Outpatient versus inpatient intravenous antimicrobial therapy : a population-based observational cohort study of adverse events and costs
Bibliographic record
Abstract
BACKGROUND: Bacterial infections such as osteomyelitis and endocarditis routinely require several weeks of treatment with intravenous (IV) antimicrobials. Outpatient parenteral antimicrobial therapy (OPAT) programs allow patients to receive IV antimicrobials in an outpatient clinic or at home. The outcomes and costs of such treatments remain uncertain. METHODS: We conducted a retrospective observational cohort study over a 5-year study interval (June 1, 2012, to March 31, 2018) using population-based linked administrative data from British Columbia, Canada. Patients receiving OPAT following a hospitalization for bacterial infection were matched based on infection type and implied duration of IV antimicrobials to patients receiving inpatient parenteral antimicrobial therapy (IPAT). Cumulative adverse events and direct healthcare costs were estimated over a 90-day outcome interval. RESULTS: In a matched cohort of 1,842 patients, adverse events occurred in 35.6% of OPAT patients and 39.0% of IPAT patients (adjusted odds ratio, 1.04; 95%CI, 0.83-1.30; p=0.61). Relative to IPAT patients, OPAT patients were significantly more likely to experience hospital readmission (30.5% vs 23.0%) but significantly less likely to experience C. difficile diarrhea (1.2% vs 3.1%) or death (2.0% vs 8.8%). Estimated mean direct healthcare costs were $30,166 for OPAT patients and $50,038 for IPAT patients (cost ratio, 0.60; average cost savings with OPAT, $17,579; 95%CI, $14,131-$21,027; p<0.001). CONCLUSION: Outpatient IV antimicrobial therapy is associated with a similar overall prevalence of adverse events and with substantial cost savings relative to patients remaining in hospital to complete IV antimicrobials. These findings should inform efforts to expand OPAT use.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".