JEEVHITAA -- An End-to-End HCAI System to Support Collective Care

TL;DR

JEEVHITAA is a mobile health system that supports coordinated, multi-actor care networks with secure data sharing, role-aware access, and AI-generated summaries, addressing limitations of current individual-centric platforms.

Contribution

The paper introduces JEEVHITAA, a novel end-to-end system enabling secure, role-based, multi-actor health data sharing with integrated AI summaries, filling a gap in existing mobile health solutions.

Findings

System architecture and security primitives demonstrated robustness with synthetic data.

Feasibility study confirmed practical use in real-life care circles.

Plans outlined for longitudinal evaluation of access control and credibility.

Abstract

Current mobile health platforms are predominantly individual-centric and lack the support for coordinated, auditable multi-actor workflows. However, in many settings worldwide, health decisions are enacted by multi-actor care networks rather than single users. We present JEEVHITAA, a cross-platform mobile system enabling role-aware sharing and verifiable information flows within permissioned care circles. JEEVHITAA ingests platform and device data (Health-Connect, BLE), builds layered profiles from sensors and tiered onboarding, and enforces fine-grained, time-bounded access control across care graphs. Data are end-to-end encrypted both locally and during peer synchronization; documents can be captured or uploaded as PDFs. An integrated retrieval-augmented LLM produces structured, role-targeted summaries and action plans, offers evidence-grounded verification with provenance and confidence scores, and supports advanced insights on reports. We describe the architecture, connector abstractions, security primitives, and report robustness evaluations using synthetic ontology-driven data, as well as a feasibility study with a real-life care circle. We outline plans for longitudinal in-the-wild evaluation of access control correctness and credibility support.