Synthetic data This demo uses fabricated data for "Sample Children's Hospital," a fictional 200-bed pediatric academic medical center. No real patient or institution data is shown. Methodology, structure, and visualization patterns reflect what an actual engagement deliverable looks like.
Sample dashboard demo

What you'd see in product, across the four lenses.

Every Perioptimal engagement produces a working analytics layer that the institution operates after the engagement concludes. This demo walks through what that layer looks like across all four lenses, using synthetic data for a fictional pediatric academic medical center. The methodology is identical to engagement deliverables -- only the data is fabricated.

Institution:Sample Children's Hospital (fictional) Period:Q1 2026 Volume:3,247 cases Roster:18 attendings · 12 CRNA/AA · 8 ORs + 4 ASC
Lens 01 · The Patient

Outcomes, harm reduction, recovery, experience.

Working backward from preventable adverse events to the latent conditions that produced them, and forward from the patient's first encounter to PACU discharge. The patient lens is examined first on every surface, without exception.
Same-day cancellation rate
2.7%
↑ 0.4 pts vs. trailing 90d
Q1 2026 · institution · 87 cancellations
Adverse events / 1,000 cases
4.2/ 1k
↓ 0.8 pts vs. baseline
Phase-attributed · severity-weighted
Avg PACU recovery time
68min
flat vs. trailing 90d
Excludes prolonged-stay outliers
Pre-op completeness rate
86%
↓ 2.1 pts — investigate
Documentation timeliness, all phases

Same-day cancellation rate · daily, Q1 2026

90 days · trended
5% 4% 3% 2% 1% Jan Feb Mar target 3.0% Feb 17 peak

What this surfaced: A discernible upward shift in mid-February driven by patient-related factors (NPO violations, day-of medication issues). Decomposed by reason in the next panel. Pre-op completeness rate also dropped 2.1 points in the same window -- the two are likely related.

Cancellation by reason

Q1 · n=87
87 cancellations Patient (38%) Anesthesia (20%) Surgeon (17%) Scheduling (12%) System (8%) Other (5%)

Avoidability: 64% of patient-related and 71% of scheduling cancellations are classified avoidable. The structural lever is upstream pre-op coordination, not day-of recovery.

Adverse events by phase · severity-weighted

Q1 · n=14 events · rate per 1k cases
7 5 3 1 Cardiac 5.4 / 1k General 3.4 / 1k Ortho 2.4 / 1k Neuro 3.0 / 1k ENT 1.7 / 1k Urology 1.4 / 1k Pre-op Intra-op PACU Post-discharge

Cardiac post-op cluster: Cardiac service shows elevated PACU-phase events compared to other services. The methodology traces this back to a specific recovery-phase staffing pattern at end-of-day. The intervention target is structural rather than individual.

Patient lens · methodology output

February cancellation spike resolves to upstream pre-op coordination

The mid-February rate inflection traces to a 7-day window of elevated patient-related cancellations. Decomposition: 68% NPO violations and 19% day-of-medication issues. Pre-op completeness rate fell 2.1 points in the same window. The recommendation is upstream pre-op screening reinforcement, not day-of process improvement -- the visible failure (cancellation rate) is a downstream symptom of an upstream coordination gap.

Cardiac PACU-phase event rate is structurally elevated but follows a recoverable pattern. Recommendation: end-of-day cardiac PACU staffing reinforcement targeted at 16:00-18:00 window where rate concentrates.

Lens 02 · The Team

Workload, supervision, on-call, sustainability.

