# Decision Tree: Complete Examples #decision-tree #examples #case-studies #real-decisions Master decision trees through detailed real-world examples showing complete tree construction, probability assessment, and outcome analysis. ← [[probability-basics|Back to Probability Basics]] ## 📚 Example Categories 1. [Career & Education Decisions](#career-education) 2. [Business Strategy Trees](#business-strategy) 3. [Personal Financial Decisions](#financial-decisions) 4. [Medical & Health Choices](#medical-decisions) 5. [Investment & Risk Analysis](#investment-analysis) --- ## 🎓 Career & Education Decisions {#career-education} ### Example 1: MBA vs. Work Experience Decision **Background:** 28-year-old software engineer with 5 years experience deciding between immediate MBA or continuing work for 3 more years. **Current Situation:** - Salary: $95,000 - Savings: $50,000 - Goal: Senior management by age 40 - MBA cost: $180,000 (tuition + opportunity cost) #### Complete Decision Tree Structure ``` MBA Timing Decision 🔷 ┌─────────┴─────────────┐ MBA Now Work 3 Years │ │ Admission Results 🔶 Career Progress 🔶 ┌─────────┴─────────┐ ┌─────────┴─────────┐ Top School Good School Promotion Lateral (25%) (65%) (70%) (30%) │ │ │ │ MBA Outcome 🔶 MBA Outcome 🔶 │ Delayed MBA 🔷 ┌─────┴─────┐ ┌─────┴─────┐ │ │ Success Average Success Average │ Apply Later (80%) (20%) (75%) (25%) │ │ │ │ │ │ │ Later Results 🔶 $140K $120K $130K $110K $125K ┌─────┴─────┐ at 32 at 32 at 32 at 32 at 31 Success Struggle (60%) (40%) │ │ $135K $115K at 35 at 35 ``` #### Detailed Probability Assessment **MBA Admission Probabilities (Based on Profile Analysis):** ``` Profile Strength: - GMAT: 720 (strong) - GPA: 3.6 (good) - Work experience: 5 years (adequate) - Leadership: Limited (weakness) - Essays/Recommendations: Expected strong Admission Consultant Assessment: Top 10 School (Harvard, Stanford, Wharton): 25% Good School (Top 15-25): 65% Rejection/Wait: 10% ``` **MBA Success Probabilities:** ``` Top School Success Rate: Based on employment reports + career services data: - High-paying role within 6 months: 80% - Average outcome: 20% Good School Success Rate: - High-paying role within 6 months: 75% - Average outcome: 25% ``` **Career Progression Without MBA:** ``` Current Performance: Top 20% performer Company Promotion History: 70% of top performers promoted within 3 years Industry Trends: Technical roles increasingly require leadership skills Promotion Probability: 70% Lateral Movement: 30% ``` #### Expected Value Calculations **MBA Now Path - Top School:** ``` Costs: - Tuition: $120,000 - Living expenses: $60,000 - Opportunity cost (2 years salary): $190,000 Total Cost: $370,000 Benefits (Success Case - 80% probability): - Starting salary at 30: $140,000 - Expected growth: 8% annually - Salary at 40: $302,000 Net Present Value (10% discount rate): Success (80%): $1,650,000 lifetime - $370,000 cost = $1,280,000 Average (20%): $1,200,000 lifetime - $370,000 cost = $830,000 Expected Value: (0.8 × $1,280,000) + (0.2 × $830,000) = $1,190,000 ``` **Work 3 Years Path:** ``` Promotion Case (70%): - Salary progression: $95K → $125K by year 3 - Later MBA outcomes: 60% success rate - Career acceleration at age 35 No Promotion Case (30%): - Salary progression: $95K → $105K by year 3 - Later MBA less competitive - Slower career advancement Expected Value Analysis: Promotion path: $1,100,000 lifetime value No promotion path: $850,000 lifetime value Expected: (0.7 × $1,100,000) + (0.3 × $850,000) = $1,025,000 ``` #### Decision Analysis Results **Path Comparison:** 1. **MBA Now (Top School): $1,190,000 expected** 2. **MBA Now (Good School): $1,050,000 expected** 3. Work 3 Years: $1,025,000 expected **Key Insights:** - MBA now has higher expected value IF admission to top school - Risk: 10% chance of rejection makes work path safer - Time value: Earlier career acceleration compounds over time **Sensitivity Analysis:** - If promotion probability increases to 85%: Work path becomes optimal - If MBA costs decrease by 