---
status: seed
type: musing
stage: developing
created: 2026-03-16
last_updated: 2026-03-16
tags: [glp-1, adherence, value-based-care, capitation, ai-healthcare, clinical-ai, epic, abridge, openevidence, research-session]
---

# Research Session: GLP-1 Adherence Interventions and AI-Healthcare Adoption

## Research Question

**Can GLP-1 adherence interventions (care coordination, lifestyle integration, CGM monitoring, digital therapeutics) close the adherence gap that makes capitated economics work — or does solving the math require price compression to ~$50/month before VBC GLP-1 coverage becomes structurally viable?**

Secondary question: **What does the actual adoption curve of ambient AI scribes tell us about whether the "scribe as beachhead" theory for clinical AI is materializing — and does Epic's entry change that story?**

## Why This Question

**Priority justification:** The March 12 session ended with the most important unresolved tension in the entire GLP-1 analysis: MA plans are restricting access despite theoretical incentives to cover GLP-1s. The BALANCE model (May 2026 Medicaid launch) is the first formal policy test of whether medication + lifestyle can solve the adherence paradox. Three months out from launch is exactly when preparatory data should be available.

The secondary question comes from the research directive: AI-healthcare startups are a priority. The KB has a claim that "AI scribes reached 92% provider adoption in under 3 years" — but this was written without interrogating what adoption actually means. Is adoption = accounts created, or active daily use? Does the burnout reduction materialize? Is Abridge pulling ahead?

**Connections to existing KB:**
- Active thread: GLP-1 cost-effectiveness under capitation requires solving the adherence paradox (March 12 claim candidate)
- Active thread: MA plans' near-universal prior auth demonstrates capitation alone ≠ prevention incentive (March 12 claim candidate)
- Existing KB claim: "ambient AI documentation reduces physician documentation burden by 73 percent but the relationship between automation and burnout is more complex than time savings alone" — needs updating with 2025-2026 evidence

**What would change my mind:**
- If BALANCE model design includes an adherence monitoring component using CGM/wearables, that strengthens the atoms-to-bits thesis (physical monitoring solves the behavioral gap)
- If purpose-built MA plans (Devoted, Oak Street) are covering GLP-1s while generic MA plans restrict, that strongly validates the "VBC form vs. substance" distinction
- If AI scribe adoption is plateauing at 30-40% ACTIVE daily use despite 90%+ account creation, the "beachhead" theory needs qualification
- If AI scribe companies are monetizing through workflow data → clinical intelligence (not just documentation), the atoms-to-bits thesis gets extended

## Direction Selection Rationale

Following active inference principles: these questions have the highest learning value because they CHALLENGE the attractor state thesis (GLP-1 question) and TEST a KB claim empirically (AI scribe question). Both are areas where I could be wrong in ways that matter.

GLP-1 adherence is the March 12 active thread with highest priority. AI scribe adoption is in the research directive and has a KB claim that may be stale.

---

## What I Found

### Track 1: GLP-1 Adherence — The Digital Combination Works (Observationally)

**The headline finding:** Multiple convergent 2025 studies show digital behavioral support substantially improves GLP-1 outcomes AND may reduce drug requirements:

1. **JMIR retrospective cohort (Voy platform, UK):** Engaged patients lost 11.53% vs. 8% body weight at 5 months. Digital components: live video coaching, in-app support, real-time weight monitoring, adherence tracking.

2. **Danish digital + treat-to-target study:** 16.7% weight loss at 64 weeks — matching clinical trial outcomes — while using HALF the typical semaglutide dose. This is the most economically significant finding: same outcomes, 50% drug cost.

3. **WHO December 2025 guidelines:** Formal conditional recommendation for "GLP-1 therapies combined with intensive behavioral therapy" — not medication alone. First-ever WHO guideline on GLP-1 explicitly requires behavioral combination.

4. **Critical RCT finding on weight regain after discontinuation (the 64.8% scenario):**
   - GLP-1 alone: +8.7 kg regain — NO BETTER than placebo (+7.6 kg)
   - Exercise-containing arm: +5.4 kg
   - Combination (GLP-1 + exercise): only +3.5 kg

**The core insight this changes:** The existing March 12 framing assumed the adherence paradox is about drug continuity — keep patients on the drug and they capture savings. The new evidence suggests the real issue is behavioral change that OUTLASTS pharmacotherapy. GLP-1 alone doesn't produce durable change; the combination does. The drug is a catalyst, not the treatment itself.

