Improving Medication Adherence Through Adaptive Digital Interventions (iMedA) in Patients With Hypertension: Protocol for an Interrupted Time Series Study

Kobra Etminani, Carina Göransson, Alexander Galozy, Margaretha Norell Pejner, Sławomir Nowaczyk, Kobra Etminani, Carina Göransson, Alexander Galozy, Margaretha Norell Pejner, Sławomir Nowaczyk

Abstract

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://ichgcp.net/clinical-trials-registry/NCT04413500.

International registered report identifier (irrid): DERR1-10.2196/24494.

Keywords: artificial intelligence; digital intervention; hypertension; mHealth; medication adherence.

Conflict of interest statement

Conflicts of Interest: None declared.

©Kobra Etminani, Carina Göransson, Alexander Galozy, Margaretha Norell Pejner, Sławomir Nowaczyk. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 12.05.2021.

Figures

Figure 1
Figure 1
Conceptual model of just-in-time adaptive intervention components.
Figure 2
Figure 2
An illustration of the preintervention step (ie, the first 14 days). HL: health literacy; MUAH-16: 16-item Maastricht Utrecht Adherence in Hypertension; QoL: quality of life.
Figure 3
Figure 3
An illustration of the intervention phase. PA: physical activity; RL: reinforcement learning; RP: random policy.

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