Clinical decision support systems to guide healthcare providers on HIV testing

AIDS. 2022 Jul 1;36(8):1083-1093. doi: 10.1097/QAD.0000000000003211. Epub 2022 Mar 4.

Abstract

Objective: To understand the impact of clinical decision support systems (CDSSs) on improving HIV testing and diagnosis.

Design: An original global systematic review (PROSPERO Number: CRD42020175576) of peer-reviewed articles reporting on electronic CDSSs that generate triggers encouraging healthcare providers to perform an HIV test.

Methods: Medline, Embase, Cochrane CENTRAL and CINAHL EBSCOhost were searched up to 17 November 2020 and reference lists of included articles were checked. Qualitative and quantitative syntheses (using meta-analyses) of identified studies were performed.

Results: The search identified 1424 records. Twenty-two articles met inclusion criteria (19 of 22 non-HIV endemic settings); 18 clinical and four laboratory-driven reminders. Reminders promoted 'universal' HIV testing for all patients without a known HIV infection and no recent documented HIV test, or 'targeted' HIV testing in patients with clinical risk-factors or specific diagnostic tests. CDSSs increased HIV testing in hospital and nonhospital setting, with the pooled risk-ratio amongst studies reporting comparable outcome measures in hospital settings (n = 3) of 2.57 [95% confidence interval (CI) 1.53-4.33, random-effect model] and in nonhospital settings (n = 4) of 2.13 (95% CI 1.78-4.14, random effect model). Results of the clinical impact of CDSSs on HIV diagnosis were mixed.

Conclusion: CDSSs improve HIV testing and may, potentially, improve diagnosis. The data support the broader study of CDSSs in low- and high prevalent HIV settings to determine their precise impact on UNAIDS goals to reach universal HIV testing and treatment coverage.

Publication types

  • Meta-Analysis
  • Systematic Review
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Decision Support Systems, Clinical*
  • HIV Infections* / diagnosis
  • HIV Testing*
  • Health Personnel
  • Humans
  • Outcome Assessment, Health Care