Adherence Dashboard (Kenya)
LVCT Health, Kenya (April 2021)
Last updated
LVCT Health, Kenya (April 2021)
Last updated
Dashboard to identify patients with potential retention to support adherence in HIV care through data collection of HIV Testing services, clinical services, and key population services.
Presenter: Peris Nasimiyu and Pinto Shukuru, LVCT Health
Data Elements
Missed HIV appointment
Due for VL
Pending VL Results
High VL
Unstable
Evidence
Appointment keep rate increased to around 80% from around 60%.
12 month ART cohort retention around 70% with fluctuations due to migration which they are now able to track.
Viral load suppression around 92-94%.
Use of EMR from 1 clinic in 2014 to 12 care clinics in 2017.
Technology Requirements / Interoperability
Computer with internet and server.
Cell phone - Mobile Application with offline functionality.
Dashboard- integrated with DHIS2/National Reporting System.
Use of Ushauri (synched with EMR) for appointment reminders via text.
Interoperability layer between EMR and NASCOP and NASCOP VL website for direct sync of VL and EID data.
Calculations / Algorithms
High viral load- client with VL copies of more than 400.
Due for VL- has been on ART for more than 6 months, then 1 year apart, identified pregnant, on EAC 3 months after reporting high VL.
Missed HIV appointment- more than 24 hrs have elapsed since the day they were to come for their clinic appointment; Defaulter- 72 hrs; LTFU- 30 days.
Pending VL results- client bled for VL testing but lab yet to dispatch results.
Unstable- new client of less than 12 months on ART, client with VL more than 1,000 copies; client with adherence of less than 95%.
Factors to Scale
Need to implement within OpenMRS-based EMR.
Unable to flag key indicators - use hybrid model of paper and electronic version.
Power outages due to location and country infrastructure.
Need to synchronize EMR to reporting systems.
Implementation Considerations
Patients need access to mobile phones.
Power outages prevent upload of data - paper version needed to bridge gap.
Patients need to be language and technology literate to use mobile application.
System not able to flag at-risk patients so highlighted in register.
Register also track outreach attempts, final outcome recorded in EMR.
Train service providers.
Governance Considerations
Data Security - proper storage of paper version.
Potential loss of data upload and retrieval due to power outages.
Capacity of service providers including willingness and laxity.