Abstract
Abstract
Introduction and hypothesis
Patients with recurrent urinary tract infection (rUTI) have limited knowledge of preventive strategies to lower the risk of UTI. We aimed to develop and test the feasibility of an eHealth system for women with rUTI, named myRUTIcoach, and explored the facilitators and barriers related to its adoption.
Methods
We developed myRUTIcoach in a structured iterative process and tested its feasibility among 25 women with rUTI over 2 months. Subsequent questionnaires covered satisfaction, accessibility, and experiences with myRUTIcoach. A random selection of participants and relevant stakeholders took part in semi-structured interviews to explore adoption. Data were analyzed and elaborated using inductive and deductive approaches using the Non-adoption, Abandonment, Spread, Scale-up, and Sustainability (NASSS) framework.
Results
MyRUTIcoach was not only widely accepted but also facilitated communication with health care professionals (HCPs) and contributed to greater knowledge of rUTI. Women graded the system a mean of 8.0 (±0.6) out of 10, with 89% stating that they would recommend it to others. Patients indicated that self-management skills were the major facilitators and barriers related to adoption, whereas HCPs stated that the disconnect between myRUTIcoach and electronic health care records (EHRs) was the major barrier.
Conclusions
This research describes the development and testing of myRUTIcoach for women with rUTI. Patients and HCPs reported high satisfaction and compliance with myRUTIcoach. However, adoption by the intended users is complex and influenced by all examined domains of the NASSS framework. We have already improved linkage to EHRs, but further optimization to meet patient needs may improve the effectiveness of this self-management tool for rUTI.
Publisher
Springer Science and Business Media LLC
Subject
Urology,Obstetrics and Gynecology
Cited by
1 articles.
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1. Intelligent Medication System Based on Internet of Things;2024 IEEE 3rd International Conference on Electrical Engineering, Big Data and Algorithms (EEBDA);2024-02-27