Living Reviews: The Future of Evidence

Systematic reviews have a fundamental problem: they start becoming outdated the moment they're published. EvidAI's Living Review System addresses this challenge in a way no other platform can match.

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The Evidence Decay Problem

Research has shown that systematic reviews become outdated at an alarming rate:

Source: This pattern has been documented in multiple studies examining systematic review currency across medical specialties.

The Real-World Impact

• Clinical Guidelines: Physicians may follow recommendations based on incomplete evidence
• Drug Approvals: Regulatory decisions made without the latest safety and efficacy data
• Coverage Decisions: Payers basing access on outdated assessments
• Research Direction: Scientists unaware of recently answered questions

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How Others Handle Updates

Traditional Manual Updates

Current Platform Capabilities

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EvidAI's Living Review System

Fully Automated End-to-End

           EvidAI LIVING REVIEW WORKFLOW
           
    ┌──────────────────────────────────────────────────────┐
    │           AUTOMATED MONITORING                        │
    │                                                       │
    │  11 Databases Searched:                              │
    │  • PubMed/MEDLINE (Daily)                            │
    │  • Embase (Weekly)                                   │
    │  • Cochrane CENTRAL (Weekly)                         │
    │  • Web of Science (Weekly)                           │
    │  • ClinicalTrials.gov (Weekly)                       │
    │  • Preprint servers (Daily)                          │
    │  • + 5 more databases                                │
    │                                                       │
    └────────────────────────┬─────────────────────────────┘
                             │
                             ▼
    ┌──────────────────────────────────────────────────────┐
    │           AI SCREENING                                │
    │                                                       │
    │  New papers automatically screened using:             │
    │  • Same criteria as original review                   │
    │  • 4-model consensus system                          │
    │  • Confidence-based routing                          │
    │                                                       │
    └────────────────────────┬─────────────────────────────┘
                             │
                             ▼
    ┌──────────────────────────────────────────────────────┐
    │           IMPACT ASSESSMENT                           │
    │                                                       │
    │  For each relevant study, AI assesses:               │
    │  • Would this change effect direction?               │
    │  • Would this change statistical significance?       │
    │  • How much would confidence intervals change?       │
    │                                                       │
    │  Classification:                                      │
    │  • LOW: Log for quarterly review                     │
    │  • MODERATE: Schedule monthly update                 │
    │  • HIGH: Trigger immediate update                    │
    │                                                       │
    └────────────────────────┬─────────────────────────────┘
                             │
                             ▼
    ┌──────────────────────────────────────────────────────┐
    │           AUTOMATED UPDATE                            │
    │                                                       │
    │  When triggered:                                      │
    │  • Extract data from new studies                     │
    │  • Recalculate meta-analysis                         │
    │  • Update GRADE certainty                            │
    │  • Regenerate forest plots                           │
    │  • Update version (v1.0 → v1.1 or v2.0)             │
    │  • Notify all stakeholders                           │
    │                                                       │
    └──────────────────────────────────────────────────────┘

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Capability Comparison

Monitoring & Detection

Impact Assessment

Update Execution

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Real-World Example

Living Review: SGLT2 Inhibitors in Heart Failure

MONITORING LOG: 12-Week Period
═══════════════════════════════════════════════════════════════

Initial State:
├── Included Studies: 8
├── Pooled HR: 0.73 [0.67-0.80]
├── Conclusion: "Significant reduction in HF hospitalization"
└── Version: v2.0.0

Weeks 1-4:
├── Searches executed: 44 (4 weeks × 11 databases)
├── New records found: 847
├── Relevant after AI screening: 3
├── Impact assessment: LOW (post-hoc analyses)
└── Action: Logged for quarterly review

Week 5:
├── New relevant RCT detected: SUSTAIN-CHINA (n=868)
├── AI-extracted effect: HR 0.68 [0.54-0.86]
├── Impact assessment: MODERATE (would narrow CI by 8%)
└── Action: Scheduled for monthly update

Week 8 (Monthly Update):
├── Studies: 8 → 9
├── Pooled HR: 0.73 [0.67-0.80] → 0.72 [0.67-0.78]
├── Conclusion: Unchanged (more precise)
├── Version: v2.0.0 → v2.1.0
└── 12 stakeholders notified

Week 12: ⚠️ MAJOR UPDATE TRIGGERED
├── New study: SOUL-CV (n=9,642, CV outcomes trial)
├── Impact assessment: HIGH
│   └── Reason: CV mortality now reaches significance
├── Version: v2.1.0 → v3.0.0 (in progress)
└── All stakeholders + admins notified

═══════════════════════════════════════════════════════════════

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Economic Comparison

3-Year Cost Analysis

Value Beyond Cost

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Why This Matters

For Pharmaceutical Companies

A drug generating $50M/month cannot afford outdated evidence in FDA submissions. A 6-month delay waiting for a traditional update represents $300M in potential revenue impact. Living reviews eliminate this risk.

For Healthcare Organizations

Clinical guidelines based on outdated evidence can lead to suboptimal patient care. Living reviews ensure your guidance reflects the best available evidence.

For Research Funders

Understanding the current evidence landscape requires current evidence. Living reviews prevent duplicate research investments.

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Summary

EvidAI's Living Review System isn't just an improvement—it's a paradigm shift from static snapshots to dynamic, continuously-updated evidence resources.