Enhancing EHR Systems with data from wearables: An end-to-end Solution for monitoring post-Surgical Symptoms in older adults

TL;DR

This paper presents ROAMM-EHR, an integrated mHealth platform that captures real-time sensor and patient-reported data from smartwatches, enhancing EHR systems for better post-surgical symptom monitoring in older adults.

Contribution

The study introduces a scalable, human-centered platform that seamlessly integrates real-time wearable data into EHR systems, addressing current limitations in dynamic patient monitoring.

Findings

Successful integration of smartwatch data into Epic EHR system

Real-time symptom monitoring enabled for post-surgical patients

Improved potential for timely interventions and care management

Abstract

Mobile health (mHealth) apps have gained popularity over the past decade for patient health monitoring, yet their potential for timely intervention is underutilized due to limited integration with electronic health records (EHR) systems. Current EHR systems lack real-time monitoring capabilities for symptoms, medication adherence, physical and social functions, and community integration. Existing systems typically rely on static, in-clinic measures rather than dynamic, real-time patient data. This highlights the need for automated, scalable, and human-centered platforms to integrate patient-generated health data (PGHD) within EHR. Incorporating PGHD in a user-friendly format can enhance patient symptom surveillance, ultimately improving care management and post-surgical outcomes. To address this barrier, we have developed an mHealth platform, ROAMM-EHR, to capture real-time sensor data and Patient Reported Outcomes (PROs) using a smartwatch. The ROAMM-EHR platform can capture data from a consumer smartwatch, send captured data to a secure server, and display information within the Epic EHR system using a user-friendly interface, thus enabling healthcare providers to monitor post-surgical symptoms effectively.