通过适应性数字干预改善高血压患者的药物依从性（iMedA）：一项中断时间序列研究的方案

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

作者信息

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

机构信息

Center for Applied Intelligent Systems Research, Halmstad University, Halmstad, Sweden.

Center for Research on Welfare, Health and Sport, Halmstad University, Halmstad, Sweden.

出版信息

JMIR Res Protoc. 2021 May 12;10(5):e24494. doi: 10.2196/24494.

DOI:10.2196/24494

PMID:33978593

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8156113/

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://clinicaltrials.gov/ct2/show/NCT04413500.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/24494.

摘要

背景

为降低长期住院成本，迫切需要提高高血压患者的用药依从性（MA）。我们认为，这可以通过一个人工智能代理来实现，该代理可帮助患者了解关键的个体依从性风险因素并设计适当的干预计划。瑞典高血压的发病率估计约为27%。尽管瑞典的血压控制有所改善，但接受治疗的患者中只有不到一半达到了足够的血压水平。高血压是冠心病、中风以及心力衰竭的主要危险因素。用药依从性是高血压患者取得良好临床疗效的关键因素。

目的

本研究的总体目标是设计、开发、测试和评估一种名为iMedA的适应性数字干预措施，通过移动应用程序提供该干预措施，以提高高血压患者的用药依从性、自我护理管理能力和血压控制水平。

方法

本研究设计为中断时间序列研究。我们将在通过移动应用程序提供数字干预措施前14天、提供干预措施的6个月期间以及干预措施结束后14天，每天收集数据。将使用分段回归分析来分析效果。研究参与者将在瑞典哈兰省招募。数字干预措施的设计遵循即时自适应干预框架。主要（远端）结局指标是用药依从性，次要结局指标是血压。在进行纵向中断时间序列研究之前，基于包括系统评价、焦点小组访谈和一项试点研究在内的需求评估过程，开展数字干预措施的设计。