Utilizing Big Data analytics and electronic health record data in HIV prevention, treatment, and care research: a literature review

• Published in: AIDS care 2024-05, Vol.36 (5), p.583-603
• Main Authors: Qiao, Shan, Li, Xiaoming, Olatosi, Bankole, Young, Sean D.
• Format: Article
• Language: English
• Subjects: Affordability; Big Data; Big Data analytics; Charges; Communications technology; Computerized medical records; Data analysis; Data science; Digitization; Disease prevention; Electronic health records; Electronic medical records; Epidemics; Health services; HIV; Human immunodeficiency virus; Information technology; Literature reviews; Mathematical analysis; Medical records; prediction model; Prevention; Prevention programs; Preventive medicine
• ISSN: 0954-0121; 1360-0451; 1360-0451
• DOI: 10.1080/09540121.2021.1948499

Propelled by the transformative power of modern information and communication technologies, digitalization of data, and the increasing affordability of high-performance computing, Big Data science has brought forth revolutionary advancement in many areas of business, industry, health, and medicine. The HIV research and care service community is no exception to the benefits from the availability and utilization of Big Data analytics. Electronic health record (EHR) data (e.g., administrative and billing data, electronic medical records, or other digital records of information pertinent to individual or population health) are an essential source of health and disease outcome data because of the large amount of real-world, comprehensive, and often longitudinal data, which provide a good opportunity for leveraging advanced Big Data analytics in addressing challenges in HIV prevention, treatment, and care. This review focuses on studies that apply Big Data analytics to EHR data with aims to synthesize the HIV-related issues that EHR data studies can tackle, identify challenges in the utilization of EHR data in HIV research and practice, and discuss future needs and directions that can realize the promising potential role of Big Data in ending the HIV epidemic.