Principled consent-first design with best scope discipline in batch — but design phase only, no code, no FHIR/HL7, no AI layer. Blueprint not product.
Principled design, exceptional scope discipline, no code yet. Check back at spec-to-code phase. CLA governance structure worth noting in open-source health data governance framing.
Not a runnable repository (spec, white paper, or design artifact). UHR is a design specification — README, governance docs, and an AGPL-3.0 + CLA license. There is no application to install yet. Read the spec to understand the consent-first append-only data model, then revisit once the project moves into the spec-to-code phase.
URL: https://github.com/Aaqib-bashir1/unified-health-record
Date: 2026-05-28
Analyst: FRAME v1.0 / Synambix
Documents reviewed: README.md
FUNCTIONAL | Score: 12/24 | Principled design with strong scope discipline — but design-phase only, no working code, no interoperability standards, and no AI layer. Scores at the FUNCTIONAL floor on the strength of its “what this is not” clarity alone.
| Dimension | Score | Evidence |
|---|---|---|
| Patient Agency Index | 2/3 | Patient owns data; consent-first access; explicit, revocable, scope-bound access model; correct framing. Design-phase only — no implementation to verify architecture backs up claims. |
| Architecture Integrity | 1/3 | Append-only data model and amendment-based corrections described in principles. No architecture doc or technical implementation visible. SECURITY.md exists but design only. |
| Technical Maturity | 0/3 | Explicitly “design and foundation phase. No production deployment exists yet.” Scope frozen, core models being defined. 1 star, 0 forks, no code visible beyond documentation. |
| Safety & Disclaimer Posture | 2/3 | ”No AI diagnosis or treatment recommendations” explicit; “no automated clinical decision-making”; “context and clarity, not medical judgment.” No “not a medical device” disclaimer by name. SECURITY.md linked. |
| Interoperability Stack | 1/3 | No health interoperability standards mentioned. No FHIR, HL7, CCDA, or any EHR connector. “Manual digitisation supported” is the only data path mentioned. May be in the spec doc — not visible from README. |
| CLAIM Alignment | 2/3 | ”Clarity over automation. Consent over convenience. Continuity over speed.” No AI in scope. Patient agency framing is correct. No explicit CLAIM literacy framework. No interrogative stance design. |
| Sustainability Model | 1/3 | AGPL-3.0 with CLA granting project lead right to relicense. Single maintainer. 1 star. Design phase. No community. |
| Scope Honesty | 3/3 | ”What UHR Is NOT” section with explicit ❌ bullets. “Design and foundation phase” stated. “No production deployment exists yet.” The clearest scope statement of any project in the batch. |
| TOTAL | 12/24 |
Contextual Grounding: Not applicable — no AI layer by design. The system stores patient records but does not process them with AI.
Interrogative Stance: Not applicable by design. UHR provides “context and clarity, not medical judgment” — it is explicitly not a reasoning partner.
Associative Integration: Low. No interoperability standards means no path to connect this system’s records to other health data sources or AI tools without manual export.
Judgment Layer Activation: Correct in concept. The consent model, the explicit “no automated clinical decision-making” commitment, and the doctor-notification-when-history-is-filtered all put the patient in the judgment seat. No implementation to verify.
Methodological Transfer: Not in scope. This is a record-keeping tool, not a literacy platform.
UHR starts from the right premise — information loss is the core problem, not lack of expertise — and designs toward the right solution: a patient-controlled longitudinal timeline with consent-first access. The principles are sound. The gap between principle and implementation is currently total.
The project scores at the FUNCTIONAL floor rather than ASPIRATIONAL for one reason: its scope discipline. It knows exactly what it is not, and it states this clearly. That discipline is harder to maintain than it looks, and most patient AI projects that score higher on technical maturity have lost it somewhere.
If this project produces working code that implements its stated design, it would score 15-17 — FUNCTIONAL with a clear path to FOUNDATIONAL if it adds FHIR import and an AI reasoning layer. Right now it is a well-designed blueprint.
MONITOR. The design is principled and the scope discipline is exceptional. No code yet. Check back when the spec-to-code phase begins. The CLA governance structure is worth noting in any PRISM-N or open-source health data governance framing.