Failure Modes · Contract 2 → 4
The architecture that scaled for one payer silently breaks for many.
Most VBC startups execute beautifully on contract 1. The wall comes at payer contract 2 or 3 — invisible until you hit it, then you're mid-rewrite with a delivery slipping. Check what's true for you.
Payer-readiness self-assessment
Check every statement that's true today. Your risk score updates live. If three or more are true, the wall is closer than it looks.
The five failure modes
Each one is invisible until it isn't. Here's the pattern, the symptom that warns you, and the fix to put in early.
Failure 01
Claims–clinical reconciliation stops scaling
Pattern: bespoke mapping logic per payer. By contract 3 you have five forks that diverge subtly.
Symptom: data engineering spends 60%+ of its time on payer-specific reconciliation bugs.
Fix early: two layers — a payer adapter that normalizes to a canonical claim shape, and domain logic that only touches the canonical. Adding payer 6 = a 2-week adapter, not a 3-month rewrite.
Failure 02
Attribution edge cases compound silently
Pattern: multi-payer membership, mid-quarter changes, and dual-eligibles each break logic that assumed clean effective dates.
Symptom: "the dashboards don't match what the payer paid us" in QBRs — the kind of thing that loses renewals.
Fix early: make attribution lag-aware and replayable. Every decision reproducible from inputs; reconcile as a daily delta job, not a quarterly fire drill.
Failure 03
ADT routing collapses under multi-source intake
Pattern: a few clean ADT feeds become 40+ sources with different formats and timing.
Symptom: care navigation misses high-priority admits — alerts arrive late or fail dedup. Interventions miss their window.
Fix early: treat ADT as a streaming, deduplicated, normalized pipeline. Canonical patient ID + normalized event type + dedup window keyed on (patient + event + time bucket).
Failure 04
Risk-model ops debt outpaces the model
Pattern: a great Q1 model drifts; feature definitions change; nobody remembers which version is in production.
Symptom: "why was this member flagged high-risk?" takes two days — or the answer is "we're not sure."
Fix early: treat models as versioned production artifacts — immutable feature store, training snapshot, decision lineage. "Why 0.73?" is a query, not an investigation.
Failure 05
The multi-payer canonical model gets vetoed for "speed"
Pattern: engineering proposes a canonical patient model; product shelves it because contract 2 wants integration in 60 days. By contract 4 you have four data models that don't talk.
Symptom: you can't answer "what's our PMPM across the whole book?" without a 3-week project. Investors ask for cross-payer benchmarks. You stall.
Fix early: invest the canonical-model time before contract 2. Slower now, dramatically faster later. Teams that win have a mature canonical model by contract 3; teams that lose keep deferring it.
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