Reactive Adherence Counseling (Haiti)
I-Tech, Haiti (April 2021)
Last updated
I-Tech, Haiti (April 2021)
Last updated
Introduces predictive analytics to improve HIV clinical management. It pairs improvements to a routine data system with theory-based behavior change interventions for patients and health care workers.
Presenter: Nancy Puttkammer, I-TECH
路 Appointment Date (history)
路 Visit Date
路 Proportion of days covered based on dispensing (changed with COVID)
路 Sex
路 Age
路 Marital status
路 Time from HIV diagnosis to enrollment in HIV care and treatment
路 Time from HIV diagnosis to ART initiation
路 Baseline CD4 count
路 Body mass index
路 World Health Organization (WHO) stage of HIV disease progression ART regime.
Puttkammer N, Simoni JM, Sandifer T, et al. An EMR-Based Alert with Brief Provider-Led ART Adherence Counseling: Promising Results of the InfoPlus Adherence Pilot Study Among Haitian Adults with HIV Initiating ART. AIDS Behav 2020. PMID: 32715409
Can work in EHR
Interest in exchange of risk information with community health worker tool/app
Risk level using data elements at left
Need to implement within OpenMRS-based EMR
Prediction model needs refreshing as conditions change (multi-month dispensing)
Most helpful when using EHR at the point-of-care
Will need to be re-implemented with OpenMRS rollout
Threshold of data quality needed (being investigated)
Prediction models are being revisited using machine learning (super learner models) with additional data elements.
Complexity of implementing a clinical decision support prediction model needs to be weighed against the benefit of added sensitivity and specificity gained (is it worth it)
Need governance (what sensitivity and specificity of prediction is adequate; whether it鈥檚 suitable to implement in all facilities using EMR or only sites with sufficient data quality)
Need actionable clinical and psychosocial support for those determined to be at high risk
Data Elements
Evidence
Technology Requirements / Interoperability
Calculations / Algorithms
Factors to Scale
Implementation Considerations
Governance Considerations