Stability monitoring of patients  with myasthenia gravis using a  mobile-based application

Emad Alaei Tafti; Marjan Ghazisaeedi; Payam Sarraf

doi:10.18502/cjn.v22i1.12615

Emad Alaei Tafti Department of Health Information Technology, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran
Marjan Ghazisaeedi Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran
Payam Sarraf Iranian Center of Neurological Research, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran

DOI: https://doi.org/10.18502/cjn.v22i1.12615

Keywords: Medical Informatics Applications; Monitoring; Myasthenia Gravis; Mobile Health; Mobile Applications; Neuromuscular Junction Diseases

Abstract

Background: Failure in early diagnosis of myasthenia gravis (MG) and the risks of taking certain medications and undergoing surgery and anesthesia can lead to severe respiratory disorders and death. However, there are therapeutic measures that significantly control the disease and improve individual’s functionality.

Methods: First, an expert panel was formed, and a needs assessment questionnaire was prepared for the information elements and the capabilities required for the application and provided to neurologists with a subspecialty fellowship in neuromuscular diseases. Then, based on the analyzed results, the application was designed and created in 2 versions (physician and patient), and in 2 languages (Persian and English). Eventually, a questionnaire for user interaction and satisfaction was provided to 5 relevant physicians to evaluate the application.

Results: The results showed that neurologists considered all items of the needs assessment questionnaire to be 100% essential. The capabilities of the application included registering the medication name and dose, recording symptoms and complaints by the patient, completing standard questionnaires, online chat, medication reminder, sending alerts to the doctor when the patient is unwell, and providing a variety of reports. The usability evaluation showed that neurologists evaluated the application at a good level with the average score of 8.23 ± 0.47 (out of 9 points).

Conclusion: In the long run, using this technology can reduce costs, improve patients’ quality of life (QOL) and health care, change health behaviors, and ultimately, improve individual’s health.