Development of a novel mobile application to detect urine protein for nephrotic syndrome disease monitoring

• Authors: Chia-shi Wang, Emory University; Richard Boyd, Georgia Institute of Technology; Russell Mitchell, Georgia Institute of Technology; W. Darryl Wright, Georgia Institute of Technology; Courtney McCracken, Emory University; Ngoc-Cam Escoffery, Emory University; Rachel Elizabeth Patzer, Emory University; Larry Greenbaum, Emory University
• Journal Title: BMC Medical Informatics and Decision Making
• Volume: Volume 19, Number 1
• Publisher: BMC (part of Springer Nature) | 2019-05-30, Pages 105-105
• Type of Work: Article | Final Publisher PDF
• Publisher DOI: http://doi.org/10.1186/s12911-019-0822-z
• Subjects: Health Sciences, Medicine and Surgery; Engineering, Biomedical
• Keywords: Science & Technology; Life Sciences & Biomedicine; Medical Informatics; Nephrotic syndrome; Mobile applications; Urinalysis; Children; CARE

Abstract

Background: Home monitoring of urine protein is a critical component of disease management in childhood nephrotic syndrome. We describe the development of a novel mobile application, UrApp - Nephrotic Syndrome Manager, to aid disease monitoring. Methods: UrApp was iteratively developed by a panel of two pediatric nephrologists and three research engineers from May 2017 to October 2018 for Apple iPhones. App features were devised by this expert panel to support urine monitoring and other home care tasks. Each feature and user-app interface element was systematically reviewed by the panel and iteratively redesigned to remove anticipated use issues. The app prototype was then refined based on two rounds of usability testing and semi-structured user interviews with a total of 20 caregivers and adolescent patients. The analytic function of UrApp in providing a camera read of the urine test strip was compared to a standard urinalysis machine using 88 patient urine samples and three iPhones, model versions 6S and 7. Exact agreement and weighted kappa were calculated between the UrApp and urinalysis machine reads. Results: The final UrApp features include: camera read of a urine test strip; analysis of urine protein trends and alerts for new disease relapse/remission; transmission of urine protein results to providers; education materials; and medication reminders. During the second round of UrApp usability testing, all users were able to perform each of the functions without error and all perceived UrApp to be helpful and indicated that they would use UrApp. UrApp camera results had 97% exact agreement and an overall weighted kappa value of 0.91 (95% CI, 0.85-0.97) compared with standard urinalysis machine interpretation. Conclusions: UrApp was specifically designed to support patients and families living with nephrotic syndrome by supporting disease monitoring and home management tasks. The technically innovative feature that makes this possible is the use of a smartphone camera to read the urine test strip. This novel tool has the potential to improve disease monitoring and reduce management burden.