25%: MBA path advantage increases significantly - If discount rate increases to 15%: Present value favors work path **Final Decision Factors:** ``` Quantitative: MBA now slightly better expected value Qualitative Considerations: + MBA provides broader network + Career flexibility increases + Personal growth through education - High financial risk and stress - Two years out of workforce - Opportunity cost of current momentum Decision: Apply to MBA programs while continuing work Strategy: Accept only if admitted to top 10 school ``` --- ### Example 2: Graduate School vs. Industry Experience **Background:** Recent computer science graduate choosing between PhD program, master's degree, or entering tech industry. #### Decision Tree Structure ``` Post-Graduation Path 🔷 ┌─────────┬─────────┬─────────┐ PhD (CS) MS (CS) Industry │ │ │ Completion 🔶 Completion 🔶 Job Market 🔶 ┌─────┴─────┐ ┌─────┴─────┐ ┌─────┴─────┐ Success Dropout Success Dropout FAANG Good Average (75%) (25%) (95%) (5%) (15%) (50%) (35%) │ │ │ │ │ │ │ Academic 🔷 Tech High Entry $150K $110K $85K ┌─────┴─────┐ Entry Paying Level │ │ │ Tenure Industry $95K Jobs $95K Tech Tech Tech Track R&D │ $120K │ Path Path Path (40%) (60%) │ │ │ │ │ │ │ │ │ │ │ │ │ │ $120K $140K │ │ │ $300K $200K $150K tenure at 28 │ │ │ at 30 at 30 at 30 at 35 │ │ │ $180K $220K $160K at 30 at 30 at 30 ``` #### Probability Assessment Process **PhD Completion Rates:** ``` Reference Class: CS PhD programs at target universities Data Sources: - NSF Survey of Earned Doctorates - University department data - Advisor consultation Base completion rate: 65% Personal factors: + Strong undergraduate performance: +5% + Research experience: +3% + Advisor match: +2% Adjusted completion rate: 75% ``` **Industry Entry Success:** ``` Current Job Market Analysis: FAANG company hiring: 15% (highly competitive) Good tech company: 50% (solid opportunities) Average company: 35% (backup options) Personal assessment: - Strong GPA (3.8) - Internship experience - Technical project portfolio - Good interviewing skills Probabilities validated by career services data ``` #### Outcome Value Analysis **PhD Success Path Analysis:** ``` Academic Track (40% of completers): - Postdoc years: $45K × 3 years = $135K - Assistant professor: $75K starting - Tenure track uncertainty: 40% success - Tenured salary: $120K at age 35 - Job security: High - Work satisfaction: High (research focus) Industry R&D Track (60% of completers): - Research scientist role: $140K starting at 28 - Career growth: 6% annually - Senior scientist: $200K by 35 - Job satisfaction: High (applied research) - Career flexibility: Medium ``` **Master's Degree Outcomes:** ``` Completion rate: 95% (much higher than PhD) Time investment: 2 years vs 6 years for PhD Cost: $80K vs $0 (RA/TA funding for PhD) High-paying outcomes (70% of completers): - Software engineer: $120K starting - Data scientist: $115K starting - Product manager: $110K starting - Growth trajectory: 8% annually Entry-level outcomes (30% of completers): - Junior developer: $95K starting - Growth trajectory: 6% annually ``` #### Expected Value Comparison (10-Year Horizon) **PhD Path Expected Value:** ``` Success × Academic Track: 0.75 × 0.40 × $850K = $255K Success × Industry Track: 0.75 × 0.60 × $1,200K = $540K Dropout: 0.25 × $600K = $150K Total Expected Value: $945K ``` **Master's Path Expected Value:** ``` Success × High Pay: 0.95 × 0.70 × $1,100K = $731K Success × Average Pay: 0.95 × 0.30 × $850K = $242K Dropout: 0.05 × $700K = $35K Total Expected Value: $1,008K ``` **Direct Industry Expected Value:** ``` FAANG Track: 0.15 × $1,800K = $270K Good Company: 0.50 × $1,200K = $600K Average Company: 0.35 × $900K = $315K Total Expected Value: $1,185K ``` #### Decision Analysis **Ranking by Expected Value:** 1. **Direct Industry: $1,185K** 2. Master's Degree: $1,008K 3. PhD Program: $945K **Risk Assessment:** - Industry: Low risk, immediate income - Master's: Medium risk, moderate delay - PhD: High risk, significant opportunity cost **Qualitative Factors:** ``` Research Interest Level: High (favors PhD) Financial Pressure: Medium (favors industry) Long-term Career Goals: Tech leadership (favors MS/Industry) Learning Preference: Practical application (favors MS/Industry) Risk Tolerance: Medium-Low (favors industry) ``` **Final Decision Framework:** ``` If research passion > financial optimization: PhD If balanced career goals: Master's degree If immediate financial independence needed: Industry Chosen Path: Master's degree Rationale: Balanced risk-reward, keeps options open, strong ROI ``` --- ## 🏢 Business Strategy Trees {#business-strategy} ### Example 3: Market Entry Strategy for SaaS Startup **Background:** B2B SaaS company with successful product in US market considering European expansion. **Current State:** - US Revenue: $5M ARR - Team: 40 employees - Funding: $10M Series A - Product: Project management software #### Strategic Decision Tree ``` European Market Entry 🔷 ┌─────────┬─────────┬─────────┐ Direct Entry Partnership Gradual │ │ Expansion Regulatory 🔶 Partner 🔶 │ ┌─────────┴───┐ ┌─────┴─────┐ Market Test 🔶 Smooth Complex Success Failure ┌─────┴─────┐ (60%) (40%) (70%) (30%) Strong Weak │ │ │ │ (40%) (60%) Launch Strategy 🔷 Delayed │ │ │ │ ┌─────────┴─────────┐ Entry │ │ Scale 🔷 Pivot 🔷 Aggressive Conservative │ │ │ │ │ │ │ │ │ │ Full Local Market Response 🔶 │ Alt Route Exit Entry Focus ┌─────┴─────┐ │ │ │ │ │ │ Success Fail │ │ │ │ │ Revenue Revenue (30%) (70%) │ │ │ │ │ Growth Stable │ │ │ │ │ │ │ │ │ $3M -$2M │ │ │ │ │ $8M $2M Year 1 │ │ │ │ │ │ Year 3 Year 3 │ │ │ │ │ │ $1.5M │ $1.8M $4M $0 $0 Year 1│ Year 2 Year 2 │ $2.2M Year 2 ``` #### Market Analysis & Probability Assessment **Regulatory Environment Analysis:** ``` GDPR Compliance Requirements: - Data handling modifications needed - Legal review process: 3-6 months - Implementation cost: $200K-500K Probability Assessment: Smooth regulatory process (60%): - Based on: Similar company experiences - Standard compliance path - No major data handling issues Complex regulatory process (40%): - Based on: 30% of companies face delays - Additional features required - Extended legal reviews ``` **Partnership Strategy Assessment:** ``` Potential Partners Evaluated: - Local consulting firms: 5 prospects - Technology integrators: 3 prospects - Reseller networks: 8 prospects Success Probability (70%): - Based on: Initial partner conversations - Market demand validation - Competitive partnership landscape Partner Quality Factors: + Established customer base + Technical competency + Cultural alignment - Revenue sharing requirements - Limited control over customer experience ``` **Gradual Expansion Market Testing:** ``` Test Market Strategy: - Target: UK and Germany initially - Approach: Remote sales, localized marketing - Investment: $300K for 6-month test Strong Response Probability (40%): - Based on: Market research data - Competitor analysis - Early customer interviews Success Criteria: - 50+ qualified leads per month - 15% conversion rate - $50K ARR within 6 months ``` #### Financial Modeling & Expected Values **Direct Entry - Aggressive Launch:** ``` Investment Required: - European office setup: $500K - Local team hiring: $800K - Marketing campaign: $600K - Legal/regulatory: $300K Total: $2.2M Success Case (30% probability): Year 1: $3M revenue, -$500K net (investment recovery) Year 2: $6M revenue, $2M net Year 3: $10M revenue, $4M net 3-Year NPV: $4.2M Failure Case (70% probability): Year 1: $500K revenue, -$2M net Year 2: $800K revenue, -$1.5M net Pivot/Exit: -$1M sunk costs 3-Year NPV: -$3.8M Expected Value: (0.3 × $4.2M) + (0.7 × -$3.8M) = -$1.4M ``` **Partnership Route:** ``` Investment Required: - Partner enablement: $150K - Marketing support: $200K - Legal agreements: $50K Total: $400K Success Case (70% probability): Year 1: $1.5M revenue (50% to partner), $750K net Year 2: $3M revenue (50% to partner), $1.5M net Year 3: $5M revenue (50% to partner), $2.5M net 3-Year NPV: $3.2M Failure Case (30% probability): Year 1: $200K revenue, -$300K net Alternative route pivot: $500K additional investment Recovery scenario: $1M net over 2 years 3-Year NPV: $0.2M Expected Value: (0.7 × $3.2M) + (0.3 × $0.2M) = $2.3M ``` **Gradual Expansion:** ``` Phase 1 Investment: $300K (market testing) Strong Response (40%): - Scale to full entry: Additional $1.5M investment - 3-year revenue: $8M - 3-year costs: $2.5M - 3-Year NPV: $4.8M Weak Response (60%): - Local focus strategy: Additional $200K - 3-year revenue: $2M - 3-year costs: $800K - 3-Year NPV: $1.0M Expected Value: (0.4 × $4.8M) + (0.6 × $1.0M) = $2.5M ``` #### Decision Analysis Results **Strategy Ranking by Expected Value:** 1. **Gradual Expansion: $2.5M** 2. Partnership Route: $2.3M 3. Direct Entry: -$1.4M **Risk-Adjusted Analysis:** ``` Gradual Expansion: - Highest expected value - Lowest downside risk - Learning opportunity before major commitment - Preserves optionality Partnership Route: - Second-highest expected value - Shared risk with partner - Faster market entry - Less control over customer experience Direct Entry: - Negative expected value - Highest risk and reward potential - Maximum control and learning - Requires significant confidence in market ``` #### Strategic Decision **Chosen Strategy: Gradual Expansion** **Implementation Plan:** ``` Phase 1 (Months 1-6): Market Testing - UK/Germany focus - Remote sales team - Digital marketing campaigns - Customer development interviews Decision Point: Month 6 Review - Evaluate market response - Assess competition - Review financial metrics - Decide on Phase 2 approach Phase 2 Options (Months 7-18): If Strong Response: Full market entry If Moderate Response: Partnership hybrid If Weak Response: Refined local focus ``` **Success Metrics:** ``` Phase 1 Success Criteria: - 200+ qualified leads - 30+ customers acquired - $100K+ ARR - <$60K customer acquisition cost Phase 2 Decision Triggers: - Market size validation - Competitive positioning - Regulatory clarity - Resource availability ``` --- ## 💰 Personal Financial Decisions {#financial-decisions} ### Example 4: Real Estate Investment vs. Stock Market **Background:** 35-year-old professional with $100K saved, deciding between rental property investment or stock market investing. **Personal Situation:** - Current income: $120K/year - Savings: $100K - Monthly surplus: $3K - Risk tolerance: Moderate - Investment timeline: 15 years #### Investment Decision Tree ``` Investment Strategy 🔷 ┌─────────┬─────────┬─────────┐ Real Estate Stock Market Hybrid │ │ Approach Property Search 🔶 Market Timing 🔶 │ ┌─────────┴─────────┐ ┌─────┴─────┐ │ Good Property Average Bull Bear │ (40%) (60%) Market Market │ │ │ (60%) (40%) │ Property Mgmt 🔶 │ │ │ ┌─────┴─────┐ │ │ │ Portfolio Mix 🔶 Easy Difficult│ │ │ ┌─────────┴─────────┐ (70%) (30%) │ │ │ Balanced Conservative │ │ │ │ │ (70%) (30%) │ │ Property │ │ │ │ │ Issues │ │ │ Market Market │ 🔶 │ │ │ Performance Performance │ ┌─┴─┐ │ │ │ 🔶 🔶 │ │ │ │ │ │ ┌───┴───┐ ┌───┴───┐ Minor Major │ Strong Weak │ Good Average│ Good Poor (80%)(20%) │ Growth Perf │ (60%) (40%) │ (70%)(30%) │ │ │ │ │ │ │ │ │ │ │ $280K$180K $220K$350K$80K$40K $320K $180K$240K$120K│ 15yr 15yr 15yr 15yr 15yr 15yr 15yr 15yr 15yr 15yr │ ``` #### Investment Analysis Framework **Real Estate Investment Modeling:** ``` Property Investment Scenario: Purchase Price: $400K (using $80K down payment) Mortgage: $320K at 4.5% (30-year) Monthly Payment: $1,621 Property Taxes: $400/month Insurance: $150/month Maintenance: $200/month Total Monthly Costs: $2,371 Rental Income Projections: Market Rate Research: $2,600-2,900/month Conservative Estimate: $2,700/month Net Monthly Cash Flow: $329 Property Appreciation Assumptions: Historical Data: 3.2% annually (local market) Conservative Estimate: 3% annually Optimistic Estimate: 4% annually ``` **Property Quality Probability Assessment:** ``` Good Property (40% probability): - Desirable neighborhood - Quality construction - Reliable tenant demand - Minimal maintenance issues - Expected appreciation: 