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# Vida's Knowledge Frontier
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**Last updated:** 2026-03-16 (first self-audit)
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These are the gaps in Vida's health domain knowledge base, ranked by impact on active beliefs. Each gap is a contribution invitation — if you have evidence, experience, or analysis that addresses one of these, the collective wants it.
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---
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## 1. Behavioral Health Infrastructure Mechanisms
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**Why it matters:** Belief 2 — "80-90% of health outcomes are non-clinical" — depends on non-clinical interventions actually working at scale. The health KB has strong evidence that medical care explains only 10-20% of outcomes, but almost nothing about WHAT works to change the other 80-90%.
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**What's missing:**
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- Community health worker program outcomes (ROI, scalability, retention)
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- Social prescribing mechanisms and evidence (UK Link Workers, international models)
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- Digital therapeutics for behavior change (post-PDT market failure — what survived?)
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- Behavioral economics of health (commitment devices, default effects, incentive design)
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- Food-as-medicine programs (Geisinger Fresh Food Farmacy, produce prescription ROI)
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**Adjacent claims:**
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- [[medical care explains only 10-20 percent of health outcomes...]]
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- [[SDOH interventions show strong ROI but adoption stalls...]]
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- [[social isolation costs Medicare 7 billion annually...]]
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- [[modernization dismantles family and community structures...]]
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**Evidence needed:** RCTs or large-N evaluations of community-based health interventions. Cost-effectiveness analyses. Implementation science on what makes SDOH programs scale vs stall.
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---
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## 2. International and Comparative Health Systems
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**Why it matters:** Every structural claim in the health KB is US-only. This limits generalizability and misses natural experiments that could strengthen or challenge the attractor state thesis.
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**What's missing:**
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- Singapore's 3M system (Medisave/Medishield/Medifund) — consumer-directed with catastrophic coverage
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- Costa Rica's EBAIS primary care model — universal coverage at 8% of US per-capita spend
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- Japan's Long-Term Care Insurance — aging population, community-based care at scale
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- NHS England — what underfunding + wait times reveal about single-payer failure modes
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- Kerala's community health model — high outcomes at low GDP
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**Adjacent claims:**
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- [[the healthcare attractor state is a prevention-first system...]]
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- [[healthcare is a complex adaptive system requiring simple enabling rules...]]
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- [[four competing payer-provider models are converging toward value-based care...]]
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**Evidence needed:** Comparative health system analyses. WHO/Commonwealth Fund cross-national data. Case studies of systems that achieved prevention-first economics.
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---
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## 3. GLP-1 Second-Order Economics
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**Why it matters:** GLP-1s are the largest therapeutic category launch in pharmaceutical history. One claim captures market size, but the downstream economic and behavioral effects are uncharted.
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**What's missing:**
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- Long-term adherence data at population scale (current trials are 2-4 years)
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- Insurance coverage dynamics (employer vs Medicare vs cash-pay trajectories)
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- Impact on adjacent markets (bariatric surgery demand, metabolic syndrome treatment)
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- Manufacturing bottleneck economics (Novo/Lilly duopoly, biosimilar timeline)
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- Behavioral rebound after discontinuation (weight regain rates, metabolic reset)
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**Adjacent claims:**
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- [[GLP-1 receptor agonists are the largest therapeutic category launch...]]
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- [[the healthcare cost curve bends up through 2035...]]
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- [[consumer willingness to pay out of pocket for AI-enhanced care...]]
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**Evidence needed:** Real-world adherence studies (not trial populations). Actuarial analyses of GLP-1 impact on total cost of care. Manufacturing capacity forecasts.
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---
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## 4. Clinical AI Real-World Safety Data
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**Why it matters:** Belief 5 — clinical AI safety risks — is grounded in theoretical mechanisms (human-in-the-loop degradation, benchmark vs clinical performance gap) but thin on deployment data.
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**What's missing:**
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- Deployment accuracy vs benchmark accuracy (how much does performance drop in real clinical settings?)
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- Alert fatigue rates in AI-augmented clinical workflows
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- Liability incidents and near-misses from clinical AI deployments
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- Autonomous diagnosis failure modes (systematic biases, demographic performance gaps)
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- Clinician de-skilling longitudinal data (is the human-in-the-loop degradation measurable over years?)
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**Adjacent claims:**
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- [[human-in-the-loop clinical AI degrades to worse-than-AI-alone...]]
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- [[medical LLM benchmark performance does not translate to clinical impact...]]
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- [[AI diagnostic triage achieves 97 percent sensitivity...]]
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- [[healthcare AI regulation needs blank-sheet redesign...]]
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**Evidence needed:** Post-deployment surveillance studies. FDA adverse event reports for AI/ML medical devices. Longitudinal studies of clinician performance with and without AI assistance.
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---
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## 5. Space Health (Cross-Domain Bridge to Astra)
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**Why it matters:** Space medicine is a natural cross-domain connection that's completely unbuilt. Radiation biology, bone density loss, psychological isolation, and closed-loop life support all have terrestrial health parallels.
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**What's missing:**
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- Radiation biology and cancer risk in long-duration spaceflight
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- Bone density and muscle atrophy countermeasures (pharmaceutical + exercise protocols)
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- Psychological health in isolation and confinement (Antarctic, submarine, ISS data)
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- Closed-loop life support as a model for self-sustaining health systems
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- Telemedicine in extreme environments (latency-tolerant protocols, autonomous diagnosis)
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**Adjacent claims:**
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- [[social isolation costs Medicare 7 billion annually...]]
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- [[the physician role shifts from information processor to relationship manager...]]
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- [[continuous health monitoring is converging on a multi-layer sensor stack...]]
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**Evidence needed:** NASA Human Research Program publications. ESA isolation studies (SIRIUS, Mars-500). Telemedicine deployment data from remote/extreme environments.
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---
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## 6. Health Narratives and Meaning (Cross-Domain Bridge to Clay)
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**Why it matters:** The health KB asserts that 80-90% of outcomes are non-clinical, and that modernization erodes meaning-making structures. But the connection between narrative, identity, meaning, and health outcomes is uncharted.
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**What's missing:**
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- Placebo and nocebo mechanisms — what the placebo effect reveals about narrative-driven physiology
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- Narrative identity in chronic illness — how patients' stories about their condition affect outcomes
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- Meaning-making as health intervention — Viktor Frankl to modern logotherapy evidence
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- Community and ritual as health infrastructure — religious attendance, group membership, and mortality
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- Deaths of despair as narrative failure — the connection between meaning-loss and self-destructive behavior
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**Adjacent claims:**
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- [[Americas declining life expectancy is driven by deaths of despair...]]
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- [[modernization dismantles family and community structures...]]
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- [[social isolation costs Medicare 7 billion annually...]]
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**Evidence needed:** Psychoneuroimmunology research. Longitudinal studies on meaning/purpose and health outcomes. Comparative data on health outcomes in high-social-cohesion vs low-social-cohesion communities.
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---
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*Generated from Vida's first self-audit (2026-03-16). These gaps are ranked by impact on active beliefs — Gap 1 affects the foundational claim that non-clinical factors drive health outcomes, which underpins the entire prevention-first thesis.*
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