selfdriven Clinic Org
A collaborative organisation - supported by the selfdriven Services and selfdriven.university
1. Overview
Partners: selfdriven.services × selfdriven.university
Budget Estimate: ~USD 100 000
Type: Collaborative Organisation
!! UPDATE FOR CLINIC
2. Background & Rationale
2.1 Context
Global health systems face compounding pressures: aging populations, chronic conditions, and rising costs.
selfdriven Health (SDH) envisions a shift toward participatory, data-empowered health management.
Research domains highlighted on selfdriven.health include:
- Practitioner-in-the-Loop healthcare models
- Verifiable self-generated observations
- AI-enabled behavior change and adaptive feedback loops
Supporting studies:
- Royal Society of Medicine (2022) — SDH improves outcomes and reduces costs.
- News-Medical (2022) — Patient-generated data can enhance system sustainability.
2.2 Why ORG + Token
A selfdriven ORG enables transparent, community-governed research.
The SDH token aligns incentives by rewarding participation, governance, and data contribution.
| Feature | Value |
|---|---|
| On-chain transparency | Verifiable allocation and results |
| Token-based incentives | Rewards for data and engagement |
| Community voting | Collective decision-making on experiments |
| Ethical compliance | Built-in consent and accountability |
| Scalable model | Global, modular, open-source |
3. Objectives
- Deploy a ORG-governed R&D fund powered by the SDH token.
- Execute two pilot studies aligned with selfdriven.health research domains.
- Measure outcomes in engagement, participation, and data quality.
- Publish open findings and DAO governance whitepaper.
- Validate the tokenised R&D model for sustainable research funding.
4. Research Questions
5. Methodology & Work Plan
| Phase | Months | Deliverables |
|---|---|---|
| 0 · Setup & Design | Month 1 | Form R&D committee (University + DAO) · Define governance & token model · Smart-contract design & audit · Ethics & consent protocol · Community call for proposals |
| 1 · Selection & Onboarding | Month 2 | DAO vote to select pilot studies · Recruit participants · Define instruments & pipelines · Baseline data collection |
| 2 · Pilot Execution | Months 3–4 | Conduct experiments · Token distribution · Monitor AI / practitioner feedback loops · Weekly validation |
| 3 · Analysis & Reflection | Month 5 | Data cleaning · Statistical & qualitative evaluation · Governance reflection |
| 4 · Reporting & Scale-Up | Month 6 | Publish whitepaper · Host symposium · DAO vote on next-round funding |
6. Metrics / KPIs
7. Governance Model
ORG Architecture
- Governance Token: SDH
- Voting Model: Quadratic with identity voting
- Treasury: Smart-contract-controlled multi-sig
- Roles:
- Facilitators — oversee milestones
- Contributors — submit research proposals
- Participants — engage & earn tokens
Reward Framework
| Contribution Type | Reward Mechanism |
|---|---|
| Research proposal accepted | Milestone-based SDH grants |
| Active participation | Micro-incentives (per verified action) |
| Governance engagement | Token reward / reputation gain |
| Publication or tool creation | Bonus SDH / credential NFT |
8. Budget Estimate
| Category | ** Phase 1 Cost (USD)** | Description |
|---|---|---|
| Research & Personnel | - | Academic & technical staff |
| Smart-Contract Dev & Audit | - | DAO + token logic |
| Infrastructure & Analytics | - | Cloud + dashboards |
| Participant Compensation | - | SDH / fiat hybrid |
| Legal / Compliance / Ethics | - | Privacy, IRB, contracts |
| Community Engagement | - | Workshops, comms |
| Contingency | - | 10 % reserve |
| Total | 100 000 USD | — |
9. Funding Partners
Potential sources include:
- MRFF – Emerging Priorities & Consumer-Driven Research
- NHMRC Partnership Grants
- Cardano Project Catalyst / Blockchain R&D Funds
- Philanthropic Innovation Foundations (Wellcome, Minderoo, etc.)
- Corporate HealthTech Collaborations
10. Risks & Mitigation
| Risk | Mitigation |
|---|---|
| Low community engagement | Outreach + tiered incentives |
| Governance centralization | Quadratic voting + delegation caps |
| Privacy / legal exposure | Ethics approval + encrypted data |
| Smart-contract vulnerabilities | Security audits + staged rollout |
| Regulatory uncertainty | Legal review + adaptive policy |
| Budget overruns | Milestone-based disbursement |
11. Expected Outcomes
By End Phase 1:
- Operational DAO-governed research fund
- Two pilot studies completed
- Public whitepaper + open-data release
- Demonstrated governance transparency
- Template for future DAO-led research
Long-Term Vision:
A perpetual selfdriven Health Research Network — funding, governing, and validating decentralized health innovation through tokenized collaboration.
12. Next Steps
- Finalize MoU between DAO and University.
- Deploy minimal DAO contracts (Cardano / compatible).
- Recruit founding researchers and participants.
- Apply for matched funding (public + Web3).
- Publish charter and call for participation.