Official websites use. Share sensitive information only on official, secure websites. For commercial re-use, please contact journals. Research about mobile health technologies for inflammatory bowel diseases reveals that these devices are mainly used to predict or self-report disease activity. However, in the near future these tools can be used to integrate large data sets into machine learning for the development of personalized treatment algorithms.
This is a special smartphone app for patients to record patient-reported outcomes and a wearable to track physical activity, heart rate, and sleep quality. For data analysis, we used interpretative phenomenological analysis. The analysis of the data revealed 11 themes that were mentioned by at least 3 participants. Patients identified benefits, risks, and potentials for improvement, which should be considered in the further development of the devices and patient-reported outcome scales, and in the implementation of usual care.
The study provides helpful advice for developing and implementing mHealth technologies and adapting patient-reported outcomes to the needs of people with IBD. Incidence rates are increasing in regions such as Asia, South America, and Africa where Western lifestyle habits are being adopted. All these factors influence the risk of disease.
This data can then be used in the future together with data from other sources for the selection of an individual therapy concept. In addition, the measurement of patient-reported outcomes PROs , along with other clinical outcomes, is required for the assessment of therapy response.
A recent review summarized different electronic and mobile applications for patients with IBD and showed that publications about telemonitoring with wearable devices and smartphone apps are still relatively rare.
