Understanding Health Data APIs
Incorporating health data into your application is extremely powerful. When selecting a biomarker API platform, you need to consider more than just raw data access. Intelligence layers are crucial for transforming measurements into actionable insights. Maximum coverage mattersāthe more wearables supported plus smartphone monitoring, the more users you can serve.
Who This Guide Is For
This comprehensive resource helps developers, product managers, and technical decision-makers evaluate health data API platforms including Sahha, Terra, Rook, Spike, and Vital. Learn the differences between raw data aggregation and intelligence-powered platforms.
About This Guide
What this site is: A comprehensive technical guide with platform comparisons, integration patterns, and biomarker education.
What this site is not: We do not provide API services. We evaluate and compare existing platforms (Sahha, Terra, Rook, Spike) to help you choose the right solution.
What Are Biomarkers?
Biomarkers are measurable indicators of health statusāfrom sleep quality and activity levels to heart rate variability and stress markers. They transform raw sensor data into actionable health insights that power personalized recommendations, retention predictions, and wellness interventions.
Types of Biomarkers
Biomarkers are organized into five main categories:
- Activity - Steps, exercise minutes, energy expenditure
- Body - Weight, BMI, body composition
- Vitals - Heart rate, blood pressure, oxygen saturation
- Sleep - Duration, quality, sleep stages
- Reproductive - Menstrual cycle tracking
Some biomarkers can be collected passively from smartphones without any wearable device, while others require specific wearable sensors. Understanding which biomarkers you need and how to access them is crucial for building effective health applications.
View Comprehensive Biomarker Breakdown ā
Why Intelligence Layers Matter
Raw data tells you what happened. Intelligence layers tell you what it means and what to do next. This is the critical difference between data aggregation and actionable health intelligence.
Raw Data Only
Sleep data:
- Duration: 7h 23m
- Deep sleep: 1h 12m
- REM sleep: 1h 45m
- Interruptions: 4
What does this mean? You have to figure it out.
Intelligence Layer
Sleep quality score: 0.72 (Medium)
Insight: "Sleep quality below your baselineārecovery capacity reduced by 15%"
Recommendation: "Reduce workout intensity today. Avoid evening caffeine."
Retention signal: "3 consecutive nights of declining sleepāengagement risk in 10 days"
Explore Intelligence Layers & Scores ā
Platform Comparison
Here's an honest comparison of major health data aggregators. Each has strengths depending on your use case.
| Platform | Wearable Integration | Intelligence Layers | Data Retention | Real-time Data |
|---|---|---|---|---|
| Sahha | HealthKit Health Connect + Smartphone | 5 Scores 14 Archetypes + MCP | 3 months | Yes |
| Terra | 300+ devices HealthKit Health Connect | Raw data only | Pass-through | Yes |
| Rook | HealthKit Health Connect Limited devices | Raw data only | 10 days | Batch only |
| Spike | Medical Equipment EMR systems | GenAI processing | Pass-through | Yes |
| Vital/Junction | Lab testing only Wearables sunset | Raw data only | Pass-through | Yes |
Sahha vs Terra
Behavioral intelligence vs raw data aggregation
Read comparison ā
Sahha vs Rook
Intelligence layers vs simple aggregation
Read comparison ā
Sahha vs Spike
Consumer health vs medical equipment focus
Read comparison ā
Rook vs Terra
Batch processing vs real-time webhooks
Read comparison ā
Integration Approaches
There's no single "best" approachāthe right choice depends on your use case. The three main strategies are:
Direct Device Integration
Integrate directly with 300+ device manufacturers. Maximum device breadth but 6-12 month timeline and ongoing maintenance burden.
Platform APIs
Use HealthKit (iOS) and Health Connect (Android) for unified wearable access. Simpler integration but limited to devices users already own.
Smartphone Sensors
Passive monitoring via accelerometer, screen time, and app usage. 100% coverage without wearables but different data precision.
Read Complete Integration Guide ā
Industry Applications
Biomarkers power applications across diverse industriesāfrom insurance underwriting to fitness coaching, mental health monitoring to supplement personalization.
š„ Insurance & Health Plans
Wellness programs, risk assessment, claims prediction, member retention. Requires 100% coverage via smartphone monitoring.
šļø Fitness Apps & Gyms
Personalized workouts, recovery optimization, churn prediction. Intelligence layers adjust intensity based on sleep quality.
š§ Mental Health
Depression detection 3-5 days early, intervention tracking, crisis prevention. Passive smartphone monitoring reduces patient burden.
š Supplements
Personalize supplement stacks based on sleep, activity, stress. Track effectiveness over time with biomarker trends.
š¬ Clinical Research
Remote patient monitoring, adherence tracking, real-world evidence. High data quality for regulatory compliance.
š¤ AI/ML Models
Pre-processed features accelerate model development. Historical data enables supervised learning for health predictions.
Deep Dive Guides
Explore specific topics in depth with our detailed guides:
Biomarker Types
Complete overview of biomarker categories, collection methods, and applications
Why Intelligence Layers Matter
Deep dive on processing raw data into actionable insights with ROI examples
Smartphone vs Wearable Data
Coverage analysis, accuracy trade-offs, and when each approach makes sense
Platform APIs vs Direct Integration
Cost comparison, maintenance burden, and technical implementation
Choosing a Health Data API
Decision framework, requirements checklist, and platform evaluation
Integration Best Practices
Technical guide covering auth, data models, webhooks, error handling