Co-Design, Development, and Evaluation of a Health Monitoring Tool Using Smartwatch Data: A Proof-of-Concept Study

Ruhi Kiran Bajaj (), Rebecca Mary Meiring and Fernando Beltran
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Ruhi Kiran Bajaj: Department of Information Systems and Operations Management (ISOM), The University of Auckland, Auckland 1010, New Zealand
Rebecca Mary Meiring: Department of Exercise Sciences, The University of Auckland, Auckland 1023, New Zealand
Fernando Beltran: Department of Information Systems and Operations Management (ISOM), The University of Auckland, Auckland 1010, New Zealand

Future Internet, 2023, vol. 15, issue 3, 1-15

Abstract: Computational analysis and integration of smartwatch data with Electronic Medical Records (EMR) present potential uses in preventing, diagnosing, and managing chronic diseases. One of the key requirements for the successful clinical application of smartwatch data is understanding healthcare professional (HCP) perspectives on whether these devices can play a role in preventive care. Gaining insights from the vast amount of smartwatch data is a challenge for HCPs, thus tools are needed to support HCPs when integrating personalized health monitoring devices with EMR. This study aimed to develop and evaluate an application prototype, co-designed with HCPs and employing design science research methodology and diffusion of innovation frameworks to identify the potential for clinical integration. A machine learning algorithm was developed to detect possible health anomalies in smartwatch data, and these were presented visually to HCPs in a web-based platform. HCPs completed a usability questionnaire to evaluate the prototype, and over 60% of HCPs scored positively on usability. This preliminary study tested the proposed research to solve the practical challenges of HCP in interpreting smartwatch data before fully integrating smartwatches into the EMR. The findings provide design directions for future applications that use smartwatch data to improve clinical decision-making and reduce HCP workloads.

Keywords: Electronic Medical Record (EMR); smartwatch; machine learning; anomaly detection; health monitoring; co-design; design science; diffusion of innovation (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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