CLAIM CANDIDATE: "GLP-1 medications function as behavioral change catalysts rather than standalone treatments — combination with structured behavioral support achieves equivalent outcomes at half the drug cost AND reduces post-discontinuation weight regain by 60%, making medication-plus-behavioral the economically rational standard of care"

### Track 2: BALANCE Model Design — Smarter Than Expected

The design is more sophisticated than the original March 12 analysis captured:

1. **Two-track payment mechanism:** CMS offering BOTH (a) higher capitated rates for obesity AND (b) reinsurance stop-loss. This directly addresses the two structural barriers identified in March 12: short-term cost pressure and tail risk from high-cost adherents.

2. **Manufacturer-funded lifestyle support:** The behavioral intervention component is MANUFACTURER FUNDED at no cost to payers. CMS is requiring drug companies to fund the behavioral support that makes their drugs cost-effective — shifting implementation costs while requiring evidence-based design.

3. **Targeted eligibility:** Not universal coverage — requires BMI threshold + evidence of metabolic dysfunction (heart failure, uncontrolled hypertension, pre-diabetes). Consistent with the sarcopenia risk argument: the populations most at cardiac risk from obesity get the drug; the populations where GLP-1 muscle loss is most dangerous (healthy elderly) are filtered.

4. **Timeline:** BALANCE Medicaid May 2026, Medicare Bridge July 2026, full Medicare Part D January 2027.

The March 12 question was: "does capitation create prevention incentives?" The BALANCE answer: capitation alone doesn't, but capitation + payment adjustment + reinsurance + manufacturer-funded lifestyle + targeted access might.

CLAIM CANDIDATE: "CMS BALANCE model's dual payment mechanism — capitation rate adjustment plus reinsurance stop-loss — directly addresses the structural barriers (short-term cost, tail risk) that cause MA plans to restrict GLP-1s despite theoretical prevention incentives"

### Track 3: AI Scribe Market — Epic's Entry Changes the Thesis

**Epic AI Charting launched February 4, 2026** — a native ambient documentation tool that queues orders AND creates notes, accessing full patient history from the EHR. Key facts:
- 42% of acute hospital EHR market, 55% of US hospital beds
- "Good enough" for most documentation use cases at fraction of standalone scribe cost
- Native integration is structurally superior for most use cases

**Abridge's position (pre- and post-Epic entry):**
- $100M ARR, $5.3B valuation by mid-2025
- $117M contracted ARR (growth secured even pre-Epic)
- Won top KLAS ambient AI slot in 2025
- Pivot announced: "more than an AI scribe" — pursuing real-time prior auth, coding, clinical decision support inside Epic workflows
- WVU Medicine expanded across 25 hospitals in March 2026 — one month after Epic entry (implicit market validation of continued demand)

**The "beachhead" thesis needs revision:** Original framing: "ambient scribes are the beachhead for broader clinical AI trust — documentation adoption leads to care delivery AI adoption." Epic's entry creates a different dynamic: the incumbent is commoditizing the beachhead before standalone AI companies can leverage the trust into higher-value workflows.

CLAIM CANDIDATE: "Epic's native AI Charting commoditizes ambient documentation before standalone AI scribes can convert beachhead trust into clinical decision support revenue, forcing Abridge and competitors to complete a platform pivot under competitive pressure"

**Burnout reduction confirmed (new evidence):** Yale/JAMA study (263 physicians, 6 health systems): burnout dropped from 51.9% → 38.8% (74% lower odds). Mechanism: not just time savings — 61% cognitive load reduction + 78% more undivided patient attention. The KB claim about burnout complexity is now supported.

### Track 4: OpenEvidence — Beachhead Thesis Holds for Clinical Reasoning

OpenEvidence operates in a different workflow (clinical reasoning vs. documentation) and is NOT threatened by Epic AI Charting:
- 40%+ of US physicians daily (same % as existing KB claim, much larger absolute scale)
- 20M clinical consultations/month by January 2026 (2,000%+ YoY growth)
- $12B valuation (3x growth in months)
- First AI to score 100% on USMLE (all parts)
- March 10, 2026: first 1M-consultation single day

The benchmark-vs-outcomes tension is now empirically testable at this scale. Concerning: 44% of physicians still worried about accuracy/misinformation despite being heavy users. Trust barriers persist even in the most-adopted clinical AI product.

