Factors Influencing Sustained Engagement with ECG Self-Monitoring: Perspectives from Patients and Health Care Providers

Meghan Reading; Dawon Baik; Melissa Beauchemin; Kathleen T. Hickey; Jacqueline A. Merrill

doi:10.1055/s-0038-1672138

Applied Clinical Informatics, Table of Contents

Appl Clin Inform 2018; 09(04): 772-781
DOI: 10.1055/s-0038-1672138

Research Article

Georg Thieme Verlag KG Stuttgart · New York

Factors Influencing Sustained Engagement with ECG Self-Monitoring: Perspectives from Patients and Health Care Providers

Meghan Reading

¹Division of Health Informatics, Department of Healthcare Policy and Research, Weill Cornell Medicine, Cornell University, New York, New York, United States

,

Dawon Baik

²School of Nursing, Columbia University, New York, New York, United States

,

Melissa Beauchemin

²School of Nursing, Columbia University, New York, New York, United States

,

Kathleen T. Hickey

²School of Nursing, Columbia University, New York, New York, United States

,

Jacqueline A. Merrill

²School of Nursing, Columbia University, New York, New York, United States

³Department of Biomedical Informatics, Columbia University, New York, New York, United States

› Author Affiliations

Abstract

Background Patient-generated health data (PGHD) collected digitally with mobile health (mHealth) technology has garnered recent excitement for its potential to improve precision management of chronic conditions such as atrial fibrillation (AF), a common cardiac arrhythmia. However, sustained engagement is a major barrier to collection of PGHD. Little is known about barriers to sustained engagement or strategies to intervene upon engagement through application design.

Objective This article investigates individual patient differences in sustained engagement among individuals with a history of AF who are self-monitoring using mHealth technology.

Methods This qualitative study involved patients, health care providers, and research coordinators previously involved in a randomized, controlled trial involving electrocardiogram (ECG) self-monitoring of AF. Patients were adults with a history of AF randomized to the intervention arm of this trial who self-monitored using ECG mHealth technology for 6 months. Semistructured interviews and focus groups were conducted separately with health care providers and research coordinators, engaged patients, and unengaged patients. A validated model of sustained engagement, an adapted unified theory of acceptance and use of technology (UTAUT), guided data collection, and analysis through directed content analysis.

Results We interviewed 13 patients (7 engaged, 6 unengaged), 6 providers, and 2 research coordinators. In addition to finding differences between engaged and unengaged patients within each predictor in the adapted UTAUT model (perceived ease of use, perceived usefulness, facilitating conditions), four additional factors were identified as being related to sustained engagement in this population. These are: (1) internal motivation to manage health, (2) relationship with health care provider, (3) supportive environments, and (4) feedback and guidance.

Conclusion Although it required some modification, the adapted UTAUT model was useful in understanding of the parameters of sustained engagement. The findings of this study provide initial requirement specifications for the design of applications that engage patients in this unique population of adults with AF.

Keywords

patient engagement - patient-provider communication - workflows and human interactions - smart phone - mobile platforms - general information systems and technologies in clinics - consumer health informatics

Full Text

References

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Supplementary Material

Supplementary Material