4% annually Average Property (60% probability): - Decent neighborhood - Standard construction - Normal tenant turnover - Standard maintenance - Expected appreciation: 3% annually ``` **Stock Market Investment Modeling:** ``` Portfolio Allocation Options: Conservative: 60% bonds, 40% stocks Balanced: 40% bonds, 60% stocks Aggressive: 20% bonds, 80% stocks Historical Return Analysis: Conservative Portfolio: 6% average annual return Balanced Portfolio: 8% average annual return Aggressive Portfolio: 10% average annual return Market Timing Considerations: Bull Market Entry (60% probability): - First 5 years: Above-average returns - Following years: Normal returns Bear Market Entry (40% probability): - First 2 years: Below-average returns - Recovery period: Above-average returns ``` #### Expected Value Calculations (15-Year Horizon) **Real Estate Path Analysis:** ``` Good Property + Easy Management (40% × 70% = 28%): Initial Investment: $80K down payment Monthly Contributions: $329 cash flow + $1K additional Property Value Growth: $400K → $720K (4% appreciation) Mortgage Paydown: $145K principal reduction Total Value: $720K property + $290K cash savings = $1,010K Net Worth: $1,010K - $175K remaining mortgage = $835K Good Property + Difficult Management (40% × 30% = 12%): Additional Costs: $200/month management, $2K/year repairs Reduced Cash Flow: $129/month + $1K additional Total Value: $720K property + $210K cash savings = $930K Net Worth: $930K - $175K remaining mortgage = $755K Average Property + Easy Management (60% × 70% = 42%): Property Value Growth: $400K → $635K (3% appreciation) Monthly Cash Flow: $329 + $1K additional Total Value: $635K property + $290K cash = $925K Net Worth: $925K - $175K remaining mortgage = $750K Average Property + Difficult Management (60% × 30% = 18%): Property Value Growth: $400K → $635K Reduced Cash Flow: $129/month + $1K additional Total Value: $635K property + $210K cash = $845K Net Worth: $845K - $175K remaining mortgage = $670K Weighted Expected Value: (0.28 × $835K) + (0.12 × $755K) + (0.42 × $750K) + (0.18 × $670K) = $766K ``` **Stock Market Path Analysis:** ``` Bull Market + Balanced Portfolio (60% × 70% = 42%): Initial Investment: $100K Monthly Contributions: $3K Portfolio Growth: 9% average annual return 15-Year Value: $1,240K Bull Market + Conservative Portfolio (60% × 30% = 18%): Portfolio Growth: 7% average annual return 15-Year Value: $985K Bear Market + Balanced Portfolio (40% × 60% = 24%): Portfolio Growth: 7% average annual return 15-Year Value: $985K Bear Market + Conservative Portfolio (40% × 40% = 16%): Portfolio Growth: 5% average annual return 15-Year Value: $795K Weighted Expected Value: (0.42 × $1,240K) + (0.18 × $985K) + (0.24 × $985K) + (0.16 × $795K) = $1,062K ``` **Hybrid Approach Analysis:** ``` Split Strategy: 50% Real Estate, 50% Stock Market Real Estate: $40K down payment on $200K property Stock Market: $60K initial + $1.5K monthly Expected Value Calculation: Real Estate Component: $383K (50% of real estate expected value) Stock Market Component: $531K (scaled portfolio value) Total Expected Value: $914K Risk Profile: Lower than pure real estate, higher than pure stock market Diversification Benefit: Reduced correlation between asset classes ``` #### Risk Analysis & Sensitivity Testing **Risk Factors Assessment:** ``` Real Estate Risks: - Vacancy periods: 5-10% income reduction - Major repairs: $5K-15K unexpected costs - Interest rate changes: Affect property values - Local market downturns: 10-30% value decline - Illiquidity: Difficult to exit quickly Stock Market Risks: - Market volatility: 20-40% swings possible - Sequence of returns risk: Poor early returns hurt outcome - Inflation impact: Real return reduction - Emotional decision-making: Buy high, sell low tendency - Economic recession: Extended low returns Hybrid Approach Risks: - Complexity of managing two asset classes - Potentially sub-optimal allocation - Higher transaction costs - Time management challenges ``` **Sensitivity