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Improving Medication Adherence Through Adaptive Digital Interventions (iMedA) in Patients With Hypertension: Protocol for an Interrupted Time Series Study
Center for Applied Intelligent Systems Research, Halmstad University, Halmstad, Sweden .ORCID iD: 0000-0003-2006-6229
Center for Research on Welfare, Health and Sport, Halmstad University, Halmstad, Sweden .ORCID iD: 0000-0001-6215-2032
Center for Applied Intelligent Systems Research, Halmstad University, Halmstad, Sweden .ORCID iD: 0000-0002-7453-9186
Center for Research on Welfare, Health and Sport, Halmstad University, Halmstad, Sweden; Hemvårdsförvaltningen, Halmstad, Sweden .ORCID iD: 0000-0002-1174-2523
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2021 (English)In: JMIR Research Protocols, E-ISSN 1929-0748, Vol. 10, no 5, article id e24494Article in journal (Refereed) Published
Abstract [en]

Background: There is a strong need to improve medication adherence (MA) for individuals with hypertension in order to reduce long-term hospitalization costs. We believe this can be achieved through an artificial intelligence agent that helps the patient in understanding key individual adherence risk factors and designing an appropriate intervention plan. The incidence of hypertension in Sweden is estimated at approximately 27%. Although blood pressure control has increased in Sweden, barely half of the treated patients achieved adequate blood pressure levels. It is a major risk factor for coronary heart disease and stroke as well as heart failure. MA is a key factor for good clinical outcomes in persons with hypertension.

Objective: The overall aim of this study is to design, develop, test, and evaluate an adaptive digital intervention called iMedA, delivered via a mobile app to improve MA, self-care management, and blood pressure control for persons with hypertension.

Methods: The study design is an interrupted time series. We will collect data on a daily basis, 14 days before, during 6 months of delivering digital interventions through the mobile app, and 14 days after. The effect will be analyzed using segmented regression analysis. The participants will be recruited in Region Halland, Sweden. The design of the digital interventions follows the just-in-time adaptive intervention framework. The primary (distal) outcome is MA, and the secondary outcome is blood pressure. The design of the digital intervention is developed based on a needs assessment process including a systematic review, focus group interviews, and a pilot study, before conducting the longitudinal interrupted time series study.

Results: The focus groups of persons with hypertension have been conducted to perform the needs assessment in a Swedish context. The design and development of digital interventions are in progress, and the interventions are planned to be ready in November 2020. Then, the 2-week pilot study for usability evaluation will start, and the interrupted time series study, which we plan to start in February 2021, will follow it.

Conclusions: We hypothesize that iMedA will improve medication adherence and self-care management. This study could illustrate how self-care management tools can be an additional (digital) treatment support to a clinical one without increasing burden on health care staff.

Trial Registration: ClinicalTrials.gov NCT04413500; https://clinicaltrials.gov/ct2/show/NCT04413500

Place, publisher, year, edition, pages
JMIR Publications, 2021. Vol. 10, no 5, article id e24494
Keywords [en]
Artificial intelligence, Digital intervention, Hypertension, Medication adherence, MHealth
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Nursing
Identifiers
URN: urn:nbn:se:oru:diva-110594DOI: 10.2196/24494ISI: 000658257400006Scopus ID: 2-s2.0-85106034833OAI: oai:DiVA.org:oru-110594DiVA, id: diva2:1824771
Funder
Vinnova, 2017-04617Available from: 2024-01-08 Created: 2024-01-08 Last updated: 2024-01-17Bibliographically approved

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Pejner, Margaretha Norell

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Etminani, KobraGöransson, CarinaGalozy, AlexanderPejner, Margaretha NorellNowaczyk, Sławomir
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