Analysis of the economic burden of docusate sodium at a United States tertiary care center
Bibliographic record
Abstract
OBJECTIVES: The primary objective was to determine the financial resources allocated to docusate at a representative U.S. tertiary care center. Secondary objectives included comparing docusate utilization between two tertiary care centers, and exploring alternative uses for the funds spent on docusate. METHODS: , 2019 was collected. The annual total cost associated with docusate use per year was calculated. The 2015 data from this study and a 2015 McGill University Health Centre study were compared. Also, alternative uses for the money utilized on docusate were assessed. RESULTS: Over the study period, 37,034 docusate prescriptions and 265,123 docusate doses were recorded. The average cost of prescribing docusate was $25,624.14 per year and $49.37 per hospital bed per year. A comparison between the 2015 data of University Hospital and McGill showed that McGill prescribed 107 doses and spent $10.09 more per hospital bed than University Hospital. Finally, alternative uses for the average yearly spending on docusate equated to 0.35 the salary of a nurse, 0.51 the salary of a secretary, 20.66 colonoscopies, 27.00 upper endoscopies, 186.71 mammograms, 1,399.37 doses of polyethylene glycol 3350, 3,826.57 doses of lactulose, or 4,583.80 doses of psyllium. CONCLUSION: A single average size tertiary care hospital spent about $25,000 yearly on docusate despite its lack of clinical effectiveness. While this amount is small compared to an overall hospital budget, when considering likely comparable docusate use at the U.S's 6,090 hospitals, the economic burden of docusate becomes significant. The funds currently being used on docusate could be redirected to alternative, more cost-effective purposes.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".