Your key is stored only in your browser — never on any server
🔒Your key is stored locally on your device. All other session data clears when you close the tab. AI calls go directly from your browser to Anthropic — we never see your key or your data.
Don't have a key? Click How to Get a Key tab above for a step-by-step guide.
This will replace all entered values with the benchmark defaults for the selected department and clear any saved data for this department.
⚠️
Report will be cleared
You have an AI Analysis report from your current metrics. Running a new simulation will load different values — your existing report will no longer match the data and will be erased.
To keep the report, click Cancel and use 🖨️ Print to save it first.
σ
CliniqOptimize
AI-powered healthcare quality improvement. No Six Sigma training required.
📊
Enter Metrics
See gaps vs benchmarks instantly
🤖
AI Guides You
Charter, RCA, solutions, control plan
🏥
EHR-Specific
Epic, Cerner, Meditech & more
Your experience level?
Personalizes AI depth and which tools are shown.
🟡
Yellow Belt
New to QI · clinic owners, charge nurses, frontline staff
🟢
Green Belt
Familiar with DMAIC · leads department projects
⚫
Black Belt
Expert practitioner · multi-department programs
⚠ Pick a level to continue.
Connect your API key
CliniqOptimize runs on Anthropic's Claude AI. Paste your key below to get started.
🔒Stored only in your browser. AI calls go directly to Anthropic — we never see your data.
Quick tasks use Haiku (~$0.002). Full analyses use Sonnet (~$0.08).
About CliniqOptimize
Why this tool exists, who it's for, and what it does
👨⚕️
Ryan
Physician Assistant · 15+ years clinical experience
Global HealthSix Sigma Green BeltHealth Systems ImprovementMilitary Medicine
🎯 Why I Built This
Over 15 years practicing as a Physician Assistant across urgent care, internal medicine, military medicine, and occupational health, I have witnessed firsthand how dramatically patient safety improves when a clinical team intentionally applies proven process improvement methods. The progress is real and measurable — and deeply encouraging.
Yet healthcare still operates far from Six Sigma levels of reliability. Larger health systems with dedicated quality departments may approach 3–4 sigma in select processes. Most facilities do not. And for small to mid-sized clinics, the gap is far wider.
That gap — and the preventable harm it causes — is what motivated this application. A solo practitioner running an urgent care clinic deserves access to the same quality infrastructure as a 500-bed health system. Not a watered-down version — the real thing, adapted for their context and their EHR.
🚀 What CliniqOptimize Does
CliniqOptimize puts the full DMAIC methodology — Define, Measure, Analyze, Improve, Control — into the hands of any clinician or quality team, regardless of their formal Six Sigma training. Every analysis is grounded in peer-reviewed evidence (178+ verified citations across PubMed and Consensus), calibrated to your department, and translated into specific actions inside your EHR.
One design principle sets this tool apart: every recommendation names the specific EHR feature to implement it. Six Sigma tells you what to improve. Your EHR is the most powerful instrument for making it stick. This tool connects the two.
⚙️ Features
📊 Dashboard
Sigma, DPMO, Cpk · 9 departments · live benchmarks
🎯 Define — AI Charter
Problem statement, SMART goal, business case, milestones
178+ verified citations · PubMed + Consensus · APA 7th · Live DOI
🤖 AI Models
Claude Sonnet 4.6
All DMAIC phases
Claude Haiku 4.5
Real-time & quick tasks
PubMed + Consensus
Live citation verification
Dashboard
Enter metrics · see gaps vs. benchmarks
📋📥 Auto-fill from Dashboard
1
Set department and EHR in the status bar above
2
Enter your metric values — color codes show gaps vs. benchmarks instantly
3
Click ✨ AI Analysis for a full AI-powered bottleneck report
✅Sigma, DPMO, COPQ, top bottlenecks — live
🔑Connect Anthropic API to unlock all analysis features
~$0.08/analysis · $5 → ~13 full runs
AI ConnectedBelt: YellowEHR: EpicDept: Emergency Department
Performance Summary
Live · color-coded vs. benchmarks
Emergency Department
💰 CMS Revenue Context
ⓘ
💰 CFO / Executive
CMS Revenue Context — Why Enter This?
These 4 fields let the AI calculate real dollar estimates for your penalty exposure and COPQ (Cost of Poor Quality). Without them, reports use percentages only. With them, every metric gap becomes a specific dollar figure — e.g., "your current readmission rate puts you at risk of a $847,000 HRRP penalty."
All calculations use the CMS IPPS formula: Payment = Base Rate × MS-DRG Weight × Wage Index ± Adjustments. Penalty programs applied: HRRP (up to 3%), VBP (±2%), HACRP (1%).
