Analytics for
Healthcare Apps
Data minimization architecture for telemedicine, mental health, fitness, and medical apps. Only 5 fields stored. No device IDs. IP never retained in analytics.
The Healthcare Analytics Challenge
Standard analytics tools weren't designed with healthcare data sensitivity in mind
Device Identifiers
Standard tools collect IDFA, IDFV, and GAID by default. Combined with health-related events, these become sensitive data.
Risk: Device ID + "booked_therapy_session" = sensitive combination
Unlimited Custom Properties
Tools that accept arbitrary data fields create risk of accidental health data leakage by developers.
Risk: One logEvent({condition: "diabetes"}) creates exposure
IP Address Retention
Many analytics tools store or log IP addresses. Regulators increasingly view IP + health context as sensitive.
Note: HHS guidance (2024) treats IP + health context as potentially protected
Persistent User Tracking
Cross-session user IDs create longitudinal health profiles that may trigger additional regulatory requirements.
Risk: User profiles spanning months of health-related behavior
Third-Party Destinations
Analytics data often flows to advertising networks, making it difficult to control where health data ends up.
Complexity: Multiple data processors increase audit surface
Audit Burden
The more data you collect, the more you need to document, secure, and potentially provide in subject access requests.
Overhead: Unlimited fields = unlimited audit scope
Our Approach: Data Minimization by Design
Return of Avoidance (ROA) β the best way to protect sensitive data is to never collect it
What We Store
Exactly 5 fields, enforced by API
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1.
event_name
What action occurred (e.g., "appointment_booked")
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2.
session_id
Temporary, rotating every 2 hours, hashed server-side
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3.
timestamp
When the event occurred
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4.
platform
iOS or Android
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5.
country
Derived from IP (country-level only), IP then discarded
API Enforcement: Any extra fields are silently rejected. Developers cannot accidentally leak data.
What We Don't Store
By design, not by configuration
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β
IP addresses
Processed transiently for geolocation, never stored in analytics
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β
Device IDs (IDFA, IDFV, GAID)
Never collected, never transmitted
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β
Persistent user IDs
No cross-session user tracking
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β
Custom properties
API rejects any extra fields
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β
User agent strings
Not collected, not stored
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β
Precise geolocation
Only country-level, not city or coordinates
Audit-friendly: If it's not collected, it can't be breached, leaked, or requested.
Technical Architecture
RAM-Only Session IDs
Session identifiers are generated in device memory and never written to disk. On app restart, a new session begins automatically.
2-Hour Rotation
Session IDs rotate automatically every 2 hours of active use. Long sessions don't create persistent identifiers.
Server-Side Hashing
Session IDs are hashed server-side with a daily rotating salt. Even if data were accessed, session correlation across days is impossible.
What Healthcare Apps Can Measure
Data minimization doesn't mean no insights β it means focused insights
Feature Adoption
Which features are used most? Where do users spend their time? What's gaining traction?
Conversion Funnels
Auto-discovered conversion paths show you how users progress through booking, onboarding, or treatment flows.
Drop-Off Detection
Automated alerts when users abandon key flows β like appointment booking or medication logging.
Session Depth
Average events per session, session duration, and engagement patterns across platforms.
Platform Comparison
iOS vs Android engagement, conversion rates, and feature usage differences.
Geographic Trends
Country-level distribution of usage β understand where your app is gaining traction.
β οΈ Honest Limitations
Session-based analytics intentionally cannot provide some metrics that require persistent user tracking:
- β’ DAU/MAU: Requires persistent user IDs
- β’ Cohort retention: D7/D30 retention requires cross-session tracking
- β’ Individual user journeys: We track sessions, not people
- β’ Cross-device tracking: Intentionally impossible
This is a deliberate design choice β these are the metrics that require the most sensitive data. For healthcare apps, this trade-off often makes sense.
Healthcare App Types
Data minimization benefits any app handling health-adjacent information
Telemedicine & Telehealth
Track appointment booking flows, video call quality indicators, and feature usage without linking to patient identity.
- β’ Appointment booking conversion rates
- β’ Feature adoption (chat, video, messaging)
- β’ Session engagement patterns
Mental Health & Wellness
Understand how users engage with meditation, journaling, or therapy features without creating sensitive behavioral profiles.
- β’ Feature engagement (meditations, exercises)
- β’ Session completion rates
- β’ Onboarding funnel optimization
Fitness & Health Tracking
Measure workout feature usage, tracking adoption, and in-app engagement without building individual health profiles.
- β’ Workout completion patterns
- β’ Feature discovery and adoption
- β’ Platform comparison (iOS vs Android)
Women's Health & Fertility
Particularly sensitive category. Track feature usage and conversion flows without any personal health data retention.
- β’ Feature engagement metrics
- β’ Onboarding completion rates
- β’ Geographic distribution
Medical Device Companion Apps
Understand how users interact with device pairing, data sync, and monitoring features without storing device-patient links.
- β’ Device pairing success rates
- β’ Feature usage patterns
- β’ Error and drop-off detection
Patient Portals
Track portal feature usage, message/scheduling adoption, and engagement without linking analytics to patient records.
- β’ Feature adoption rates
- β’ Task completion funnels
- β’ Mobile vs web comparison
Frequently Asked Questions
What data does Respectlytics store for healthcare apps?
Exactly 5 fields: event_name, session_id, timestamp, platform, and country. No device identifiers (IDFA, IDFV, GAID), no user IDs, no custom properties. IP addresses are processed transiently for country-level geolocation and immediately discardedβnever stored in analytics.
How does session identification work?
Session IDs are generated in device RAM only (never written to disk), rotate automatically every 2 hours, and reset on app restart. Server-side, they're hashed with a daily rotating salt. This makes cross-session tracking technically impossible.
Can developers accidentally send health data through custom properties?
No. Unlike Firebase or Mixpanel, Respectlytics enforces a strict 5-field schema at the API level. Any extra properties are silently rejected. This prevents accidental PII or health data leakage by design.
What analytics can healthcare apps get with only 5 fields?
Feature usage, conversion funnels, drop-off points, session depth, engagement patterns, platform distribution, and geographic trendsβall the metrics you need to improve your app without tracking individuals across sessions.
Does Respectlytics provide a BAA?
Contact us to discuss your specific requirements at [email protected]. Our data minimization architecture means we store minimal data, but healthcare organizations should consult their legal team about their specific compliance needs.
How does data minimization help with healthcare regulations?
Data minimization means collecting only what you need. By storing just 5 fields with no identifiers, you significantly reduce your data surface area. Less data means less risk and simpler audits. Consult your legal team to determine how this applies to your specific situation.
βοΈ Legal Disclaimer
This information is provided for educational purposes and does not constitute legal advice. Regulations vary by jurisdiction and change over time. Respectlytics does not claim compliance with any specific regulation (HIPAA, GDPR, etc.). Consult your legal team to determine the requirements that apply to your situation.
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