Hope for Ethos Sudha Community-CITYLAB CATALYST PROJECT

 Pragya Richa | CityLab Catalyst | Healthcare Innovation 

 This project focused on enabling real-world adoption of an AI-powered diabetes management platform by addressing a critical but often overlooked barrier: reimbursement. While many digital health solutions are clinically strong, they fail to scale because they do not align with how healthcare is paid for in the U.S. 

I initially joined the project with a narrow technical task:

Identify the medical codes physicians could use to prescribe an AI diabetes platform. 

At the outset, my work centered on identifying ICD-10 diagnosis codes and CPT/HCPCS procedure codes related to diabetes care.

As I researched the codes, I realized that codes alone are not enough.

In U.S. healthcare, reimbursement follows a strict and interconnected logic:

Diagnosis → Procedure → Payer → Approval

Without understanding and designing for this full chain, even the most innovative AI tools cannot be prescribed, reimbursed, or adopted at scale. This realization led me to expand my role beyond code identification into systems-level design.

I developed a Diabetes Reimbursement Framework that translates innovation into real-world feasibility:

Mapped Type 1 and Type 2 diabetes and major complications—including neuropathy, CKD, foot ulcers, and Charcot joints—to establish medical necessity.

Identified reimbursable services aligned with digital diabetes management:

• Chronic Care Management (CCM)
   
• Remote Patient Monitoring (RPM)
   
• Remote Therapeutic Monitoring (RTM)
   
• Diabetes Self-Management Training (DSMT)
   
• Medical Nutrition Therapy (MNT)
   

Clarified how reimbursement differs across settings:

• Outpatient (OPD): CPT/HCPCS-based reimbursement, where the AI platform is prescribed
   
• Inpatient (IPD): DRG-based bundled payments, representing costly complications the platform aims to prevent
   

Analyzed Medicare, Medicaid, commercial insurance, HMOs, and self-pay models to identify coverage variability and adoption constraints.

Built a structured Diabetes Reimbursement Tracker (Excel) linking:
ICD-10 → CPT/HCPCS → Payer rules,
forming the prescribability backbone for the AI platform and enabling future automation.

Enables physicians to prescribe the platform with clarity and confidence

Reduces claim denials by aligning documentation with CMS requirements

Bridges the gap between clinical innovation and financial viability

Strengthens outpatient care pathways to help prevent costly inpatient complications

 I demonstrated innovative leadership by:

• Expanding the project scope beyond the initial ask when systemic gaps became evident
   
• Applying systems thinking across clinical, policy, and reimbursement domains
   
• Translating complex healthcare rules into practical tools others could immediately use
   
• Bridging lived patient experience, technology design, and healthcare economics
   

Rather than completing a task, I reshaped the direction of the work to ensure real-world applicability.

This experience reinforced a core insight:

Healthcare innovation becomes real only when reimbursement aligns with care.
The framework I built is adaptable beyond diabetes to other chronic conditions where AI, monitoring, and payment models must work together to advance equity, access, and sustainability—directly aligning with CityLab Catalyst’s mission.