampling window start.
Clinic, department, or organizational unit being audited.
Person completing this form.
E.g., 08:00–12:00 clinic sessions on 2026-07-05, or morning and afternoon sessions across three days.
Choose the method used to select observed appointments.
Count of patient arrivals/appointments included in this sample.
List the appointment categories (e.g., return visits, new patients, procedures, telehealth) and approximate proportions.
How you define arrival relative to scheduled time (e.g., early, on-time, late), and any cutoffs used in coding.
List roles and counts (e.g., 2 RNs, 1 MA, 1 front-desk, 2 providers). Note any absences or float staff.
Number of exam rooms in use, dedicated procedure rooms, and any rooms reserved or blocked during the sample.
Example steps: check-in -> vitals -> triage -> wait for room -> rooming/assessment -> provider -> orders/tests -> discharge/check-out. Indicate which steps are parallel or sequential.
Median patient wait from arrival (or scheduled time) to being seen by provider. If not calculated, leave blank and describe in notes.
Optional; useful to understand tail experience.
Estimate across observed appointments; helps identify whether visit length variability drives waits.
Select the causes you observed or that your data indicate. Use 'Other' to add specifics.
Describe observed 'Other' causes here.
Document rules used when multiple factors applied (e.g., primary cause selected based on last-mile delay). This improves reproducibility.
Where did most of the waiting concentrate?
Describe if 'Other' was selected.
How much this bottleneck/contributor increases waits.
1.0 10.0
A pragmatic estimate to help prioritize interventions.
1.0 10.0
Explain how you combined impact and ease to set priorities (example: high-impact + easy fix = top priority).
List specific interventions you plan to try. For each, include who is responsible and a short hypothesis (e.g., 'Add one buffer slot 30 minutes after first clinic hour — hypothesis: will reduce clustering and decrease median wait by 10 minutes').
Select one or more small experiments to try rapidly and measure.
Describe the experiment and expected effect.
Suggest at least 3–14 days depending on volume; note how you will measure success.
E.g., median wait, 90th percentile wait, % visits starting within 15 minutes of scheduled time, staff workload impact, patient satisfaction.
Paste URLs to scheduling reports, EHR extracts, or shared spreadsheets that support this audit.
Capture immediate actions, owners, and target dates.
People or groups who should review or authorize experiments (e.g., clinic manager, medical director, operations).
Anything else auditors want to record that didn't fit above (patient experience notes, safety concerns, unusual events).
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