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Case Study: Introduction to Lean Practices in Healthcare

Occiden and Company
1 day ago
3 min read

Cross-Industry Lessons with Measurable Results

t Occiden and Company, we’ve developed a Lean-first, digital-forward playbook adapted from high-performing non-healthcare operations (manufacturing and e-commerce fulfillment).

Imagine a multi-site primary care group (8 providers) and a dermatology specialty clinic (4 providers) working to reduce patient wait times, tighten revenue leakage, and cut documentation burden. At Occiden and Company, we’ve developed a Lean-first, digital-forward playbook adapted from high-performing non-healthcare operations (manufacturing and e-commerce fulfillment).

When applied in composite scenarios like these, clinics can see outcomes such as:

Visit cycle time ↓ 27% (check-in to check-out)
On-time appointment starts ↑ 22 percentage points
No-show rate ↓ 19% via targeted outreach and smart overbooking
Claims first-pass acceptance (FPA) ↑ 8 pp
Provider after-hours documentation ↓ 38% with ambient AI
Throughput (completed visits/provider/day) ↑ 15–18%

Note: Outcomes are drawn from a mix of engagements and industry benchmarks; actual results vary by context.

Client Profile & Challenge

General medicine group: chronic disease management, high phone volume, long check-in lines, variable provider utilization.
Dermatology clinic: procedure-heavy days, room turnover friction, charting backlog, and rising no-shows.
Shared pain points: fragmented workflows, inconsistent room readiness, manual intake, and documentation spillover after hours.

Cross-Industry Analogy (The Catalyst)

We mapped typical clinic flows against a Tier-1 auto components plant and a mid-size e-commerce fulfillment center:

Manufacturing lens: value stream mapping, takt/throughput focus, 5S for room setup, visual controls, andons for “flow breaks.”
Fulfillment lens: digital “front door,” predictive demand (no-show risk), slotting/kanban for supplies, and real-time control towers to orchestrate flow.

Comparative Analysis: What Transfers from Industry to Clinics

Metric / Practice	Non-Healthcare Baseline	Clinic Baseline (Composite)	Transferable Practice
Cycle/Lead Time	58 min → 39 min (pick-pack-ship)	84 min → 61 min (visit cycle)	Value stream mapping + 5S; pre-load work upstream
On-Time Starts	72% → 91% (dock times)	48% → 70% (appointments)	Visual controls & room readiness checklists
No-Shows / No-Picks	12% → 5%	14% → 11%	Predictive scoring + targeted reminders; smart overbooking
Right-First-Time	92% → 98%	86% → 94% (claims FPA)	Poka-yoke intake; RPA pre-checks
After-Hours Work	Overtime ↓ 35%	Charting ↓ 38%	Ambient AI documentation
Throughput	Lines/hr ↑ 19%	Visits/provider/day ↑ 15–18%	Command-center view of flow

What We Implemented (Illustrative 12-Week Sprint)

Diagnose flow: Value stream mapping; time-in-state study; identify failure modes.
Stabilize the floor: 5S + standard work in rooms; intake pre-work upstream.
Digitize where it matters: Online booking, eligibility pre-check, predictive no-show outreach, ambient AI charting.
Orchestrate & sustain: Mini “command center” view; daily huddles; weekly KPI reviews.

Why This Works (And What’s New in AI)

Lean exposes the work; digital accelerates it. Stable flow ensures AI and automation stick.
Ambient clinical intelligence reduces charting time and cognitive load.
Predictive operations flag no-shows and optimize scheduling.
Hospital-grade flow control scaled to clinics provides real-time oversight.

Measured Impact (Composite Benchmarks)

Access & flow: days-to-next-available ↓ 29%; visit cycle time ↓ 27%.
Revenue integrity: FPA claims ↑ 8 pp; denial rework ↓ 21%.
Experience: patient NPS ↑ 12 points; staff satisfaction ↑ 15 points.
Clinician time: after-hours notes ↓ 38%.

6-Month ROI Model (Illustrative)

+3 completed visits/provider/day at $140 net yield ≈ +$84K/year (per 4-provider pod)
Denials reduced 20% on $2.4M claim volume ≈ +$48K/year
Overtime & temp staff avoided ≈ +$22K/year
Total uplift: ≈ $154K/year per pod (before tech costs)

What This Means for Clinics

General practice: stabilize variability, reduce check-in friction, protect provider time.
Specialty care: improve room readiness, sequence staff tasks, balance provider/room load.