Using outcomes data to justify instituting new technology: a single institution’s experience
Bibliographic record
Abstract
BACKGROUND: The PILLAR II trial demonstrated PINPOINT is safe, feasible to use with no reported adverse events and resulted in no anastomotic leaks in patients who had a change in surgical plan based on PINPOINT's intraoperative assessment of tissue perfusion during colorectal resection. Whether the cost savings associated with this reduction in anastomotic complications can offset the cost of investing in PINPOINT is unknown. METHODS: We performed a retrospective analysis of all patients (N = 347) undergoing colectomy with primary anastomosis from January 2015 to April 2016. These patients were stratified based on whether fluorescence imaging was used intraoperatively. The clinical outcomes of these patients were then evaluated based on their development of an anastomotic leak or stricture. The direct hospital costs per case were then calculated, and the economic impact of using fluorescence imaging was examined to assess whether decreased direct costs would justify the initial expenditures to purchase new technology (PINPOINT System, NOVADAQ, Canada). RESULTS: Fluorescence imaging in colorectal surgery using PINPOINT reduced the anastomotic failure rate in patients who underwent colon resection. The PINPOINT group (n = 238) had two (0.84%) anastomotic failures, while the non-PINPOINT group (n = 109) had six (5.5%) anastomotic failures. In the PINPOINT group, 11 (4.6%) patients had a change in the resection margin based on the results of the fluorescence imaging, and none of these patients experienced an anastomotic failure. Cost per case was less in the PINPOINT group secondary to fewer direct costs associated with complications. CONCLUSIONS: These results validate the findings of the PILLAR II trial and confirm the decrease in direct costs due to reduction in anastomotic failures as a result of using PINPOINT justified the expense of the new technology after just 143 cases.
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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 | 0.013 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".