Barriers to Implementation of Rapid and Point-of-Care Tests for Human Immunodeficiency Virus Infection
Bibliographic record
Abstract
Implementation of human immunodeficiency virus rapid and point-of-care tests (RDT/POCT) is understood to be impeded by many different factors that operate at 4 main levels-test devices, patients, providers, and health systems-yet a knowledge gap exists of how they act and interact to impede implementation. To fill this gap, and with a view to improving the quality of implementation, we conducted a systematic review. METHODS: Five databases were searched, 16,672 citations were retrieved, and data were abstracted on 132 studies by 2 reviewers. FINDINGS: Across 3 levels (ie, patients, providers, and health systems), a majority (59%, 112/190) of the 190 barriers were related to the integration of RDT/POCT, followed by test-device-related concern (ie, accuracy) at 41% (78/190). At the patient level, a lack of awareness about tests (15/54, 28%) and time taken to test (12/54, 22%) dominated. At the provider and health system levels, integration of RDT/POCT in clinical workflows (7/24, 29%) and within hospitals (21/34, 62%) prevailed. Accuracy (57/78, 73%) was dominant only at the device level. INTERPRETATION: Integration barriers dominated the findings followed by test accuracy. Although accuracy has improved during the years, an ideal implementation could be achieved by improving the integration of RDT/POCT within clinics, hospitals, and health systems, with clear protocols, training on quality assurance and control, clear communication, and linkage plans to improve health outcomes of patients. This finding is pertinent for a future envisioned implementation and global scale-up of RDT/POCT-based initiatives.
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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 | 0.069 | 0.323 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".