Validation Parameters of Patient-Generated Data for Digitally Recorded Allergic Rhinitis Symptom and Medication...

Area of Science:

• Allergy and immunology
• Digital health
• Data science

Background:

• Mobile health (mHealth) facilitates allergy monitoring through patient-reported outcomes.
• Ensuring data completeness and accuracy in long-term digital symptom recording is challenging.
• Patient adherence is crucial for the quality of data collected via mHealth tools.

Purpose of the Study:

• To investigate the link between adherence to digital symptom recording and patient-generated scores.
• To identify reliable proxy measures for the quality and accuracy of patient-recorded data.
• To assess the utility of specific parameters in validating data from mobile health allergy apps.

Main Methods:

• 101 children with seasonal allergic rhinitis used the AllergyMonitor app daily.
• Adherence was measured as the percentage of days with recorded data.
• Four parameters (intravariation index, zero values, coefficient of variation, trend changes) were analyzed for three disease indices (RTSS, CSMS, VAS).

Main Results:

• Patient adherence varied, with 64.4% considered highly adherent (>80%).
• Percentage of zero values, coefficient of variation, and intravariation index did not correlate with adherence.
• A higher proportion of trend changes in symptom scores was significantly associated with high adherence.

Conclusions:

• The percentage of trend changes in symptom scores (RTSS, CSMS, VAS) can serve as a proxy for data quality in allergic rhinitis patients.
• Further real-world validation is needed before recommending this parameter for routine use in mHealth allergy management tools.