ArticleJMIR cardio2024
Impact of an mHealth App (Kencom) on Patients With Untreated Hypertension Initiating Antihypertensive Medications: Real-World Cohort Study.
Article in JMIR cardio, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Identifying and Evaluating Patient-Centered Mobile and Web Apps for Patients With Chronic Spontaneous Urticaria: Systematic Search and Content Analysis.JMIR mHealth and uHealth · 2026Article
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: To prevent the further development of cardiovascular diseases, it is a growing global priority to detect untreated hypertension in patients and ensure adequate blood pressure control via drug therapy. However, few effective tools that facilitate the initiation of antihypertensive medications among such patients have been identified. Objective: We aimed to determine whether a mobile health (mHealth) app facilitates the initiation of antihypertensive medications among patients with untreated hypertension. Methods: We analyzed a large longitudinal integrated database mainly comprised of data from middle-aged, employed people and their families. The database contained data from health checkups, health insurance claims, and the mHealth app kencom. kencom is used to manage daily life logs (eg, weight, number of steps) and to provide health information tailored to customers. Patients with untreated hypertension were identified using the baseline health checkup data, and follow-up health checkups were conducted to identify the rate of initiation of antihypertensive medications between mHealth app users and nonusers. Antihypertensive medication status was confirmed via a questionnaire administered during the medical checkup as well as a review of the health insurance claims database. We conducted a modified Poisson regression analysis, weighted by inverse probability of treatment weighting, to examine the effect of mHealth app usage on the initiation of antihypertensive medications. Additionally, data from four lifestyle questionnaires from the baseline and follow-up health checkups were collected to evaluate lifestyle modifications that could be attributed to the mHealth app. Results: Data were collected from 50,803 eligible patients (mean age 49, SD 9 years; men n=39,412, 77.6%; women n=11,391, 22.4%) with a median follow-up period of 3.0 (IQR 2.3-3.1) years. The rate of initiation of antihypertensive medications was significantly higher in the mHealth app user group than in the nonuser group: 23.4% (3482/14,879) versus 18.5% (6646/35,924; P<.001), respectively. The risk ratio of mHealth app usage for initiated antihypertensive medications was 1.28 (95% CI 1.23-1.33). Among those who did not intend to improve their lifestyle habits such as exercise and diet at baseline, the rate of lifestyle improvement at follow-up was compared between mHealth app users and nonusers, using data from the questionnaires; mHealth app users demonstrated a significantly higher rate of lifestyle changes than nonusers. Conclusions: For patients with untreated hypertension, the use of the mHealth app kencom, which was not dedicated to hypertension treatment, was associated with a higher initiation of antihypertensive medications.
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