Analysis:** ``` Scenario 1: Real Estate Market Decline If property appreciation drops to 1% annually: Real Estate Expected Value: $612K (vs $766K base case) Scenario 2: Stock Market Extended Bear Market If market returns 5% annually for 15 years: Stock Market Expected Value: $795K (vs $1,062K base case) Scenario 3: Interest Rate Increases If mortgage rates rise to 6%: Real Estate Cash Flow: -$150/month Property Investment Attractiveness: Significantly reduced Scenario 4: High Inflation Environment Real Estate: Generally benefits from inflation hedge Stock Market: Mixed impact depending on sector allocation ``` #### Decision Analysis & Recommendations **Expected Value Ranking:** 1. **Stock Market Investment: $1,062K** 2. Hybrid Approach: $914K 3. Real Estate Investment: $766K **Risk-Adjusted Considerations:** ``` Stock Market Advantages: + Highest expected value + Superior liquidity + Lower time commitment + Professional management (index funds) + Easy diversification Real Estate Advantages: + Tangible asset + Inflation hedge + Tax benefits + Leverage utilization + Personal control Hybrid Approach Advantages: + Diversification benefits + Balanced risk exposure + Learning opportunity + Flexibility to adjust allocation ``` **Personal Situation Analysis:** ``` Time Availability: Limited (favors stock market) Investment Knowledge: Moderate (both feasible) Risk Tolerance: Moderate (supports diversified approach) Income Stability: High (supports either strategy) Geographic Flexibility: May relocate (favors stock market) Tax Situation: W-2 employee (real estate tax benefits valuable) ``` **Final Recommendation: Stock Market with Real Estate Option** **Implementation Strategy:** ``` Year 1-2: Stock Market Focus - Invest full $100K in diversified portfolio - Continue $3K monthly contributions - Learn about real estate investing - Monitor local real estate market Years 3-5: Evaluate Real Estate Entry - Assess financial position - Review market conditions - Consider hybrid approach if attractive opportunities arise Decision Criteria for Real Estate Addition: - Net worth exceeds $300K - Strong local market fundamentals - Identified high-quality property - Comfortable with landlord responsibilities ``` --- ## 🏥 Medical & Health Choices {#medical-decisions} ### Example 5: Treatment Options for Chronic Condition **Background:** 45-year-old patient diagnosed with moderate heart disease, choosing between treatment approaches. **Medical Context:** - Condition: Coronary artery disease (70% blockage in one vessel) - Symptoms: Mild chest pain during exercise - Overall health: Good otherwise - Family history: Heart disease - Lifestyle: Sedentary, high-stress job #### Treatment Decision Tree ``` Treatment Choice 🔷 ┌─────────┬─────────┬─────────┐ Medication Angioplasty Surgery Only (Stent) (Bypass) │ │ │ Medication 🔶 Procedure 🔶 Surgery 🔶 Response ┌─────┴─────┐ ┌─────┴─────┐ ┌─────┴─────┐│Success Comp│Success Comp│ Good Poor │ (92%) (8%) │ (95%) (5%) │ (70%)(30%) │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ Lifestyle 🔷 │ │ │ │ │ │ │ ┌─────┴─────┐ │ │ │ │ │ │ │ Change NoChange│ │ Complications│ │ Complications (60%) (40%) │ │ Management🔶 │ │ Management🔶 │ │ │ │ ┌─────┴─────┐│ │ ┌─────┴─────┐ Long Normal │ Normal Major │ Normal Major │ Term Mgmt │ Recovery Issues │ Recovery Issues │ Better │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ │ Quality Life │ Quality Reduced│ Quality Significant 85% 75% │ 90% 65% │ 95% Health │ 5yr 5yr │ 5yr 5yr │ 5yr Issues │ surv surv │ surv surv │ surv 80% │ 95% 85% │ 98% 90% │ 99% 5yr │ 10yr 10yr │ 10yr 10yr │ 10yr surv │ 90% 80% │ 95% 85% │ 97% 90% │ │ │ 10yr │ │ │ surv │ │ │ 85% │ ``` #### Medical Evidence & Probability Assessment **Medication Response Probabilities:** ``` Clinical Trial Data for Similar Patients: Good Response (70%): - Symptoms improve significantly - Exercise tolerance increases - Progression halted or slowed Poor Response (30%): - Continued symptoms - Limited exercise improvement - Disease progression likely Lifestyle