JMIR Publications

ABSTRACT

Background:

Patient-reported outcome measures (PROMs) like health-related quality of life (HRQoL) are usually assessed at greater time intervals such as diagnostic time points, after treatment, and during follow-up. Many PROMs require frequent data collection (weekly or daily). Electronic PROMs enable high-resolution tracking but face declining response rates. Integrating PROMs into electronic health records (EHRs) could improve response rates and personalize therapy.

Objective:

This study evaluates the technical and clinical feasibility of high-frequency HRQoL assessments for routine care in EHRs.

Methods:

Patients receive E-Mails on their mobile devices with one-time links to a web-based app called MyEDC. This app communicates with an electronic data capture (EDC) proxy in the demilitarized zone (DMZ) of the hospital. With a polling mechanism, these patient data are transferred to the protected hospital network and uploaded to the EHR system. HRQoL on a visual analog scale (VAS) is assessed over the course of treatment in four clinical use cases: psychosomatics, hematology, visceral surgery and neurosurgery.

Results:

Quality of life trajectories (QoL-T) were collected for 104 patients with daily or weekly data collection between 2 weeks and 3 months. The HRQoL analyses revealed clinically relevant findings across the four different medical domains: In the use case psychosomatics, 36 patients showed a significant increase in HRQoL following four weeks of therapy, rising from a median of 42% to 60% (P=.01). An analysis of 25 patients in hematology demonstrated a significant correlation between HRQoL and QLQ-C30 Global Health Status score (P=.02). For 26 patients in visceral surgery, a significant association was observed between HRQoL and the reported pain level (P<.001). The clinical feasibility was further highlighted in the neurosurgery use case, where 23 patients showed a median response time to the electronic PROM questionnaires of 5.3 hours. HRQoL values were associated with disease-specific symptoms and scores, indicating clinical validity of this readout. Considerable variability of HRQoL was observed over time, both intra-individually and inter-individually. Median area under curve (AUC) of HRQoL ranged from 0.47 to 0.77. Median time to answer ranged from 0.9 to 7.1 hours. No significant association between number of responses and age was observed.

Conclusions:

High-resolution quality of life trajectories with EHR integration are technically and clinically feasible. They offer a novel readout beyond survival analysis or PROM endpoints, enabling precise disease characterization and treatment comparison. Clinical Trial: N/A