Build Clinical Decision Support System rules engine and alerting

How the CDSS Fits Into the Kiosk Architecture A CDSS in the kiosk ecosystem acts as the clinical brain of the system. It receives patient vitals and contextual data from the kiosk, applies evidence based rules or AI models, and returns actionable insights for triage, risk scoring, referral, and follow up. It must integrate seamlessly with the backend, patient app, doctor app, and analytics layer using standard health interoperability protocols. Purpose of the CDSS in the Kiosk Ecosystem The CDSS is not just an add on — it is the clinical intelligence layer that transforms raw measurements into meaningful decisions. Core Purposes • Risk Stratification: Identify high risk patients (hypertension, diabetes, respiratory issues, substance abuse, etc.). • Clinical Triage: Recommend next steps (self care, teleconsultation, urgent referral). • Decision Support for Doctors: Provide guideline based suggestions during teleconsultation. • Population Health Insights: Detect patterns across kiosks (e.g., rising BP trends in a community). • Quality & Compliance: Ensure all outputs follow clinical guidelines (WHO, local MOH). CDSS is not standalone — it is embedded into the workflow and must operate in real time, with high reliability and auditability. Where the CDSS Gets Its Data Your infographic already shows the ecosystem. Here’s how to explain the data flow clearly: Data Sources Feeding the CDSS • Kiosk Peripheral Devices o Blood pressure monitor o Weight scale o Temperature sensor o SpO₂ sensor o Glucose meter o Drug of abuse testing module o Future modules (ECG, spirometry, etc.) • Patient App Inputs o Symptoms o Medical history o Lifestyle data o Medication adherence o Demographics • Doctor App Inputs o Clinical notes o Diagnoses o Prescriptions o Follow up plans • Backend Platform o Historical patient records o Previous kiosk visits o Alerts and flags o Population health datasets • Telemetry & Device Performance o Device reliability o Measurement quality o Error logs Data Flow Summary Kiosk → Backend → CDSS Engine → Insights → Patient App / Doctor App / Command Center Dashboard What Insights the CDSS Must Produce These are the insights suppliers must commit to delivering. Patient-Level Insights • Risk scores (cardiac, diabetic, respiratory, substance abuse) • Abnormal vital alerts (threshold-based + trend-based) • Early warning scores • Personalized recommendations (self-care, lifestyle, follow-up) • Medication adherence risk • Referral urgency classification Clinician-Level Insights • Diagnostic support based on guidelines • Suggested investigations • Treatment pathways • Contraindication alerts • Drug–drug interaction alerts • Chronic disease management plans System-Level Insights • Population health trends • Outbreak detection signals • Device performance analytics • Kiosk utilization patterns • Predictive maintenance alerts Interoperability Requirements (Specs Suppliers Must Meet) The following are clear, non-negotiable specs. Standards & Protocols • FHIR (HL7) APIs o Patient o Observation o Encounter o Condition o Medication o CarePlan • DICOM (if imaging modules added later) • LOINC coding for lab/vital measurements • SNOMED CT for diagnoses and clinical terminology Integration Requirements • Real-time API ingestion from kiosk backend • Ability to push insights back to: o Patient app o Doctor app o Command center dashboard • Support for offline mode with sync • JSON/RESTful API compatibility • Secure authentication (OAuth2, JWT) Security & Compliance • End-to-end encryption • Audit logs for all decisions • Role-based access control • Compliance with POPIA (South Africa), GDPR, HIPAA-equivalent safeguards Performance Requirements • Decision latency less than 2 seconds • 99.5% uptime • Scalable to thousands of kiosks • Cloud + edge computing capability