Change Success (if medication works): Patient Profile Assessment: + Motivated by diagnosis + Strong family support - High-stress job - Previous failed attempts Realistic Success Rate: 60% ``` **Angioplasty (Stent) Outcomes:** ``` Procedure Success Rate: 92% Based on: Hospital data for similar blockages Factors: Single vessel, good overall health, experienced team Complication Rate: 8% - Minor complications: 6% (bleeding, temporary issues) - Major complications: 2% (heart attack, stroke, death) Long-term Outcomes (if successful): - Immediate symptom relief: 85% - 5-year patency: 75% (stent remains open) - Need for re-intervention: 20% within 5 years ``` **Bypass Surgery Outcomes:** ``` Surgery Success Rate: 95% Based on: National database for single vessel bypass Risk factors: Age 45 (low risk), single vessel (lower complexity) Complication Rate: 5% - Minor complications: 3% (infection, arrhythmia) - Major complications: 2% (stroke, death, cognitive changes) Long-term Outcomes (if successful): - Complete symptom relief: 95% - 10-year graft patency: 85% - Durability: Most patients avoid re-intervention ``` #### Quality of Life & Survival Analysis **Medication Management Path:** ``` Good Response + Lifestyle Change (70% × 60% = 42%): - Quality of Life: 85% of baseline - 5-year survival: 95% - 10-year survival: 90% - Exercise capacity: Significantly improved - Medication side effects: Minimal - Annual monitoring: Required Good Response + No Lifestyle Change (70% × 40% = 28%): - Quality of Life: 75% of baseline - 5-year survival: 85% - 10-year survival: 80% - Exercise capacity: Moderately improved - Disease progression: Likely over time Poor Response (30%): - Quality of Life: 60% of baseline - Symptoms persist or worsen - Future intervention required: 80% within 2 years - Psychological impact: Moderate anxiety/depression ``` **Angioplasty Path:** ``` Successful Procedure (92%): - Immediate recovery: 3-5 days - Quality of Life: 90% of baseline within 1 month - Return to work: 1-2 weeks - Exercise capacity: Fully restored - Long-term outcomes depend on lifestyle changes Complications (8%): - Minor complications: Extended hospital stay, full recovery - Major complications: Significant impact on outcomes - Quality of Life: 65% of baseline - Recovery time: 2-6 months ``` **Surgery Path:** ``` Successful Surgery (95%): - Recovery period: 6-8 weeks - Quality of Life: 95% of baseline after recovery - Return to work: 2-3 months - Exercise capacity: Better than baseline possible - Durability: Most effective long-term solution Complications (5%): - Recovery complications: Extended rehabilitation - Cognitive changes: 2% risk of persistent issues - Quality of Life: Variable (65-85% of baseline) - Long-term survival may be affected ``` #### Expected Value Analysis (Quality-Adjusted Life Years) **Medication Strategy Expected QALY:** ``` Good Response Scenarios: - With lifestyle change: 42% × 22.5 QALY = 9.45 - Without lifestyle change: 28% × 17.5 QALY = 4.90 Poor Response Scenario: - Future intervention needed: 30% × 15.0 QALY = 4.50 Total Expected QALY: 18.85 ``` **Angioplasty Strategy Expected QALY:** ``` Successful Procedure: - 92% × 24.0 QALY = 22.08 Complications: - 8% × 16.5 QALY = 1.32 Total Expected QALY: 23.40 ``` **Surgery Strategy Expected QALY:** ``` Successful Surgery: - 95% × 25.5 QALY = 24.23 Complications: - 5% × 18.0 QALY = 0.90 Total Expected QALY: 25.13 ``` #### Risk-Benefit Analysis **Personal Risk Factors:** ``` Age Factor: 45 years old + Excellent healing capacity + Long life expectancy + Career/family obligations Health Status: Generally excellent + No diabetes, kidney disease, or other conditions + Good surgical candidate + High likelihood of procedure success Lifestyle Factors: + Motivated to change after diagnosis - High-stress job (difficult to modify) - Previous attempts at lifestyle change failed ``` **Treatment Risk Profiles:** ``` Medication (Lowest Risk): - No procedural risks - Minimal side effects - Reversible approach - May delay but not