💡 Quick reference:
HRRP up to 3% of all Medicare DRG payments (ACA §1886(q)) ·
VBP ±2% of base DRG payments (~$1.7B FY2025 pool) ·
HACRP 1% penalty for bottom 25% on HAC measures ·
Combined maximum exposure: up to 6% of Medicare base operating DRG payments
Enter Your EHR Metrics
Update instantly · click Analyze for AI deep-dive
Executive:
🔬
Root cause analysis will appear here
Click "Run Root Cause Analysis ✨" to identify key drivers.
AI Quick Wins
Top Bottlenecks
Industry benchmarks
Efficiency by Department
Live
🛡️ Patient Safety Measures
Live from entered data
—
Define
Define the problem · set a SMART goal
📋📥 Auto-fill from Dashboard
1
Click 📥 Auto-fill from Dashboard to pull your worst metric
2
Edit the SMART goal — or click ✨ Generate to AI-draft it
3
Click Generate Project Charter ✨ to produce the full charter
✅Print-ready DMAIC charter with SMART goal
📄
Charter will appear here
Fill in the fields above and click "Generate Project Charter ✨"
Measure
Calculate sigma level from real defect data
📋📋 Have defect counts from your EHR
1
Enter sample size, defect count, and opportunities per unit
2
Add data points for an SPC control chart (optional, ≥8 points)
3
Click Calculate to get certified sigma, DPMO, and Ppk
✅Sigma level, DPMO, and Cpk indices
📊 Dashboard (Estimated)
Computes sigma from metric gaps vs benchmarks — useful for quick identification of problem areas. Not statistically certified. Use for triage and prioritization.
🔬 Measure (Validated)
Computes sigma from observed defects and real data series using DMAIC-standard methods. Required for project sign-off, Ppk, and control limit calculation.
Defect / Error Count Required
Use observed defects from EHR reports
Process Statistics — optional, unlocks Ppk & UCL/LCL
USL/LSL required for Ppk · Mean/SD auto-compute if blank
💡 Where to find these: Mean & SD from your EHR reporting module (Epic Reporting Workbench, Cerner Operational Reports). USL = your performance target or policy limit.
Individual Data Series — optional, enables MR̄/d₂ control limits
Paste raw values from EHR export chart method
ne order TAT). Mean and SD auto-fill if blank above.
✅
Baseline Validated — Dashboard Now Using Measured Data
Sigma, DPMO, and Ppk on the Dashboard are now sourced from your measured defect data. AI analysis prompts will include these validated statistics.
—
Process Sigma
1σ3σ4.5σ6σ
DPMO
—
Defects per million
First-Pass Yield
—
Single step
Rolled Throughput Yield
—
Multi-step yield
Ppk (long-term)
—
≥1.33 = capable
UCL (Upper Control Limit)
—
LCL (Lower Control Limit)
—
Process Mean
—
Std Deviation
—
Analyze
Find root causes · AI ranks by impact
📋📋 Complete Define first
1
Click Pull from Define to load your problem statement
2
Add causes to each fishbone branch — or let AI fill them
3
Click Run Root Cause Analysis ✨ to rank causes by impact
✅Ranked root causes ready for Improve
Problem Statement (Fish Head)
The specific defect or outcome you are analyzing
The "effect" — paste your problem statement here.
6M Fishbone Diagram
Enter contributing factors for each category
👤 People
Human factors: staffing, training, behavior, communication, fatigue
💡 Examples to consider
• Insufficient staffing during peak hours (5–8pm surge) • Providers spending 2.8h/day on EHR vs. patient care • Triage nurses not cross-trained for MA-initiated rooming • Alert fatigue causing staff to override critical warnings • New hire orientation not covering EHR workflow shortcuts
Long D2P → Why? → Only 1 triage nurse at 5pm → Why? → Schedule built on average demand, not peak → Why? → No data-driven staffing model exists
📋 Method (Process)
Workflow design: procedures, protocols, handoffs, standard work, sequencing
💡 Examples to consider
• No MA-initiated rooming protocol — providers walk to waiting room • Bed assignment requires phone call to charge nurse (not EHR-automated) • Lab specimens collected in batches rather than on continuous flow • Discharge orders written late due to no standard morning round workflow • Medication reconciliation done verbally, not verified in EHR
High med error rate → Why? → Reconciliation done at discharge rush → Why? → No standard workflow for admission meds → Why? → SOP last updated 4 years ago
💻 Machine / Technology
EHR configuration, equipment, system design, alerts, downtime, integration
💡 Examples to consider
• Epic SmartSet missing 8 commonly ordered ED medications • 92% of drug-drug interaction alerts overridden (alert fatigue) • Bed management board not auto-updating — requires manual refresh • Lab interface sends results to wrong provider inbox 3% of the time • EHR downtime averages 45 min/month during peak hours
Providers miss critical lab results → Why? → Result routed to on-call inbox, not primary → Why? → EHR routing rule not updated when attending changed → Why? → No EHR audit process for routing rules
