Trust, Safety & Pharmacopoeia Verification Standards

⚠️ Important Medical & Emergency Notice

MediMatch AI does not provide medical diagnoses, treatment plans, or emergency services. Always consult a licensed doctor or pharmacist before changing any medication. In an emergency, dial 112 / 108 (India) or 911 (US) immediately.

🩺 Clinical Information & Tool Guidance

The MediMatch AI Trust and Safety Framework defines our core principles: the Zero-Guessing Clinical Policy, statutory pharmacopoeial grounding, and strict privacy protections under India's DPDP Act 2023. We ensure health queries remain confidential, ephemeral, and verified through transparent clinical safeguards and responsive pharmacovigilance channels.

EMERGENCY CLINICAL NOTICE

MediMatch AI does not provide emergency services. If you or someone you know requires urgent medical attention, immediately dial 112 / 108 (India) or 911 (US). Always verify all prescription outputs with a licensed pharmacist or physician.

1. The Zero-Guessing Policy

In healthcare AI, an honest "unreadable/verification required" notification is vastly safer than a plausible-sounding hallucination. Under our Zero-Guessing Policy, if prescription handwriting, pill imprints, packaging text, or lab biomarkers are blurred, obscured, or OCR confidence falls below 60%, automated guessing is strictly disabled. The system deterministic fallback returns ILLEGIBLE - MANUAL ENTRY REQUIRED and instructs the user to consult a licensed pharmacist.

2. Statutory Pharmacopoeial Grounding

Every medicine record, salt ratio, dosage frequency conversion, and drug interaction alert is benchmarked directly against statutory pharmaceutical standards: the Indian Pharmacopoeia (IP), National Formulary of India (NFI), British Pharmacopoeia (BP), and World Health Organization Essential Medicines List (WHO EML).

3. Patient Data Privacy & Ephemeral Processing (DPDP Act 2023)

We respect the confidentiality of health records under India's Digital Personal Data Protection (DPDP) Act 2023. Prescriptions and tablet photographs uploaded for scanning are downsampled client-side via canvas to ≤ 1600px and processed ephemerally in-memory. We never maintain permanent cloud storage of unauthenticated patient image records, serialize health queries into URLs, or sell health data to third-party brokers.

4. Multi-Layer Human Verification Mandate

Artificial intelligence is an assistive copilot, not an autonomous clinician. MediMatch AI enforces conspicuous visual callouts requiring physical pharmacist or physician verification before consuming any drug or altering any medication schedule.

5. Anti-Hallucination Architecture & Closed Formulary Matching

Generative models are constrained by deterministic closed-vocabulary dictionary verification. Extracted drug names must match an authenticated INN (International Nonproprietary Name) or official Jan Aushadhi generic monograph before being displayed to the patient.

6. Look-Alike Sound-Alike (LASA) Drug Safety Gates

To prevent medication dispensing errors caused by confusing brand or salt names (e.g. hydrOXYzine vs hydrALAzine), MediMatch AI employs ISMP-endorsed Tall-Man lettering and prominent confusion warnings across all interaction and comparison workflows.

7. Standardized Latin Sig Interpretation (ISMP)

Doctor prescription shorthand (OD, BD, TDS, QID, AC, PC, HS, SOS) is parsed according to Institute for Safe Medication Practices (ISMP) guidelines, translating Latin medical abbreviations into unambiguous patient instructions accompanied by time-of-day meal alerts.

8. Unbiased Generic Equivalence Standards (PMBJP Jan Aushadhi)

Our generic medicine comparison engine references the official Pradhan Mantri Bhartiya Janaushadhi Pariyojana (PMBJP) price schedules published by the Pharmaceuticals & Medical Devices Bureau of India (PMBI). We compare identical chemical salts and WHO-GMP bioequivalent formulations to ensure transparent healthcare access without commercial bias.

9. Algorithmic Transparency & Model Limitations

MediMatch AI explicitly surfaces confidence tiers (Low, Medium, High) on inference outputs, documents training boundaries, and provides clear disclaimers regarding the technical limits of mobile photography and computer vision OCR.

10. Discrepancy Reporting & Rapid Remediation Protocol

We maintain a dedicated clinical audit mailbox (support@medimatchai.in). Any reported pharmacological error, OCR misclassification, or regulatory update is triaged by our clinical review desk within 48 hours for immediate monograph remediation.