Researchers from the University of South Carolina Arnold School of Public Health, School of Medicine and College of Engineering and Computing have published a paper that provides a study protocol for using big data analytics to improve human immunodeficienty virus (HIV) medical care utilization in South Carolina. The project was led by health services policy and management clinical associate professor, Dr. Bankole Olatosi and health promotion, education, and behavior professor, Dr. Xiaoming Li and published in BMJ Open.
With this study, the authors described the process for creating a comprehensive database of information collected from private institutions, housing, prisons, mental health, Medicare, Medicaid, State Health Plan, and the department of health and human services about people living with HIV in South Carolina between 2005 and 2016. The purpose of creating such a database is the ability to use big data to better understand HIV incidence rates, healthcare access, etc.
“Linkage and retention in HIV medical care remains problematic in the United States,” Dr. Olatosi says. “Extensive health utilization data collection through electronic health records and claims data represent new opportunities for scientific discovery, and big data science is a powerful tool for investigating HIV care utilization patterns.”
This project offers a roadmap for creating person-level profiles and describes new patterns of HIV care utilization. The data includes information from 18,000 people living with HIV/AIDS (human immunodeficiency virus/acquired immune deficiency syndrome) and surveillance data from the state health department’s HIV/AIDS Reporting system. The project uses big data science techniques (e.g., machine learning) to identify new predictors of HIV utilization behavior and missed opportunities for re-engaging them back into care.Tags: Friday Letter Submission, Publish on February 14