# Vida's Knowledge Frontier **Last updated:** 2026-03-16 (first self-audit) 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. --- ## 1. Behavioral Health Infrastructure Mechanisms **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%. **What's missing:** - Community health worker program outcomes (ROI, scalability, retention) - Social prescribing mechanisms and evidence (UK Link Workers, international models) - Digital therapeutics for behavior change (post-PDT market failure — what survived?) - Behavioral economics of health (commitment devices, default effects, incentive design) - Food-as-medicine programs (Geisinger Fresh Food Farmacy, produce prescription ROI) **Adjacent claims:** - [[medical care explains only 10-20 percent of health outcomes...]] - [[SDOH interventions show strong ROI but adoption stalls...]] - [[social isolation costs Medicare 7 billion annually...]] - [[modernization dismantles family and community structures...]] **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. --- ## 2. International and Comparative Health Systems **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. **What's missing:** - Singapore's 3M system (Medisave/Medishield/Medifund) — consumer-directed with catastrophic coverage - Costa Rica's EBAIS primary care model — universal coverage at 8% of US per-capita spend - Japan's Long-Term Care Insurance — aging population, community-based care at scale - NHS England — what underfunding + wait times reveal about single-payer failure modes - Kerala's community health model — high outcomes at low GDP **Adjacent claims:** - [[the healthcare attractor state is a prevention-first system...]] - [[healthcare is a complex adaptive system requiring simple enabling rules...]] - [[four competing payer-provider models are converging toward value-based care...]] **Evidence needed:** Comparative health system analyses. WHO/Commonwealth Fund cross-national data. Case studies of systems that achieved prevention-first economics. --- ## 3. GLP-1 Second-Order Economics **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. **What's missing:** - Long-term adherence data at population scale (current trials are 2-4 years) - Insurance coverage dynamics (employer vs Medicare vs cash-pay trajectories) - Impact on adjacent markets (bariatric surgery demand, metabolic syndrome treatment) - Manufacturing bottleneck economics (Novo/Lilly duopoly, biosimilar timeline) - Behavioral rebound after discontinuation (weight regain rates, metabolic reset) **Adjacent claims:** - [[GLP-1 receptor agonists are the largest therapeutic category launch...]] - [[the healthcare cost curve bends up through 2035...]] - [[consumer willingness to pay out of pocket for AI-enhanced care...]] **Evidence needed:** Real-world adherence studies (not trial populations). Actuarial analyses of GLP-1 impact on total cost of care. Manufacturing capacity forecasts. --- ## 4. Clinical AI Real-World Safety Data **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. **What's missing:** - Deployment accuracy vs benchmark accuracy (how much does performance drop in real clinical settings?) - Alert fatigue rates in AI-augmented clinical workflows - Liability incidents and near-misses from clinical AI deployments - Autonomous diagnosis failure modes (systematic biases, demographic performance gaps) - Clinician de-skilling longitudinal data (is the human-in-the-loop degradation measurable over years?) **Adjacent claims:** - [[human-in-the-loop clinical AI degrades to worse-than-AI-alone...]] - [[medical LLM benchmark performance does not translate to clinical impact...]] - [[AI diagnostic triage achieves 97 percent sensitivity...]] - [[healthcare AI regulation needs blank-sheet redesign...]] **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. --- ## 5. Space Health (Cross-Domain Bridge to Astra) **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. **What's missing:** - Radiation biology and cancer risk in long-duration spaceflight - Bone density and muscle atrophy countermeasures (pharmaceutical + exercise protocols) - Psychological health in isolation and confinement (Antarctic, submarine, ISS data) - Closed-loop life support as a model for self-sustaining health systems - Telemedicine in extreme environments (latency-tolerant protocols, autonomous diagnosis) **Adjacent claims:** - [[social isolation costs Medicare 7 billion annually...]] - [[the physician role shifts from information processor to relationship manager...]] - [[continuous health monitoring is converging on a multi-layer sensor stack...]] **Evidence needed:** NASA Human Research Program publications. ESA isolation studies (SIRIUS, Mars-500). Telemedicine deployment data from remote/extreme environments. --- ## 6. Health Narratives and Meaning (Cross-Domain Bridge to Clay) **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. **What's missing:** - Placebo and nocebo mechanisms — what the placebo effect reveals about narrative-driven physiology - Narrative identity in chronic illness — how patients' stories about their condition affect outcomes - Meaning-making as health intervention — Viktor Frankl to modern logotherapy evidence - Community and ritual as health infrastructure — religious attendance, group membership, and mortality - Deaths of despair as narrative failure — the connection between meaning-loss and self-destructive behavior **Adjacent claims:** - [[Americas declining life expectancy is driven by deaths of despair...]] - [[modernization dismantles family and community structures...]] - [[social isolation costs Medicare 7 billion annually...]] **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. --- *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.*