Surgery, anesthesia, nursing, PACU, ancillary services. Optimize resource use and build the fair, transparent environment that makes coordination work. Every clinician sees how their numbers compare to the roster -- subjective claims about workload become observable data.
Avg attending workload (CMWV)
412
range 268 – 587
Case-mix-weighted · Q1 institution
Avg supervision ratio
3.8: 1
peak 5.2:1 · investigate
Compliant on average · degrades Tue/Thu PM
Late finish rate (after 18:00)
23%
↑ 3.2 pts vs. Q4 2025
Cardiac & General concentrated
Burnout signal range
38 – 78
2 attendings > 70
Composite z-score · relative ranking

Attending workload distribution

CMWV · Q1 · n=18
600 450 300 150 0 avg 412 ! A13 A09 A07 A04 A15 A02 A11 A18 A06 A12 A01 A16 A08 A14 A03 A17 A10 A05 Anesthesia attendings, sorted by case-mix-weighted volume

Att-07 burnout flag: not the highest workload but combination of workload, late finishes (28% vs. 23% institution), call burden (top quartile), and zero PTO taken in Q1 produces a composite burnout signal of 78 (relative to roster). Recommendation: redistribute Q2 call load.

Supervision ratio · time-of-day x day-of-week

avg ratio · Q1
07−09 09−12 12−14 14−16 16−18 Mon Tue Wed Thu Fri 3.5 3.6 3.4 3.9 4.1 3.7 3.8 3.5 5.2 4.3 3.6 3.7 3.4 4.0 4.2 3.8 3.9 3.6 5.0 4.4 3.4 3.5 3.3 3.8 4.0 ratio

Tue/Thu 14−16h slip: ratio degrades to 5.0−5.2:1 specifically at this window because complex cardiac cases overlap with mid-shift transitions. Average compliance hides the slip pattern.

On-call burden distribution · primary call frequency

Q1 · nights & weekends · cardiac stipend tagged
15 11 7 3 avg 7 nights ! A07 A13 A09 A04 A15 A02 A11 A18 A06 A12 A01 A16 A08 A14 A03 A17 A10 A05 Cardiac call (stipend) General call

Cardiac call concentration: 5 attendings carry the cardiac call rotation, but Att-07 carries the top end at 14 nights (44% above cardiac avg). Combined with workload concentration and zero PTO usage, this is the structural driver of the 78 burnout signal. Recommendation: redistribute Q2 cardiac call to bring Att-07 closer to the cardiac avg of 12.

Team lens · methodology output

Att-07 burnout flag is structural, not individual

The composite signal of 78 (out of 100) for Att-07 decomposes as: workload top-quartile (acceptable), late-finish rate 28% vs. roster avg 23% (high but not flag-level alone), cardiac call frequency 14 nights vs. cardiac peer avg 12 (concentrated), PTO usage 0 days in Q1 (significant). The combination produces the flag, not any single dimension. Recommendation: cardiac call redistribution + mandatory PTO usage policy reinforcement.

Tue/Thu 14:00−16:00 supervision ratio degradation traces to a recurring service-mix combination (cardiac complex case overlap with mid-shift transition). Recommendation: structural staffing pattern revision for these specific windows.

Lens 03 · The Day

The actual rhythm of the operating room.

First cases, turnovers, blocks, cancellations, end-of-day variance. The day is where upstream failures become visible. Every day-lens metric is decomposed into the upstream cause that produces it -- often originating in the team or patient lens.
First-case on-time start
71%
↑ 2 pts vs. Q4
Target 80% · pre-op staffing 41% of late starts
Avg turnover time
38min
flat · variance is the signal
P75 53m · P95 72m
Block utilization
84%
↓ 1.8 pts vs. Q4
General Surgery 67% — investigate
End-of-day variance
+47min
vs. predicted finish
Cardiac drives 64% of overrun

First-case start time · cause attribution

Q1 · n=412 late starts
Cause attribution · % of late starts Pre-op staffing 41% Surgeon arrival 28% Anesthesia readiness 19% Patient-related 8% Equipment / room 4% "60% of variance is upstream of the OR director's direct control"

Pre-op staffing dominates: the largest single driver of late starts is pre-op staffing readiness, not surgeon or anesthesia behavior. The fix is upstream of the OR. Most institutions discover that 60-80% of first-case variance comes from causes outside the OR director's direct control.

Turnover variance · service distribution

Q1 · min
100 75 50 25 0 Cardiac General Ortho Neuro ENT Urology 2 outliers

Cardiac variance dominates: median is reasonable but the wide IQR and two outliers (88 + 92 min) drive the institutional avg up. Decomposition reveals outliers cluster on Tuesdays/Thursdays (overlapping with the supervision-ratio degradation).

