Engaging healthcare providers to implement HIV pre-exposure prophylaxis
aDivision of Infectious Diseases, Department of Medicine, Beth Israel Deaconess Medical Center bHarvard Medical School cThe Fenway Institute, Fenway Health, Boston, Massachusetts, USA. Current opinion in HIV and AIDS
(Impact Factor: 4.68).
10/2012; 7(6):593-9. DOI: 10.1097/COH.0b013e3283590446
Recent randomized controlled trials have demonstrated that HIV pre-exposure prophylaxis (PrEP) can decrease HIV incidence among several at-risk populations, including men who have sex with men, serodiscordant couples, and heterosexual men and women. As PrEP is a biomedical intervention that requires clinical monitoring and a high level of medication adherence, maximizing the public health effectiveness of PrEP in real-world settings will require the training of a cadre of healthcare providers to prescribe PrEP. Therefore it is critical to understand provider knowledge, practices, and attitudes towards PrEP prescribing, and to develop strategies for engaging and training providers to provide PrEP.
Limited numbers of studies have focused on PrEP implementation by healthcare providers. These studies suggest that some providers are knowledgeable about PrEP, but many are not, or express misgivings. Although many clinicians report willingness to provide PrEP, few have prescribed PrEP in clinical practice. Provider comfort and skills in HIV risk assessment are suboptimal, which could limit identification of individuals who are most likely to benefit from PrEP use.
Further studies to understand facilitators and barriers to HIV-risk assessment and PrEP prescribing by practicing clinicians are needed. Innovative training strategies and decision-support interventions for providers could optimize PrEP implementation and therefore merit additional research.
Available from: Catherine Hankins
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ABSTRACT: Cost-effectiveness studies inform resource allocation, strategy, and policy development. However, due to their complexity, dependence on assumptions made, and inherent uncertainty, synthesising, and generalising the results can be difficult. We assess cost-effectiveness models evaluating expected health gains and costs of HIV pre-exposure prophylaxis (PrEP) interventions.
We conducted a systematic review comparing epidemiological and economic assumptions of cost-effectiveness studies using various modelling approaches. The following databases were searched (until January 2013): PubMed/Medline, ISI Web of Knowledge, Centre for Reviews and Dissemination databases, EconLIT, and region-specific databases. We included modelling studies reporting both cost and expected impact of a PrEP roll-out. We explored five issues: prioritisation strategies, adherence, behaviour change, toxicity, and resistance. Of 961 studies retrieved, 13 were included. Studies modelled populations (heterosexual couples, men who have sex with men, people who inject drugs) in generalised and concentrated epidemics from Southern Africa (including South Africa), Ukraine, USA, and Peru. PrEP was found to have the potential to be a cost-effective addition to HIV prevention programmes in specific settings. The extent of the impact of PrEP depended upon assumptions made concerning cost, epidemic context, programme coverage, prioritisation strategies, and individual-level adherence. Delivery of PrEP to key populations at highest risk of HIV exposure appears the most cost-effective strategy. Limitations of this review include the partial geographical coverage, our inability to perform a meta-analysis, and the paucity of information available exploring trade-offs between early treatment and PrEP.
Our review identifies the main considerations to address in assessing cost-effectiveness analyses of a PrEP intervention-cost, epidemic context, individual adherence level, PrEP programme coverage, and prioritisation strategy. Cost-effectiveness studies indicating where resources can be applied for greatest impact are essential to guide resource allocation decisions; however, the results of such analyses must be considered within the context of the underlying assumptions made. Please see later in the article for the Editors' Summary.
PLoS Medicine 03/2013; 10(3):e1001401. DOI:10.1371/journal.pmed.1001401 · 14.43 Impact Factor
JAIDS Journal of Acquired Immune Deficiency Syndromes 06/2013; 63 Suppl 1:S108-13. DOI:10.1097/QAI.0b013e318291fff4 · 4.56 Impact Factor
JAIDS Journal of Acquired Immune Deficiency Syndromes 07/2013; 64(1). DOI:10.1097/QAI.0b013e3182a3979c · 4.56 Impact Factor
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