Curating a knowledge base for individuals with coinfection of HIV and SARS-CoV-2: a study protocol of EHR-based data mining and clinical implementation

• Published in: BMJ open Vol. 12; no. 9; p. e067204
• Main Authors: Liang, Chen, Weissman, Sharon, Olatosi, Bankole, Poon, Eric G, Yarrington, Michael E, Li, Xiaoming
• Format: Journal Article
• Language: English
• Published: England British Medical Journal Publishing Group 13.09.2022; BMJ Publishing Group LTD; BMJ Publishing Group
• Series: Protocol
• Subjects: Clinical decision making; Clinical outcomes; Coinfection - epidemiology; Coronaviruses; COVID-19; COVID-19 - epidemiology; COVID-19 vaccines; Data Mining; Demographics; Disease prevention; Drug therapy; Electronic Health Records; Health informatics; HIV; HIV & AIDS; HIV Infections - complications; HIV Infections - epidemiology; Human immunodeficiency virus; Humans; Immunization; Infections; Infectious Diseases; Knowledge Bases; Laboratories; Machine learning; Medical prognosis; Risk factors; SARS-CoV-2; Semantics; Severe acute respiratory syndrome coronavirus 2; Usability; COVID-19; HIV & AIDS; Health informatics
• ISSN: 2044-6055; 2044-6055
• DOI: 10.1136/bmjopen-2022-067204

IntroductionDespite a higher risk of severe COVID-19 disease in individuals with HIV, the interactions between SARS-CoV-2 and HIV infections remain unclear. To delineate these interactions, multicentre Electronic Health Records (EHR) hold existing promise to provide full-spectrum and longitudinal clinical data, demographics and sociobehavioural data at individual level. Presently, a comprehensive EHR-based cohort for the HIV/SARS-CoV-2 coinfection has not been established; EHR integration and data mining methods tailored for studying the coinfection are urgently needed yet remain underdeveloped.Methods and analysisThe overarching goal of this exploratory/developmental study is to establish an EHR-based cohort for individuals with HIV/SARS-CoV-2 coinfection and perform large-scale EHR-based data mining to examine the interactions between HIV and SARS-CoV-2 infections and systematically identify and validate factors contributing to the severe clinical course of the coinfection. We will use a nationwide EHR database in the USA, namely, National COVID Cohort Collaborative (N3C). Ultimately, collected clinical evidence will be implemented and used to pilot test a clinical decision support prototype to assist providers in screening and referral of at-risk patients in real-world clinics.Ethics and disseminationThe study was approved by the institutional review boards at the University of South Carolina (Pro00121828) as non-human subject study. Study findings will be presented at academic conferences and published in peer-reviewed journals. This study will disseminate urgently needed clinical evidence for guiding clinical practice for individuals with the coinfection at Prisma Health, a healthcare system in collaboration.