Hospitalization Costs for Patients Undergoing Orthopedic Surgery Treated With Intravenous Acetaminophen (IV-APAP) Plus Other IV Analgesics or IV Opioid Monotherapy for Postoperative Pain
Bibliographic record
Abstract
INTRODUCTION: To assess the impact on hospitalization costs of multimodal analgesia (MMA), including intravenous acetaminophen (IV-APAP), versus IV opioid monotherapy for postoperative pain management in patients undergoing orthopedic surgery. METHODS: Hospital Drug Database (HDD), patients undergoing total knee arthroplasty (TKA), total hip arthroplasty (THA), or surgical repair of hip fracture between 1/1/2011 and 8/31/2014 were separated into postoperative pain management groups: MMA with IV-APAP plus other IV analgesics (IV-APAP group) or an IV opioid monotherapy group. All patients could have received oral analgesics. Baseline characteristics and total hospitalization costs were compared. Additionally, an inverse probability treatment weighting [IPTW] with propensity scores analysis further assessed hospitalization cost differences. RESULTS: The IV-APAP group (n = 33,954) and IV opioid monotherapy group (n = 110,300) differed significantly (P < 0.0001) across baseline characteristics, though the differences may not have been clinically meaningful. Total hospitalization costs (mean ± standard deviation) were significantly lower for the IV-APAP group than the IV opioid monotherapy group (US$12,540 ± $9564 vs. $13,242 ± $35,825; P < 0.0001). Medical costs accounted for $701 of the $702 between-group difference. Pharmacy costs were similar between groups. Results of the IPTW-adjusted analysis further supported the statistically significant cost difference. CONCLUSIONS: Patients undergoing orthopedic surgery who received MMA for postoperative pain management, including IV-APAP, had significantly lower total costs than patients who received IV opioid monotherapy. This difference was driven by medical costs; importantly, there was no difference in pharmacy costs. Generalizability of the results may be limited to patients admitted to hospitals similar to those included in HDD. Dosing could not be determined, so it was not possible to quantify utilization of IV-APAP or ascertain differences in opioid consumption between the 2 groups. This study did not account for healthcare utilization post-discharge.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".