2021
DOI: 10.1007/s11904-021-00552-3
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Machine Learning and Clinical Informatics for Improving HIV Care Continuum Outcomes

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Cited by 22 publications
(11 citation statements)
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“…The impacts of early COVID-19 disruptions on ART adherence also varied across studies. It was widely expected that COVID-19 would interrupt access to ART with adverse effects on adherence, particularly given ubiquitous disruptions to accessing care, pharmacies, and the impacts on factors known to influence adherence, such as stress and substance use [72]. Globally, an estimated one in five PLWH were unable to access their HIV care provider, and close to half of PLWH were unable to access ART refills remotely, with the least access occurring in Belarus, Brazil, Kazakhstan, Mexico, and Russia [73].…”
Section: Access To Health Servicesmentioning
confidence: 99%
“…The impacts of early COVID-19 disruptions on ART adherence also varied across studies. It was widely expected that COVID-19 would interrupt access to ART with adverse effects on adherence, particularly given ubiquitous disruptions to accessing care, pharmacies, and the impacts on factors known to influence adherence, such as stress and substance use [72]. Globally, an estimated one in five PLWH were unable to access their HIV care provider, and close to half of PLWH were unable to access ART refills remotely, with the least access occurring in Belarus, Brazil, Kazakhstan, Mexico, and Russia [73].…”
Section: Access To Health Servicesmentioning
confidence: 99%
“…Furthermore, clinical informatics and machine learning models have the potential to improve HIV care continuum outcomes. Clinical decision support systems and electronic warnings based on electronic medical records have been used effectively to improve HIV care continuum outcomes [ 28 ].…”
Section: Discussionmentioning
confidence: 99%
“…The same alert (potentially with a repaired antibody criterion) could be used to facilitate additional quality improvement interventions for hospitalised PWH. Indeed, there is a growing body of evidence that EMR data can be used to improve diagnosis, linkage and engagement in care for PWH 12–15. This analysis adds to that literature by determining sensitivity and PPV of an EMR alert and its individual elements.…”
Section: Discussionmentioning
confidence: 99%