Philcis Facility Management Ltd
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Building Open, Evidence-Based Health Technology

Building Open, Evidence-Based Health TechnologyBuilding Open, Evidence-Based Health TechnologyBuilding Open, Evidence-Based Health Technology

Healthcare software should be inspectable. Philcis builds traceable, evidence-driven open-source health technology. 

Building Open, Evidence-Based Health Technology

Building Open, Evidence-Based Health TechnologyBuilding Open, Evidence-Based Health TechnologyBuilding Open, Evidence-Based Health Technology

Healthcare software should be inspectable. Philcis builds traceable, evidence-driven open-source health technology. 

Our Mission

Our mission is to develop open-source health technology that integrates clinical AI, healthcare data science, and evidence-based healthcare AI, all while ensuring robust safety controls. We prioritize the creation of practical systems that are transparent and traceable, ultimately designed to enhance clinical decision support and foster better healthcare decisions.

FlynnMed Clinical Intelligence & Care Coordination Architecture

 

FlynnMed brings structured health records, deterministic safety checks, evidence retrieval and role-aware clinical support into one traceable workspace for patients, carers and healthcare professionals. Explore FlynnMed 

Open Source Code

Unified Patient Context Management

Combines symptoms, medicines, allergies, observations, documents, history and patient preferences into a structured longitudinal record. 

Safety-governed Clinical intelligence

Applies consent and access controls, deterministic safety rules, clinical policy checks, and trusted evidence retrieval before generating role-aware clinical support. 

Traceable patient–clinician workflow

Connects patients and healthcare professionals through consented information exchange, evidence-backed answers, care plans, pre-visit summaries and clinical review, with audit and evidence lineage maintained 

Connected Workspaces for Patients and Care Teams

Patient Workspace

A personal health workspace that helps patients and carers organise their health information, understand supported risks and stay actively involved in their care. 

 

Key features

  • Structured longitudinal health record 
  • Symptoms, medicines, allergies, observations and documents 
  • Safety findings and supported next steps 
  • Evidence-based health questions with traceable sources 
  • Care plans and task tracking 
  • Health timeline and trends 
  • Clinical trial matching 
  • Clinician access and consent control 
  • Appointment preparation and clinical notes

Care Team Workspace

A consent-controlled clinical workspace for healthcare professionals to review patient context, access evidence and prepare clinical actions within their professional role. 


Key features

  • Consent-based patient record access 
  • Patient list and longitudinal clinical context 
  • Evidence-backed clinical questions 
  • Pre-visit summaries 
  • Record-scoped clinical chat 
  • Safety review and supported-risk findings 
  • Draft medication and care proposals 
  • Evidence provenance and source traceability 
  • Audit trail of clinical interactions and decisions

Platform Architecture & Capabilities

FlynnMed is built as an inspectable open-source clinical software stack using React and TypeScript, FastAPI, PostgreSQL and modular Python services. The safety, evidence, policy and orchestration layers can be independently reviewed, tested and extended, with the platform released under the MIT Licence. 

FlynnMed includes an optional MCP server that exposes selected clinical capabilities to approved AI clients and agents through controlled tool interfaces. These tools support functions such as patient-context retrieval, clinical-output validation, note generation, trial search and email delivery, with authenticated HTTP access available through the FastAPI application. 

Clinical workflows pass through deterministic safety rules and policy controls before supported information is presented or acted upon. Current checks cover defined high-risk scenarios including potassium abnormalities, emergency symptoms, medicine–allergy conflicts and selected warfarin–NSAID combinations, while policy gates constrain responses according to role, context and permitted workflow. 

The retrieval layer searches authoritative clinical guidance, medicines data, biomedical literature and clinical-study services, including NHS/NICE, CDC, MedlinePlus, openFDA, Europe PMC/PMC and ClinicalTrials.gov. Source provider, jurisdiction and available reuse metadata are retained so evidence can be ranked and presented without treating guidance from different jurisdictions as interchangeable. 

 Retrieved evidence is extracted, ranked and evaluated before being incorporated into a clinical response. FlynnMed preserves source provenance, handles conflicting evidence, links claims back to supporting passages and applies policy checks before generating a role-appropriate answer, allowing important claims to remain traceable to their underlying evidence. 

 FlynnMed records the relationship between patient context, retrieved evidence, generated claims and clinical workflow events. Consent records, audit events, evidence ledgers and answer-claim lineage provide a reviewable history of how information was accessed, what evidence supported an output and how the resulting clinical interaction progressed.  

Downloads

Technical Performance and Safety Evaluation of FlynnMed on HealthBench Consensus 500 (pdf)Download

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 © 2026 Francis Osei. All rights reserved. 

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