Clinicians' Perspectives in Using Patient-Generated Health Data to Improve Ischemic Heart Disease Management

Khuder Alaboud; Maniza Shahreen; Humayera Islam; Tanmoy Paul; Md Kamruz Zaman Rana; Anissa Morrison; Arun Kumar; Abu Saleh Mohammad Mosa

Clinicians' Perspectives in Using Patient-Generated Health Data to Improve Ischemic Heart Disease Management

AMIA Jt Summits Transl Sci Proc. 2022 May 23:2022:112-119. eCollection 2022.

Authors

Khuder Alaboud^{1

2}, Maniza Shahreen³, Humayera Islam^{1

2}, Tanmoy Paul^{2

4}, Md Kamruz Zaman Rana^{2

3}, Anissa Morrison^{2

5}, Arun Kumar⁶, Abu Saleh Mohammad Mosa^{1

2

3

4

7}

Affiliations

¹ Institute for Data Science and Informatics (IDSI).
² NextGen Biomedical Informatics Center.
³ Department of Health Management and Informatics (HMI).
⁴ Department of Electrical Engineering and Computer Science.
⁵ University of California, Santa Barbara, CA, USA.
⁶ Division of Cardiovascular Medicine, University of Missouri, Columbia, MO, USA.
⁷ Correspondent Author.

PMID: 35854732
PMCID: PMC9285148

Abstract

Patients suffering from ischemic heart disease (IHD) should be monitored closely after being discharged. With recent advances in digital health tools, collecting, using, and sharing patient-generated health data (PGHD) has become more achievable. PGHD can complement the existing clinical data and provide a comprehensive picture of the patient's health status. Despite the potential value of PGHD in healthcare, its implementation currently remains limited due to the clinicians' concern with the reliability and accuracy of the gathered data to support decision-making and concerns regarding the added workload that PGHD might cause to clinical workflow. The main objective of the study was to investigate the clinicians' perspectives towards the use of PGHD for IHD management, focusing on data sharing, interpretation, and efficiency in decision-making. The study consists of semi-structured interviews with seven clinicians. Study results identified four main themes: data generation, data integration, data presentation, data interpretation and utilization in clinical decision-making.