18-Month Strategic Plan
Our strategic plan is built on three core pillars: Implementation Science, Knowledge Management, and Advocacy Support. This three-phase roadmap is designed to prove the efficacy of our approach and lay the groundwork for broader impact.
Implementation Science
Pilots and evidence generation for AI tools.
Knowledge Management
Centralized data and global dashboards.
Advocacy Support
Partnerships and policy influence.
Phase 1: Proof of Concept & Foundational Research
Objective: To conduct initial pilot studies that establish the feasibility and acceptability of our AI-enabled tools.
- Nurse AI Project: Complete the proof-of-concept pilot with an initial cohort of nurses in two Indian districts, focusing on assessing the tool's effectiveness in treatment planning.
- Informal Provider AI Project: Launch the proof-of-concept pilot to evaluate how ambient AI influences decision-making among informal healthcare providers, using a standardized set of clinical scenarios.
- Knowledge Management: Develop a centralized data clearinghouse to begin synthesizing and managing the data from our pilot projects, creating a single source of truth for evidence generation.
- Initial Advocacy Engagement: Identify and begin initial conversations with potential advocacy and policy partners, leveraging existing relationships with government and health ministry advisors to ensure our findings can influence future policy.
Phase 2: Evidence Generation & Expanded Feasibility
Objective: To scale our pilots, generate stronger evidence of efficacy, and build a platform to share our findings.
- Expanded Pilot: Expand the Nurse AI and Informal Provider AI projects to a larger population to assess the feasibility and acceptability of the tools at a greater scale.
- Effectiveness Study: Conduct a formal analysis of the data to generate evidence that the technology improves the quality of care, including diagnostic accuracy and adherence to guidelines.
- Global Evidence Dashboard: Begin creating a global dashboard to curate and present evidence from around the world on how IT and AI is being used to improve health in marginalized and difficult-to-reach communities. This will serve as a resource for collaborators and policymakers.
Phase 3: Dissemination, Training, and Knowledge Management
Objective: To prepare for broader implementation by disseminating our findings, building capacity through training, and exploring diversification.
- Publish Findings: Prepare and submit our findings for publication in peer-reviewed academic journals to establish our credibility and share knowledge.
- Training Capacity Building: Develop training materials and a "train the trainer" program for non-physician health workers (NPHWs), enabling partner organizations to scale the training effectively.
- Strategic Partnerships: Formally partner with organizations specializing in technology development and advocacy to leverage our knowledge management and evidence for broader impact and policy change.
- Diversification: Explore the feasibility of adapting our AI models for other healthcare cadres, such as pharmacists or community health officers.
Long-Term Goal
We will remain a knowledge management and implementation science organization. Our long-term goal is to serve as a global clearinghouse for evidence on AI in health for marginalized populations, training partners to use and deploy these proven technologies to achieve our vision of a healthier, more equitable world.
