Real-world HIV diagnostic testing patterns in the United States

• Published in: The American journal of managed care Vol. 28; no. 2; pp. e42 - e48
• Main Authors: Burudpakdee, Chakkarin, Near, Aimee M, Tse, Jenny, Faccone, Jillian, Rodriguez, Pedro L, Karichu, James K, Cheng, Mindy M
• Format: Journal Article
• Language: English
• Published: United States MultiMedia Healthcare Inc 01.02.2022
• Subjects: Adult; Algorithms; Antibodies; Demographics; Diagnostic Techniques and Procedures; Diagnostic tests; Efficiency; Female; HIV Antibodies; HIV Infections - diagnosis; HIV-1 - genetics; Humans; Immunoassay; Immunoassay - methods; Male; Medical diagnosis; Medical laboratories; Medical tests; Patients; Public health; Retrospective Studies; Sensitivity and Specificity; United States; United States; United States > US
• ISSN: 1088-0224; 1936-2692; 1936-2692
• DOI: 10.37765/ajmc.2022.88826

To understand real-world implementation of the updated CDC HIV diagnostic testing algorithm. Retrospective database analysis. Using data from Quest Diagnostics, we identified patients with at least 1 HIV-1/HIV-2 antibody differentiation test (BioRad Geenius HIV 1/2 Supplemental Assay [Geenius]) between January 1 and December 31, 2017. Study measures included Health Insurance Portability and Accountability Act-compliant patient demographics, test results, test frequency, and sequence relative to the CDC HIV diagnostic algorithm, including HIV-1 RNA Qualitative Assay (Aptima) or HIV-2 nucleic acid test (NAT). A total of 26,319 patients were identified (mean [SD] age, 40.7 [14.3] years; 66.4% male), with 28,954 Geenius tests, 7234 Aptima tests, and 298 HIV-2 NATs. In 26.4% of test sequences, the Geenius results were indeterminate or negative and required subsequent confirmatory NATs. A total of 8.5% of patients had more than 1 Geenius test in 2017, and 11.2% of the time, results of the first and second tests differed. A total of 74.2% of test sequences matched the CDC-recommended algorithm. Our study findings suggest that the CDC HIV diagnostic algorithm is complex and may pose suboptimal testing efficiency. Opportunities to improve diagnostic efficiency by reducing indeterminate results and repeat tests are warranted.