End-of-day variance · predicted vs. actual finish

Q1 · per OR per day · n=520
+180 +90 0 −90 predicted = actual Cardiac General Ortho Neuro ENT Urology +82m median +12m median −20m median

Cardiac drives 64% of overrun: the institutional +47 min average end-of-day variance is concentrated in cardiac. Decomposing further: cardiac runs +82 min median over predicted finish. The booked-vs-actual gap is the actionable signal -- the schedules are systematically optimistic for cardiac case-mix.

Day lens · methodology output

Three findings, all upstream of the day lens

The first-case start variance traces 60% to upstream pre-op staffing rather than OR-side behavior. The recommendation is structural -- pre-op staffing increase + arrival-time policy adjustment -- not generic process improvement.

Cardiac end-of-day variance reveals systematically optimistic case-mix scheduling. The schedules predict 82 minutes earlier than reality. The fix is upstream booking realism, not late-day compression. (Compression would land on the same Att-07 already showing burnout signals.)

Block utilization at 84% institutional is acceptable but General Surgery at 67% with high release-and-unfilled rate suggests demand-side or surgeon-allocation issue. Detailed in the institution lens.

Lens 04 · The Institution

Capacity, contribution, sustainability, growth.

Where the prior three lenses translate into institutional value: capacity, contribution margin, sustainability, growth. Examined last, because it follows from the others. Get the first three right and the fourth follows.
Total cases · Q1
3,247
↓ 1.8% vs. Q4
+2.4% YoY · deidentified
Cases / OR / day
5.2
flat
P50 institution · 8 ORs
Capacity headroom
11%
structural
Operational ceiling · not nominal
Service-line CM
$4.2M
↓ $0.3M vs. Q4
Q1 contribution margin

Block utilization by service

Q1 · booked / released / unfilled
% of allocated block time Cardiac 91% ENT 88% Neuro 87% Ortho 84% Urology 79% General 67% Used Released & rebooked Released, unfilled

General Surgery unfilled signal: 11% released-and-unfilled vs. institutional 4%. Combined with elevated release-and-rebooked rate, this points to a demand-side or surgeon-allocation pattern. Either insufficient case volume to fill blocks or a coordination gap in rebooking. Recommendation in next viz.

Service-line contribution margin vs. capacity

Q1 · per service
$1.5M $1.0M $500k $200k Cardiac $1.4M General $0.7M Ortho $0.9M Neuro $0.6M ENT $0.4M Urology $0.2M +$300k recoverable

General Surgery is the recoverable opportunity: contribution margin is below trend and below capacity-implied potential. The dashed overlay is the modeled CM at full block utilization (operational, not nominal). The fix is upstream of the day lens -- demand-side coordination.

Multi-month trend · cases & on-time rate

trailing 12 months · institution
1,200 1,050 900 750 85% 78% 71% 64% Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Q1 2026 reporting Monthly cases First-case on-time %

Trend stability: volume and on-time rate trended together through Q4 2025, then diverged in Q1 2026. The Q1 first-case rate dropped 6 points without a corresponding volume change -- the slip is operational, not demand-driven. The diagnosed driver is the pre-op staffing pattern surfaced in the day lens.

Institution lens · methodology output

The fourth lens follows from the first three

$0.3M Q1 contribution margin shortfall is concentrated in General Surgery's underutilized blocks. The fix is upstream of the day lens: surgeon-side allocation patterns and demand-side coordination. Modeled recovery: $300k per quarter at 78% utilization (achievable target).

Capacity headroom of 11% is structural, not operational -- the institution can absorb meaningful volume growth without infrastructure investment, conditional on resolving the General Surgery utilization issue. Cardiac is at the operational ceiling and adding cardiac volume would require addressing the Att-07 burnout signal first.

The 24-month measurement window will attest to recovery of: (a) General Surgery utilization to 78%+, (b) cardiac end-of-day variance reduction to under +30 min median, (c) Att-07 burnout signal reduction to under 60 via call redistribution, (d) first-case on-time rate recovery to 78%+.

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