Using big data analytics to improve HIV medical care utilisation in South Carolina: A study protocol
BMJ Publishing Group, 2019
academicJournal
Zugriff:
INTRODUCTION: Linkage and retention in HIV medical care remains problematic in the USA. Extensive health utilisation data collection through electronic health records (EHR) and claims data represent new opportunities for scientific discovery. Big data science (BDS) is a powerful tool for investigating HIV care utilisation patterns. The South Carolina (SC) office of Revenue and Fiscal Affairs (RFA) data warehouse captures individual-level longitudinal health utilisation data for persons living with HIV (PLWH). The data warehouse includes EHR, claims and data from private institutions, housing, prisons, mental health, Medicare, Medicaid, State Health Plan and the department of health and human services. The purpose of this study is to describe the process for creating a comprehensive database of all SC PLWH, and plans for using BDS to explore, identify, characterise and explain new predictors of missed opportunities for HIV medical care utilisation. METHODS AND ANALYSIS: This project will create person-level profiles guided by the Gelberg-Andersen Behavioral Model and describe new patterns of HIV care utilisation. The population for the comprehensive database comes from statewide HIV surveillance data (2005–2016) for all SC PLWH (N≈18000). Surveillance data are available from the state health department’s enhanced HIV/AIDS Reporting System (e-HARS). Additional data pulls for the e-HARS population will include Ryan White HIV/AIDS Program Service Reports, Health Sciences SC data and Area Health Resource Files. These data will be linked to the RFA data and serve as sources for traditional and vulnerable domain Gelberg-Anderson Behavioral Model variables. The project will use BDS techniques such as machine learning to identify new predictors of HIV care utilisation behaviour among PLWH, and ‘missed opportunities’ for re-engaging them back into care. ETHICS AND DISSEMINATION: The study team applied for data from different sources and submitted individual Institutional Review Board (IRB) applications to the University .
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Using big data analytics to improve HIV medical care utilisation in South Carolina: A study protocol
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Autor/in / Beteiligte Person: | Olatosi, Bankole ; Zhang, Jiajia ; Weissman, Sharon ; Hu, Jianjun ; Haider, Mohammad Rifat ; Li, Xiaoming |
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Veröffentlichung: | BMJ Publishing Group, 2019 |
Medientyp: | academicJournal |
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