Saudi Arabia is among the countries that have very high prevalence rates of diabetes and hypertension, with prevalence rates of almost 18% and 25%, respectively. The majority of patients with diabetes and hypertension fail to manage their diseases and to show up for their follow up appointments. Mhealth technology is among the interventions that have been recently adopted to overcome these issues and improve the quality of healthcare services. This study aims to evaluate the effectiveness of a mobile phone application named diabetes and hypertension application (DHA Tracking) to promote adherence for patients with diabetes and hypertension in Mecca, Saudi Arabia. The proposed intervention was designed to promote adherence via two features, namely, refill medication reminder (RMR) and doctor appointment reminder (DAR). The third feature, which is managing the number of unnecessary visits, was covered by the cumulative blood sugar test (Hemoglobin A1c) for patients with their doctors. The study examined the difference in adherence level before the intervention and after the intervention with samples of n = 199 and n = 165 for diabetes and hypertension, respectively. The mhealth intervention was found to have significant effects on both the refill medication reminder and the doctor's appointment reminder. Also, it was found that the intervention was efficient in reducing the number of unnecessary follow-up visits to around 20%. This study supports the evidence in the literature on the effectiveness of mhealth in promoting adherence to medication for patients with chronic diseases in the developing countries and specifically in Saudi Arabia. Positive social change that may result from this study is for better management of chronic disease symptoms and increase the awareness of using mhealth applications. This would improve the quality of life for patients, their families, and the community.
Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd2020-1073 |
Date | 01 January 2020 |
Creators | Khan, Nawaf |
Publisher | STARS |
Source Sets | University of Central Florida |
Language | English |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Electronic Theses and Dissertations, 2020- |
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