📦 Material
Supplies, medications, forms, information inputs, data quality, patient information
💡 Examples to consider
• Incomplete patient history from referring facility (missing allergy list) • Medication formulary not updated — providers ordering non-stocked drugs • Lab specimen labeling errors from pre-printed vs. bedside-printed labels • Discharge instruction templates outdated — missing post-visit care steps • Paper triage forms used in parallel with EHR — dual documentation waste
Medication errors at admission → Why? → Home med list incomplete → Why? → Patient brought paper list, not verified in EHR → Why? → No standard process for importing external med records
📊 Measurement
Data collection, metrics definition, reporting accuracy, KPI visibility, feedback loops
💡 Examples to consider
• D2P time measured from EHR registration, not physical arrival (undercounts waits) • Medication error rate only captures events reaching patients — near-misses not tracked • No real-time dashboard — managers see yesterday's data, can't respond to today's surge • Chart completion measured weekly, not daily — problems discovered too late • Staff don't know their own unit's sigma level or DPMO — no feedback loop
Process seems fine by metrics but patients complain → Why? → We only measure D2P, not total wait → Why? → EHR only timestamps provider first contact → Why? → Arrival-to-triage time not captured in our workflow
• Triage area too far from exam rooms — physical transport adds 4 min per patient • No culture of safety reporting — staff fear blame when flagging near-misses • Flu season causes 30% volume surge without proportional staffing increase • Noisy nurse station reduces communication accuracy during handoffs • Regulatory change (new CMS documentation requirement) added 12 min/visit
Near-misses not reported → Why? → Staff fear punitive response → Why? → Last reported event led to disciplinary action → Why? → No just culture policy or non-punitive reporting framework
⁉️ 5-Why Quick Tool (optional — drill down on a specific symptom)
Start with an observable symptom, then ask "Why?" five times to reach the true root cause. Click 📌 Add & Auto-sort to have AI classify the chain and place it in the correct fishbone bone automatically.
Why 1
Why 2
Why 3
Why 4
Why 5
Choose bone
AI Fishbone Analysis
endations
Root Cause Scope:
Improve
Generate evidence-based solutions
📋📋 Complete Analyze first
1
Root causes from Analyze load automatically — select one
2
Click ⚡ Generate Solution ✨ for evidence-based interventions
3
Review, edit, and send the solution to your Control plan
✅EHR-specific solutions ranked by impact
Root Cause to Address
Choose one — a focused solution will be generated
Run Root Cause Analysis in Analyze first, then return here.
🚀
Solution will appear here
Select a root cause above and click "Generate Solution ✨"
Control
Lock in gains · build a control plan
📋📋 Complete Improve first
1
Click ⬆ Pull from Improve to load your implemented changes
2
Click Generate Control Plan ✨ to build a 90-day sustainment plan
3
Export or copy the plan for your team
✅90-day control plan with SPC and audit schedule
🛡️
Control plan will appear here
Click "Generate Control Plan ✨" to lock in your gains.
FMEA
Identify failure modes before they cause harm
📋📋 Best after Define
1
Click AI Auto-Generate FMEA ✨ to seed rows from your metrics
2
Edit severity, occurrence, and detection scores (1–10 each)
3
RPN = S × O × D — rows with RPN ≥125 are high priority
✅Failure modes ranked by RPN with controls
Add Failure Mode
Process Step
Failure Mode
S
O
D
RPN
Priority
Value Stream Map
Map steps · find waste · redesign flow
📋📋 Know your process steps
1
Select a template or map your current-state steps and cycle times
2
Click Analyze Current State ✨ to identify waste and bottlenecks
3
Build the future state and click Analyze Future State ✨
✅Waste analysis with PCE% and future state
Current State — Process Steps
Enter steps and actual times from observation
Vol:
💰 Financial grounding
Daily volume — why enter this?
Without volume, the AI cannot calculate financial impact and will describe improvements directionally only. With volume, financial impact is pre-calculated in JavaScript (not AI-estimated) before the analysis runs.
Step Name
Process min
Wait min
Value Added?
Staff
Move / Del
Current State Map
———
🟢 Value-added🔴 Non-Value-Added🟡 Bottleneck ≥20min
Future State — Redesigned Flow
Design improved process · reduce waits · mark kaizen bursts
✅ Copied from current state — modify times to reflect your improvement targets.
burden, or workflow mismatches. Include the role affected, the EHR screen or module, and any workarounds staff are using. The more specific, the more targeted the analysis.
AI Agents🚧 Under Development
Five parallel AI agents · full QI analysis
📋Prereq: Enter Dashboard metrics for best results.
