Financial Benefits of a Pediatric Intensive Care Unit-based Telemedicine Program to a Rural Adult Intensive Care Unit: Impact of Keeping Acutely Ill and Injured Children in Their Local Community
Bibliographic record
Abstract
The objective of this research was to examine the fiscal impact of telemedicine consultations for acutely ill and injured children in a rural setting using pediatric intensive care unit (ICU) telemedicine. One hundred seventy-nine acutely ill and injured infants and children were cared for in the Mercy Redding ICU from April 2000 to April 2002. Data were gathered from these patients, including 47 patients who received 70 pediatric ICU telemedicine consultations during the same time period. Transport and hospital costs avoided were calculated for patients who received telemedicine consultations (Group 1) and for those not transferred due to the availability telemedicine consultations (Group 2), estimated to be one-half of the 179 patients (Group 2). The revenue generated in the rural ICU based on the ability to keep these patients was also determined. An estimated annual cost savings of $172,000 and $300,000 for transport and inpatient care was demonstrated for Group 1 and Group 2, respectively. Additionally, this program resulted in generating $186,000 and $279,000 of inpatient revenue annually for the two groups at the rural hospital. The cost of this program was approximately $120,000 per year. Given the substantial financial savings, support for underserved rural programs, and significant funds kept in the rural community, this may serve as a viable model for providing care to acutely ill and injured infants and children.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".