BPcontrol. A Mobile App to Monitor Hypertensive Patients

Appl Clin Inform. 2016 Dec 7;7(4):1120-1134. doi: 10.4338/ACI-2015-12-RA-0172.

Abstract

Background: Hypertension or high blood pressure is on the rise. Not only does it affect the elderly but is also increasingly spreading to younger sectors of the population. Treating this condition involves exhaustive monitoring of patients. The current mobile health services can be improved to perform this task more effectively.

Objective: To develop a useful, user-friendly, robust and efficient app, to monitor hypertensive patients and adapted to the particular requirements of hypertension.

Methods: This work presents BPcontrol, an Android and iOS app that allows hypertensive patients to communicate with their health-care centers, thus facilitating monitoring and diagnosis. Usability, robustness and efficiency factors for BPcontrol were evaluated for different devices and operating systems (Android, iOS and system-aware). Furthermore, its features were compared with other similar apps in the literature.

Results: BPcontrol is robust and user-friendly. The respective start-up efficiency of the Android and iOS versions of BPcontrol were 2.4 and 8.8 times faster than a system-aware app. Similar values were obtained for the communication efficiency (7.25 and 11.75 times faster for the Android and iOS respectively). When comparing plotting performance, BPcontrol was on average 2.25 times faster in the Android case. Most of the apps in the literature have no communication with a server, thus making it impossible to compare their performance with BPcontrol.

Conclusions: Its optimal design and the good behavior of its facilities make BPcontrol a very promising mobile app for monitoring hypertensive patients.

Keywords: Hypertension; remote monitoring; telemedicine and telehealth.

MeSH terms

  • Algorithms
  • Blood Pressure
  • Humans
  • Hypertension / diagnosis*
  • Hypertension / physiopathology
  • Mobile Applications*
  • Monitoring, Physiologic / methods*
  • Monitoring, Physiologic / statistics & numerical data
  • Telemedicine / methods*
  • Telemedicine / statistics & numerical data
  • User-Computer Interface

Grants and funding

Funding: This work was supported by the Ministerio de Economía y Competitividad under contract TIN2014–53234-C2–2-R. The authors are members of the research group 2014-SGR163, funded by the Generalitat de Catalunya. Besides, this research is partly supported by the European Union FEDER (CAPAP-H5 network TIN2014–53522-REDT).