Objective:

To determine the feasibility of a mobile app for clinical stroke education and detection by patients.

Background:

Stroke is a leading cause of severe disability in the US. There is no effective method for patients to accurately detect the signs of stroke without the assistance of a medical provider. At-home stroke monitoring could address deficiencies in pre-hospital stroke detection by patients. We developed a mobile app, Destroke, that allows performance of a modified NIH stroke scale (NIHSS) by patients.

Design/Methods:

We conducted a prospective open-label study to evaluate the feasibility of the Destroke app in patients with stroke. We enrolled twenty-five patients with stroke, and nineteen patients completed all study assessments. We designed a modified NIHSS that assessed twelve out of sixteen tasks on the NIHSS, with visual fields, dysarthria, ataxia, and neglect excluded. Patients completed this test eight times over a 28-day period, and surveys were performed to assess patient satisfaction on app usage and confidence in stroke detection.

Results:

Ten men and nine women participated in this study with a median age of 64 (33-76), representing ten US states and Washington D.C. Fifteen patients reported using health apps. On a 5-point Likert scale, patients rated the app as 4.2 on being able to understand and use the app and 4.3 on using the app when instructed by their doctor. For eight patients with poor confidence in detecting the signs of a stroke before the study, six of them showed higher confidence after the study.

Conclusions:

Use of an at-home stroke monitoring app is feasible by patients with stroke and results in greater confidence in detecting the signs of stroke. Further research is needed to determine the long-term effects of stroke monitoring app usage on patients’ awareness of stroke signs and the effects of this app on pre-hospital stroke detection and treatment outcomes.