Developing remote patient monitoring infrastructure using commercially available cloud platforms

Minh Cao; Ramin Ramezani; Vivek Kumar Katakwar; Wenhao Zhang; Dheeraj Boda; Muneeb Wani; Arash Naeim

doi:10.3389/fdgth.2024.1399461

Developing remote patient monitoring infrastructure using commercially available cloud platforms

Front Digit Health. 2024 Nov 6:6:1399461. doi: 10.3389/fdgth.2024.1399461. eCollection 2024.

Authors

Minh Cao¹, Ramin Ramezani¹, Vivek Kumar Katakwar², Wenhao Zhang¹, Dheeraj Boda², Muneeb Wani², Arash Naeim³

Affiliations

¹ Center for Smart Health, University of California Los Angeles, Los Angeles, CA, United States.
² UCLA Health Information Technology, University of California Los Angeles, Los Angeles, CA, United States.
³ David Geffen UCLA School of Medicine, University of California Los Angeles, Los Angeles, CA, United States.

Abstract

Wearable sensor devices for continuous patient monitoring produce a large volume of data, necessitating scalable infrastructures for efficient data processing, management and security, especially concerning Patient Health Information (PHI). Adherence to the Health Insurance Portability and Accountability Act (HIPAA), a legislation that mandates developers and healthcare providers to uphold a set of standards for safeguarding patients' health information and privacy, further complicates the development of remote patient monitoring within healthcare ecosystems. This paper presents an Internet of Things (IoT) architecture designed for the healthcare sector, utilizing commercial cloud platforms like Microsoft Azure and Amazon Web Services (AWS) to develop HIPAA-compliant health monitoring systems. By leveraging cloud functionalities such as scalability, security, and load balancing, the architecture simplifies the creation of infrastructures adhering to HIPAA standards. The study includes a cost analysis of Azure and AWS infrastructures and evaluates data processing speeds and database query latencies, offering insights into their performance for healthcare applications.

Keywords: AI; big data analytics; cloud computing; healthcare; internet of things (IoT); remote patient monitoring; wireless sensor networks.

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. Center for Smart Health, University of California, Los Angeles.