Tracking Post-Injury Recovery to Improve Clinical Research Outcomes

This leading academic medical center in New York City is dedicated to world-class research and patient care. The institute frequently conducts exploratory studies to modernize treatment plans and improve the quality of life for patients with complex neurological conditions.

Collecting consistent data during the critical first month of recovery presented several logistical challenges:

• Manual Data Gaps: Traditional methods relied on patient recall, which is often unreliable following a head injury (concussion).
• Remote Monitoring Hurdles: Measuring physical metrics like balance and heart rate outside of a controlled clinical environment was difficult.
• Participant Enrollment: Enrolling and retaining participants in a month-long study required a frictionless, user-friendly interface.
• Data Fragmentation: Consolidating physical activity, cognitive performance, and physiological data into a single research-ready stream.

We engineered a comprehensive solution using Swift that bridges the gap between the patient’s home and the research lab. The application serves as a daily recovery companion, utilizing the sensors in the iPhone and Apple Watch to record symptoms such as blurred vision, drowsiness, and heart rate variability.

The technical implementation focused on data integrity and ease of use.

• ResearchKit Integration: Utilized the Apple ResearchKit framework to build standardized cognitive tests (concentration tasks) and physical assessments (walking tests).
• Apple Watch Synchronization: Integrated the watch to capture real-time heart rate data, providing deeper physiological context to the patient-reported symptoms.
• Secure Backend Connectivity: Integrated with Sage Bionetworks' Bridge Service for secure data storage and de-identified transmission of research data.
• Location & Movement Tracking: Used Location Services and iPhone motion sensors to determine distance traveled and speed during daily walking tests.

• Dynamic Screening: An automated questionnaire to verify medical condition, age, and diagnosis before study enrollment.
• Daily Recovery Tasks: Guided walking tests with prompts to maintain speed and interactive concentration tests to measure cognitive lag.
• Symptom Tracker: Daily/weekly surveys to record subjective feelings like balance issues and drowsiness.
• Physician Dashboard: An option for patients to share a graphical representation of their progress directly with their healthcare provider.
• Activity Reminders: Automated push notifications to ensure high compliance with daily surveys and physical tasks.
• CryptoSwift Integration: Ensured high-level encryption of sensitive health data before transmission.

• Simplified Enrollment: Considerably lowered the barrier for entry, allowing the institute to engage a much larger and more diverse group of research participants.
• Accurate Treatment Plans: High-fidelity data from ResearchKit led to a more nuanced understanding of the recovery phase, resulting in better-tailored treatment protocols.
• Reduced Operational Effort: Remote monitoring eliminated the need for frequent in-person check-ups, saving significant time for the medical research team.
• Predictive Insights: The volume and accuracy of collected data helped the medical team predict long-term outcomes for patients with concussions with greater precision.
• Enhanced Patient Engagement: The mobile-first approach kept participants active in their own recovery, providing them with visual feedback on their healing journey.