Why Multi-Sig Wallets Are Inadequate for Patient Consent

Multi-sig is designed for asset custody and transaction approval, not for managing dynamic, granular data permissions. It treats consent as a binary on/off switch for a wallet, not a nuanced policy for specific data types, researchers, or time periods.\n- Static Logic: Cannot encode conditions like 'share lab results for 30 days with IRB-approved studies only'.\n- All-or-Nothing: A signature grants access to the entire wallet's data payload, violating data minimization principles.\n- Manual Overhead: Requires active, synchronous signer coordination for every new data request, creating a >24hr latency bottleneck.

Multi-sig introduces single points of failure for patient autonomy. If a patient loses a key or a designated guardian is unavailable, consent is permanently frozen. Furthermore, once a transaction is signed, the data access is irrevocable; there is no native mechanism to revoke access after a set period.\n- Fragile Recovery: Social recovery schemes (e.g., Safe{Wallet}) are slow and socially complex for non-crypto users.\n- No Time-Based Revocation: Data access, once granted, persists indefinitely unless the provider manually complies with a revocation request.\n- Guardian Centralization: Often devolves to a 2-of-3 sig with two institutional keys, defeating patient sovereignty.

Patient consent must be managed by programmable policy engines (e.g., zk-Circuits, Lit Protocol), not multi-signature committees. This allows patients to set rules that execute autonomously.\n- Attested Data Access: A researcher's credential (e.g., a Verifiable Credential from an IRB) becomes a signed input to a ZK circuit that unlocks specific data.\n- Automatic Expiry: Consent logic natively includes timelocks, auto-revoking access after the policy term.\n- Minimal Disclosure: Prove attributes (e.g., 'over 18', 'diagnosis X') without revealing the full record, using zk-SNARKs (like zkEmail for health data).

Patients should declare what they want (e.g., 'contribute to cancer research'), not manually approve how (individual data transactions). This mirrors the shift from limit orders to intent-based DEXs like UniswapX and CowSwap.\n- Declarative Policies: Set a high-level intent ('share anonymized genomics for non-commercial research'). A Solver network (like Anoma, SUAVE) finds matching research requests.\n- Passive Earnings: Patients can be matched with data buyers (e.g., VitaDAO-style projects) and compensated automatically via embedded payment rails.\n- No Live Signing: Eliminates the coordination overhead that makes multi-sig-based consent systems non-viable at scale.

Multi-sig is designed for asset custody and protocol upgrades, requiring consensus among a static set of signers. Patient consent is dynamic, time-bound, and requires fine-grained, revocable permissions for specific data types and uses.

• Static Signer Set vs. Dynamic Patient Intent
• All-or-Nothing Access vs. Granular Data Scopes
• Manual, Opaque Execution vs. Programmable, Verifiable Flows

ZK proofs allow patients to prove specific claims about their data (e.g., 'I am over 18', 'My A1C is below 7.0') without revealing the underlying raw data. This enables selective disclosure and computation on encrypted data.

• Privacy-Preserving: Share proofs, not raw PHI.
• Granular & Revocable: Consent is scoped to specific data predicates and time windows.
• Auditable Trail: All consent grants and data uses are immutably logged on-chain.

DIDs give patients a self-sovereign identity anchor. Verifiable Credentials (VCs) are tamper-proof, cryptographically signed attestations (e.g., a lab result) issued to that DID. The patient's wallet becomes a consent orchestrator.

• Self-Sovereign: Patient controls their identity and credential portfolio.
• Interoperable: Standards-based (W3C) framework works across institutions.
• Machine-Readable: Enables automated, policy-driven access for researchers.

A smart contract acts as the policy engine and access gateway. It holds the logic for: validating ZK proofs, checking VC validity periods, enforcing data usage terms, and logging access events. Think of it as UniswapX for data, matching intent with permission.

• Automated Enforcement: Code is law for data use agreements.
• Transparent & Auditable: Every access request and grant is on-chain.
• Composable: Can integrate with DeFi for incentive alignment (e.g., token rewards for data sharing).

Multi-sigs treat consent as a one-time administrative signature, not a continuous, context-aware policy. This leaks the complexity of real-world medical logic into off-chain processes.

• Key Flaw: Consent is a state, not an event. A 2-of-3 signature doesn't encode duration, data scope, or revocation triggers.
• Real Consequence: Leads to manual, error-prone workflows or over-permissioned access, violating the principle of least privilege.

Revoking access in a multi-sig setup requires a new transaction and signer coordination, creating a dangerous lag where data remains exposed.

• Key Flaw: No native, patient-initiated revocation. Patients cannot unilaterally 'undo' a signed transaction after the fact.
• Architectural Debt: Forces builders to layer notification systems and timelocks on top, creating a Rube Goldberg machine of compliance instead of a native primitive.

The solution is shifting from transaction signing to declarative intent fulfillment, inspired by systems like UniswapX and CowSwap. Patients express desired outcomes (e.g., 'share my MRI with Dr. Smith for 30 days'), not low-level approvals.

• Key Benefit: Enables programmable, time-bound, and granular consent as a native blockchain object.
• Builder Action: Implement via ZK-proofs for minimal disclosure or attribute-based encryption linked to on-chain policy NFTs, moving logic on-chain.

Valid consent often requires evaluating logic (e.g., 'is this requester a licensed oncologist?'). Multi-sigs cannot compute; they can only sign.

• Key Flaw: Pushes critical verification off-chain to centralized oracles, reintroducing trust.
• Solution Path: Leverage zk-proofs (e.g., zkOracle proofs) or decentralized identity attestations (like Veramo, SpruceID) to make verification a trustless, auditable component of the access flow.

Multi-sig participant sets don't scale for large research cohorts or dynamic care teams. Adding/removing members is a governance headache.

• Key Flaw: O(n) complexity for participant management, creating operational bottlenecks.
• Architect's Leverage: Use threshold cryptography (e.g., tSS, MPC) or policy NFTs that represent group membership, allowing a single on-chain policy to govern access for millions without updating signer sets.

Multi-sigs are often EVM-centric, but patient data ecosystems involve diverse systems. Bridging consent across chains/L2s with multi-sigs is a security nightmare.

• Key Flaw: Forces reliance on vulnerable bridge architectures (see: LayerZero, Wormhole hacks) to mirror permissions.
• Future-Proof Design: Build with cross-chain state abstraction in mind. Use general message passing with proofs or design consent as a sovereign rollup state root, making the policy layer chain-agnostic.