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Prioritizing healthcare facilities for on-site mentorship to increase HIV treatment uptake: results from EQUIP Brooke Nichols, Cheryl Hendrickson, Ntombi.

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Presentation on theme: "Prioritizing healthcare facilities for on-site mentorship to increase HIV treatment uptake: results from EQUIP Brooke Nichols, Cheryl Hendrickson, Ntombi."— Presentation transcript:

1 Prioritizing healthcare facilities for on-site mentorship to increase HIV treatment uptake: results from EQUIP Brooke Nichols, Cheryl Hendrickson, Ntombi Sigwebela, Crispin Moyo, Matthew Fox, Sydney Rosen; on behalf of EQUIP

2 Introduction Throughout Africa, resources are being invested in healthcare facilities to increase the number of new patients initiating ART, with the goal of achieving the “second 90.” Healthcare facilities frequently receive on-site mentorship to assist a facility in meeting targets (such as new-on-ART). Determining which facilities to target can be based on: A single parameter (size of facility, or catchment area size) A rough estimate based on on-the-ground experience Nothing (equal distribution of resources)

3 Objective To design a novel and practical methodology to rank individual health facilities to receive on-site mentorship based on their potential to contribute to total numbers of patients initiating treatment (“new-on-ART”) as part of a PEPFAR program to expand and improve service delivery in two provinces in Zambia.

4 Methods: Prioritization
Using PEPFAR data, we ranked all facilities offering ART in the selected provinces by number of patients initiated on ART in 2017. Using univariable and multivariable regression, we identified facility- level parameters associated with being in the top quartile of new-on- ART in 2017. Parameters associated with being in the top quartile of new-on-ART were then assigned weights and the weights summed at the facility level to calculate each facility’s prioritization score. Parameters that were significant in the univariable analysis were weighted once, parameters that were significant in the multivariable analysis were double weighted.

5 Methods: Prioritization
Facilities that received a high prioritization score but did not rank highly on treatment initiation numbers (i.e. facilities that did not initiate as many new patients as their prioritization score suggested they should) were prioritized. These were further sub-prioritized depending on the percent of the catchment area tested in the last 12 months, and whether the facility is in a high-burden district.

6 Methods: Intervention
In December 2017, some prioritized and some non-prioritized facilities received intensive day-long on-site mentorship on target setting, stock monitoring, clinician mentoring on routine HIV testing, ART initiation, and record keeping: the intervention. October December November February January Pre-intervention (2017) Post-intervention (2018) Intervention (2017)

7 Methods: analytic sub-groups
Prioritized Not prioritized Total Received intervention 7 3 10 Did not receive intervention 6 60 66 13 63 76

8 Results: change in average number of new-on-ART
21% increase 16% increase

9 Results: change in average number of new-on-ART

10 Conclusions Early data suggest that prioritizing facilities for mentorship on the basis of unrealized potential may be able to increase numbers of new-on-ART more efficiently than giving all facilities equal support. Further investigation into practical easily-applied methodologies for prioritizing healthcare facilities for technical assistance is warranted.

11 Disclaimer This presentation is made possible by the support of the American people through the United States Agency for International Development (USAID). The contents are the sole responsibility of Right to Care and do not necessarily reflect the views of USAID or the United States Government.

12 Thank you Dank jullie wel!

13 Results: proportion of new-on-ART targets achieved
Category Pre-intervention Post-intervention Prioritized, received mentoring 110% 134% Prioritized, did not receive mentoring 52% 38% Non prioritized, received mentoring 55% 34% Non prioritized, did not receive mentoring 76% 89%


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