2072. Do ID and Non-ID Clinicians Agree on IV to PO Switch Criteria? Results from Phase I of the INForming IV to ORal MEdication Report (INFORMER) Project
Bibliographic record
Abstract
Abstract Background Converting intravenous (IV) antibiotics to an oral (PO) route is an important stewardship activity to reduce patient harm, including extravasation, thrombophlebitis, and catheter-related infections. The INFORMER Project aims to develop a “smart” electronic tool to streamline IV to PO conversion in eligible patients using an algorithm derived from patient-level data. In designing the algorithm, we noted significant clinician subjectivity in reviewing PO eligibility criteria. To support algorithm development and frontline clinician buy in for future e-tool use, an initial step of our project explored agreement level for IV to PO switch between general internal medicine (GIM) vs. ID clinicians. Methods A convenience sample of GIM patients (tertiary teaching hospital) were reviewed in a 4-month pilot. Patients were still on the ward and received a target IV antibiotic (fluoroquinolone, sulfamethoxazole/trimethoprim, clindamycin, metronidazole, linezolid, fluconazole, voriconazole, azithromycin). To mimic real-time decision-making, clinicians (MD and PharmDs) retrospectively assessed IV to PO eligibility of the last IV antibiotic dose on admission for (1) GI/absorption, (2) clinical stability and (3) global review (but not given specific thresholds/criteria). Agreement level was compared for ID vs. non-ID reviews. Results Overall, 52 patients’ IV to PO eligibility was assessed by multiple clinicians; 5 GIM teams and 6 ID MDs or PharmDs participated. ID vs. GIM respective assessment of Global eligibility was 61% vs. 48% (agreement in 71% of cases). ID vs. GIM assessment of acceptable absorption was 82% vs. 67%; acceptable clinical stability was 64% vs. 62% (Fig 1). Clinician comments were reviewed to identify algorithm improvements and areas for frontline education. Conclusion Our results are consistent with prior data suggesting up to 40–50% of patients may be eligible for IV to PO conversion, even at institutions that have IV to PO protocols. Our data also shows that overall, ID clinicians were more likely to assess a patient as ready for PO antibiotics vs. non-ID clinicians. Our findings are important as understanding cases of non-agreement and obtaining GIM consensus for tool utility are important for our next step, assessing INFORMER implementation on realtime IV to PO conversion rates. Disclosures All authors: No reported disclosures.
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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 | 0.045 | 0.117 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".