Defining pediatric inpatient cardiology care delivery models: A survey of pediatric cardiology programs in the USA and Canada
Bibliographic record
Abstract
BACKGROUND: The treatment of children with cardiac disease is one of the most prevalent and costly pediatric inpatient conditions. The design of inpatient medical services for children admitted to and discharged from noncritical cardiology care units, however, is undefined. North American Pediatric Cardiology Programs were surveyed to define noncritical cardiac care unit models in current practice. METHOD: An online survey that explored institutional and functional domains for noncritical cardiac care unit was crafted. All questions were multi-choice with comment boxes for further explanation. The survey was distributed by email four times over a 5-month period. RESULTS: Most programs (n = 45, 60%) exist in free-standing children's hospitals. Most programs cohort cardiac patients on noncritical cardiac care units that are restricted to cardiac patients in 39 (54%) programs or restricted to cardiac and other subspecialty patients in 23 (32%) programs. The most common frontline providers are categorical pediatric residents (n = 58, 81%) and nurse practitioners (n = 48, 67%). However, nurse practitioners are autonomous providers in only 21 (29%) programs. Only 33% of programs use a postoperative fast-track protocol. When transitioning care to referring physicians, most programs (n = 53, 72%) use facsimile to deliver pertinent patient information. Twenty-two programs (31%) use email to transition care, and eighteen (25%) programs use verbal communication. CONCLUSION: Most programs exist in free-standing children's hospitals in which the noncritical cardiac care units are in some form restricted to cardiac patients. While nurse practitioners are used on most noncritical cardiac care units, they rarely function as autonomous providers. The majority of programs in this survey do not incorporate any postoperative fast-track protocols in their practice. Given the current era of focused handoffs within hospital systems, relatively few programs utilize verbal handoffs to the referring pediatric cardiologist/pediatrician.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".