1
What agents receive
All 5 agents receive the same context: department, EHR, belt level, and all entered metric values vs benchmarks — including gap % and sigma. Completed Measure phase data (validated sigma/DPMO) is included if available. Blank metrics are excluded. Agents do not receive problem statements, fishbone entries, or text from other tabs.
2
Run all 5 agents
Agents run in parallel. Each specializes in a domain: 📊 Process Improvement Lead (DMAIC charter), 🏥 Clinical Quality Analyst (patient safety, CMS/TJC), 📈 Statistical Expert (sigma, capability, SPC), 💻 EHR Workflow Optimizer (EHR-specific configuration), 👔 Operations Manager (staffing, capacity, throughput). Total time is the slowest single agent, not the sum.
3
Verify citations
Use 🔍 Verify Citations to run the 3-Agent Citation Verifier on agent output — checks claims against PubMed and Consensus databases. Use 🔗 Live DOI Resolver to verify any specific DOI in real time. The app flags unverified statistics and unsupported claims.
4
Cross-reference results
Look for themes appearing across 3+ agents — these are your highest-confidence priorities. Use the Process Improvement Lead output as Define phase input, EHR Optimizer for Improve Quick Wins, and Clinical Quality Analyst output for board and quality committee presentations. Use 🖨️ Print to save as PDF.
✅Output: Five parallel AI analyses: process, clinical, finance, safety, RCA
🚧
AI Agent Suite — Under Development
This feature is currently being redesigned and is not available. The 5-agent parallel analysis, citation verifier, and DOI resolver will return in a future release with improved accuracy and reliability. All other CliniqOptimize features (Dashboard, Define, Analyze, Improve, Control, FMEA, VSM, Suggestions, Human Factors) are fully operational.
Active AI Model ⓘ
Claude Sonnet 4
Sonnet 4 is recommended for all tasks. Switch to Opus 4.6 for complex FMEA or strategic analysis. Haiku 4.5 is used automatically for live monitoring.
🔍 3-Agent Citation Verifier
Anti-Hallucination🌐 Live Web Search
Each agent performs real-time web search independently — no shared context between searches. Consensus requires ≥2/3 agents in agreement. Based on CoVe (Dhuliawala et al. ACL 2024), Chain-of-Thought (Wei et al. NeurIPS 2022), anti-sycophancy (Burns et al. 2022). ⚠️ Note: uses Anthropic web search ($10/1k searches) — one verification run uses up to 9 searches (~$0.09) plus token costs.
🔬 Agent 1 — Primary Investigator
Sonnet 4 · 🌐 Web search · CoVe atomic verification
Waiting to run...
🧪 Agent 2 — Devil's Advocate
Opus 4.6 · 🌐 Web search · Searches for contradictions
Waiting to run...
📚 Agent 3 — Literature Specialist
Haiku 4.5 · 🌐 Web search · Verifies DOI + APA format
Waiting to run...
🏛️ Consensus Verdict
Each agent performed independent live web searches — results reflect actual online sources found, not training data. Synthesized by Sonnet 4 · ≥2/3 consensus rule · CoVe (Dhuliawala et al. ACL 2024) reduces hallucination ~28%
⏳ Running 3 agents with live web search...
🔗 Live DOI Resolver
CrossRef APIFree · No Auth
Queries the CrossRef REST API (api.crossref.org) directly from your browser to confirm each DOI in our citation library resolves to a real published paper with matching title, authors, and year. No API key required.
⏳ Querying CrossRef API...
💡 How AI Agents Work
When you click Run All Agents, the app reads all your entered dashboard metrics and compares each one against its benchmark. It then fires 5 API calls simultaneously — each agent acts as a different expert analyzing the same data from their own professional lens. Results arrive in parallel; if one agent errors, the others still display.
Agent
Focus
Model
📊 Process Improvement Lead
Top 3 DMAIC priorities with sigma improvement targets and timeline
Sonnet 4
🏥 Clinical Quality Analyst
Patient safety risks + EHR-specific CDS mitigations and regulatory implications
Sonnet 4
📈 Statistical Expert
Process capability verdict, sigma/DPMO in clinical terms, statistical interventions
Opus 4.6
💻 EHR Workflow Optimizer
3 specific EHR configuration changes — SmartSets, BPA alerts, order panels
Sonnet 4
⏱ Operations Manager
Staffing, scheduling improvements and capacity analysis based on throughput
Sonnet 4
💡 Pro tip: Look for themes that appear in 3+ agents — those are your highest-confidence priorities. Each agent sees the same data but answers a different question, giving you a 360° view in under 30 seconds.
For best results: Enter your actual metrics on the Dashboard · Select your EHR in the status bar · Set your belt level (agents adjust language complexity accordingly)