Digital Health, IoT & Security Engineering

Digital Health Platform Development, Medical Device Software & HIPAA Security Engineering

Consumer-grade digital health apps and wearable health platforms. FDA 21 CFR Part 11 and ISO 13485 compliant medical device software. HIPAA-compliant PHI masking and security architecture, built for regulated clinical and consumer health environments.

Digital Health Products Built Without Clinical Domain Knowledge

Apps that work as software but fail as healthcare tools, because clinical workflow alignment, patient literacy, accessibility requirements, and regulatory context were not included in the product design requirements.

IoT Data With No Governed Clinical Pipeline

Wearables generating continuous physiological data streams with no HIPAA-compliant ingestion layer, no EHR integration, and no clinical alerting logic, the device exists, but the clinical value does not.

Medical Device Software Without FDA Compliance Strategy

SaMD shipped without IEC 62304 documentation, ISO 14971 risk files, or a regulatory pathway strategy, creating 510(k) submission failure and product liability exposure at commercialization.

PHI Exposure in Development and Testing Environments

Production healthcare databases copied into dev and test environments without PHI masking, because the masking was never implemented or does not preserve referential integrity.

Digital Health, IoT & Security Engineering, What We Build

Five capability areas from consumer digital health apps and FDA-regulated medical device software through healthcare IoT platforms and HIPAA security architecture.

Digital Health Platform Development

Patient engagement, remote monitoring, telehealth, and drug pricing platforms built for clinical workflow integration and real-world patient use.

  • Patient engagement: condition management apps, medication adherence tools, and chronic disease coaching, WCAG 2.1 AA accessible
  • Remote patient monitoring platform: PRO collection, device data ingestion, symptom tracking, and clinical alert generation on threshold breach
  • Telehealth: video consultation infrastructure, asynchronous messaging, e-prescribing, and EHR chart documentation integration
  • Drug pricing transparency: real-time formulary lookup, patient cost estimation, and therapeutic alternative comparison

Medical Device Software Development, FDA & ISO 13485

SaMD development with regulatory compliance built into the process, not assembled retrospectively before submission.

  • SaMD classification and regulatory strategy: intended use definition, IEC 62304 safety classification, 510(k)/De Novo pathway selection
  • IEC 62304 software lifecycle: development plan, requirements, architecture, unit/integration/system testing, and release documentation
  • ISO 14971 risk management: hazard identification, risk estimation, control measures, and residual risk evaluation
  • Design controls: design input, output, review, verification, validation, and transfer per FDA QSR 21 CFR 820.30

Wearable Health App Development & Device Integration

Wearable connectivity engineered for clinical data quality, not just consumer dashboards.

  • HealthKit (iOS) and Health Connect (Android): continuous background collection, Garmin, Fitbit, Dexcom, Omron, and Masimo SDK integration
  • Device-to-cloud pipelines: FHIR Observation from device streams, HIPAA-compliant ingestion via AWS IoT Greengrass or Azure IoT Hub
  • Clinical alerting: threshold-based alerts (SpO2, heart rate, glucose) with configurable escalation paths to care managers
  • EHR integration: FHIR R4 Observation resources written to Epic, Cerner, or Athenahealth, visible in the clinical chart

Healthcare IoT Platform Development

Connected device ecosystems integrated into secure, governed clinical data infrastructure.

  • FDA-regulated device integration: infusion pumps, patient monitors, glucometers, via HL7 FHIR Device resource and IHE DEV profiles
  • Secure device-to-cloud: X.509 certificates, TLS 1.3, MQTT/AMQP protocol support, AWS IoT Greengrass edge computing
  • Real-time stream processing: Apache Kafka or AWS Kinesis for high-velocity ingestion, Flink for streaming analytics
  • Remote patient monitoring: structured home device capture, adherence tracking, care manager dashboard, and clinical escalation

Data Masking, PHI De-Identification & HIPAA Security

PHI security implemented at the architecture level, across production, development, testing, and analytics environments.

  • PHI masking: Datavant, Delphix, DataSunrise, referentially intact masking for dev/test that preserves data relationships
  • De-identification: HIPAA Safe Harbor and Expert Determination for research datasets and third-party data sharing
  • HIPAA architecture: VPC isolation, AES-256 encryption, TLS 1.2+, IAM least-privilege, PHI audit logging, BAA-aligned cloud config
  • SOC 2 Type II readiness: security, availability, confidentiality criteria implementation with evidence collection and audit preparation

Built for the Teams Shipping Regulated Health Products

HealthTech Startups & Medical Devices

Building regulated digital health products, HIPAA from Day 1, FDA compliance, and EHR connectivity for enterprise sales.

  • HIPAA-compliant architecture
  • FDA SaMD regulatory strategy
  • ISO 13485 QMS implementation
  • Epic App Orchard integration
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Hospitals & Health Systems

Remote patient monitoring platforms, patient engagement tools, and HIPAA security architecture for health system digital programmes.

  • Remote patient monitoring
  • Patient engagement apps
  • HIPAA architecture review
  • IoT device integration
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Life Sciences & Pharma

Connected device clinical trials, ISO 13485 medical software, and HIPAA-compliant data environments for pharma R&D.

  • ISO 13485 medical device software
  • Digital therapeutics
  • Clinical trial device data
  • PHI masking for research
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Frequently Asked Questions

What is ISO 13485 and when does digital health software require it?
ISO 13485:2016 is the quality management standard for medical devices. Digital health software requires it when the software meets the SaMD definition, software intended for diagnosis, prevention, monitoring, treatment, or alleviation of disease. Examples include ECG analysis apps, remote monitoring platforms that alert clinicians to deterioration, and AI-driven CDSS that influences specific treatment decisions. ISO 13485 requires a documented QMS covering software development (IEC 62304), risk management (ISO 14971), design controls, and post-market surveillance.
How do you maintain HIPAA compliance throughout the software development lifecycle?
HIPAA compliance is addressed at every phase: design (PHI data flow analysis, access control and encryption design before code is written); development (HIPAA safeguards as infrastructure-as-code so controls are version-controlled and reproducible); testing (PHI masking in all non-production environments, developers never access production PHI); deployment (automated compliance scanning before go-live); and operations (continuous PHI access monitoring, key rotation, and quarterly access control reviews).
What is the difference between PHI data masking and PHI de-identification?
PHI masking replaces real patient values with realistic substitutes, preserving data structure and referential integrity for development and testing while removing identifying information. It is reversible and for internal use only. PHI de-identification permanently removes or transforms all 18 HIPAA-specified identifiers (Safe Harbor method) or is certified by a statistical expert (Expert Determination method) so the data is no longer PHI. De-identified data can be shared under data use agreements for research and analytics without the consent and BAA requirements that apply to PHI.
How do you integrate wearable device data into a clinical platform without compromising data quality?
Four engineering problems must be solved simultaneously. Data continuity: handling out-of-order delivery, gap filling when sync is delayed, and duplicate detection. Data normalization: mapping heart rate, SpO2, and glucose from different devices to the same LOINC codes, units, and temporal resolution. Clinical accuracy classification: tagging consumer-grade vs clinical-grade data to enforce appropriate clinical use. HIPAA compliance: timestamps and physiological data linked to an individual are PHI, the device-to-cloud pipeline must enforce TLS, HIPAA cloud storage, IAM controls, and PHI audit logging from the first data point.

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