Cascade Monitoring in Multidisciplinary Adolescent HIV Care Settings: Protocol for Utilizing Electronic Health Records
Bibliographic record
Abstract
BACKGROUND: Past research shows that youth living with HIV (YLH) are not as engaged in the HIV treatment cascade as other HIV-positive populations. To achieve the health benefits of rapid and widespread testing and advanced pharmacologic treatment, YLH must be fully engaged in every stage of the treatment cascade. Cascade monitoring provides an opportunity to assess the youth care cascade, including engagement in care and when youth commonly drop out of care, across 10 clinical sites in the United States. Collecting electronic health record (EHR) data for prevention and care across participant recruitment venues within the Adolescent Medicine Trials Network (ATN) allows for monitoring of the prevention and care cascades within the ATN, for comparing the ATN population to large-scale surveillance, for future integration of technology-based interventions into EHRs, and for informing ATN strategic planning. OBJECTIVE: The aim of this protocol study is to examine the trends in treatment cascade, including whether patients are receiving antiretroviral therapy, adhering to regimens, attending care appointments, and maintaining suppressed viral loads, to guide new protocol development and to facilitate community engagement. This protocol is part of the ATN Scale It Up (SIU) program described in this issue. METHODS: Deidentified EHR data of YLH, aged 15 to 24 years, will be collected annually (2017 to 2022) from 10 ATN clinical sites, resulting in patient data from 2016 to 2021. These data will be transferred and stored using Dropbox Business, a Health Insurance Portability and Accountability Act-compliant site and then analyzed by the SIU analytic core. RESULTS: This study was launched in December 2017 in 10 clinical sites, with 2016's EHR data due on January 31, 2017. All 10 sites electronically uploaded their EHR data. The mandatory variables requested to monitor cascade of care include date of visit, age, gender, height, weight, race, ethnicity, viral load, and International Classification of Diseases codes for other diagnosis. In total, 70% of the sites provided data for all mandatory variables. The remaining mandatory variables were manually extracted. CONCLUSIONS: This study will provide a platform to determine how YLH across the nation progress through or drop out of the HIV treatment cascade. It will also provide a foundation for assessing impact of SIU projects on treatment cascade outcomes. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/11185.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.082 | 0.095 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.092 | 0.017 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".