### Key Surprises

1. **Digital behavioral support halves GLP-1 drug requirements.** At half the dose and equivalent outcomes, GLP-1s may be cost-effective under capitation without waiting for generic compression. This is the most important economic finding of this session.

2. **GLP-1 alone is NO BETTER than placebo for preventing weight regain.** The drug doesn't create durable behavioral change — only the combination does. Plans that cover GLP-1s without behavioral support are paying for drug costs without downstream savings.

3. **BALANCE model's capitation adjustment + reinsurance directly solves the March 12 barriers.** CMS has explicitly designed around the two structural barriers I identified. The question is whether plans will participate and whether lifestyle support will be substantive.

4. **Epic's AI Charting is the innovator's dilemma in reverse.** The incumbent is using platform position to commoditize the beachhead. Abridge must complete a platform pivot under competitive pressure.

5. **OpenEvidence at $12B valuation with 20M monthly consultations.** Clinical AI at scale — but the outcomes data doesn't exist yet.

## Belief Updates

**Belief 3 (structural misalignment): PARTIALLY RESOLVED.** The BALANCE model's dual payment mechanism directly addresses the misalignment identified in March 12. The attractor state may be closer to policy design than I thought.

**Belief 4 (atoms-to-bits boundary): REINFORCED for physical data, COMPLICATED for software.** Digital behavioral support is the "bits" that makes GLP-1 "atoms" work — supporting the thesis. But Epic's platform move shows pure software documentation AI is NOT defensible against platform incumbents. The physical data generation (wearables, CGMs) IS the defensible layer; documentation software is not.

**Existing GLP-1 claim:** Needs further scope qualification beyond March 12's payer-level vs. system-level distinction. The half-dose finding changes the economics under capitation if behavioral combination becomes the implementation standard.

---

## Follow-up Directions

### Active Threads (continue next session)

- **BALANCE model Medicaid launch (May 2026):** The launch is in 6 weeks. Look for: state Medicaid participation announcements, manufacturer opt-in/opt-out decisions (Novo Nordisk, Eli Lilly), early coverage criteria details. Key question: does the lifestyle support translate to structured exercise programs, or just nutrition apps?

- **GLP-1 half-dose + behavioral support replication:** The Danish study is observational. Look for: any RCT directly testing dose reduction + behavioral combination, any managed care organization implementing this protocol. If replicated in RCT, it changes GLP-1 economics more than any policy intervention.

- **Abridge platform pivot outcomes (Q2 2026):** Look for revenue data post-Epic entry, any contract cancellations citing Epic, KLAS Q2 scores, whether coding/prior auth capabilities are gaining traction. The test: can Abridge maintain growth while moving up the value chain?

- **OpenEvidence outcomes data:** 20M consults/month creates the empirical test for benchmark-vs-outcomes translation. Look for any population health outcomes study using OpenEvidence vs. non-use. This is the missing piece in the clinical AI story.

### Dead Ends (don't re-run these)

- **Tweet feeds:** Four sessions, all empty. The pipeline (@EricTopol, @KFF, @CDCgov, @WHO, @ABORAMADAN_MD, @StatNews) produces no content. Do not open sessions expecting tweet-based source material.

- **Devoted Health GLP-1 specifics:** No public data distinguishing Devoted's GLP-1 approach from generic MA plans. Plan documents confirm PA required; no differentiated protocols available publicly.

- **Compounded semaglutide:** Flagged as dead end in March 12; confirmed. Legal/regulatory mess, not analytically relevant.

### Branching Points (one finding opened multiple directions)

- **GLP-1 + behavioral combination at half-dose:**
  - Direction A: Write the standard-of-care claim now (supported by convergent observational + WHO guidelines), flag `experimental` until RCT replication
  - Direction B: Economic modeling of capitation economics under half-dose + behavioral assumptions
  - **Recommendation: A first.** Write the claim now; flag for RCT replication. Direction B is a Vida + Rio collaboration.

- **Epic AI Charting threat:**
  - Direction A: Write a claim about Epic platform commoditization of documentation AI (extractable now as a structural mechanism)
  - Direction B: Track Abridge pivot metrics through Q2 2026 and write outcome claims when market structure is clearer
  - **Recommendation: A for mechanism, B for outcome.** The commoditization dynamic is extractable now. Abridge's fate needs 6-12 months more data.

SOURCE: 9 archives created (7 new + 2 complementing existing context)