solve problem Angioplasty (Moderate Risk): - Low procedural risk - Potential for re-intervention - Faster recovery than surgery - Good intermediate solution Surgery (Highest Initial Risk): - Highest procedural risk - Most durable solution - Longest recovery time - Best long-term outcomes if successful ``` #### Decision Analysis & Recommendation **QALY Rankings:** 1. **Bypass Surgery: 25.13 QALY** 2. Angioplasty: 23.40 QALY 3. Medication Only: 18.85 QALY **Individual Patient Factors:** ``` Professional Considerations: - Cannot afford 2-3 month recovery (surgery) - 1-2 week recovery acceptable (angioplasty) - Continued symptoms affect work performance Family Considerations: - Young children need active parent - Spouse concerned about procedural risks - Family history creates anxiety about progression Personal Values: - Prefers definitive solutions - Moderate risk tolerance - Values quality of life over longevity - Wants to return to exercise/activities ``` **Shared Decision-Making Process:** ``` Step 1: Review all evidence and probabilities Step 2: Discuss patient values and priorities Step 3: Consider family input and concerns Step 4: Evaluate lifestyle modification commitment Step 5: Plan for follow-up and monitoring Patient Priority Ranking: 1. Return to normal activities quickly 2. Minimize long-term uncertainty 3. Avoid major complications 4. Family peace of mind ``` **Final Recommendation: Angioplasty (Stent)** **Rationale:** - Balances effectiveness with acceptable risk - Faster recovery fits lifestyle needs - High success rate with manageable complications - Preserves surgery option if needed later - Good compromise between patient and family preferences **Implementation Plan:** ``` Pre-procedure: - Cardiac catheterization to confirm anatomy - Pre-operative optimization - Family education and support Post-procedure: - Dual antiplatelet therapy - Cardiac rehabilitation program - Lifestyle modification support - Regular follow-up monitoring Long-term Plan: - Annual imaging to monitor stent - Aggressive risk factor modification - Re-evaluation if symptoms recur - Surgery consideration if stent fails ``` ## 🎯 Key Patterns Across Examples ### Common Success Factors 1. **Systematic Probability Assessment** - Used multiple information sources - Validated estimates with reference data - Included uncertainty and confidence levels 2. **Comprehensive Outcome Modeling** - Quantified both financial and non-financial impacts - Considered multiple time horizons - Included risk-adjusted calculations 3. **Sensitivity Analysis** - Tested key assumptions - Identified decision breakpoints - Planned for scenario variations 4. **Implementation Planning** - Defined clear success metrics - Established review points - Built in flexibility for adjustments ### Decision Tree Best Practices Observed 1. **Progressive Complexity** - Started simple, added detail where needed - Focused on major decision points - Avoided over-engineering 2. **Probability Calibration** - Used reference class forecasting - Sought expert opinions - Documented estimation rationale 3. **Value Integration** - Combined quantitative and qualitative factors - Used consistent measurement frameworks - Included stakeholder perspectives 4. **Decision Support Not Replacement** - Used analysis to inform, not replace judgment - Considered factors beyond the tree - Maintained focus on implementation ## 🔗 Related Resources ### Method Guides - [[node-types|Node Types & Structure]] - [[probability-basics|Probability Fundamentals]] ### Other Methods - [[01-decision-methods/04-markov-chain/index|Markov Chains]] - For state-based decisions - [[Decision Helper/01-decision-methods/05-bayesian-analysis/index|Bayesian Analysis]] - For updating beliefs ### Applications - [[business-choices|More Business Examples]] - [[02-real-world-examples/career-decisions|Career Decision Cases]] - [[complex-decisions|Advanced Decision Techniques]] --- **Next Method:** [[01-decision-methods/04-markov-chain/index|Explore Markov Chains →]]