Hospital-Based Comprehensive Care Programs for Children With Special Health Care Needs
Bibliographic record
Abstract
OBJECTIVE: To examine the effectiveness of hospital-based comprehensive care programs in improving the quality of care for children with special health care needs. DATA SOURCES: A systematic review was conducted using Ovid MEDLINE, CINAHL, EMBASE, PsycINFO, Sociological Abstracts SocioFile, and Web of Science. STUDY SELECTION: Evaluations of comprehensive care programs for categorical (those with single disease) and noncategorical groups of children with special health care needs were included. Selected articles were reviewed independently by 2 raters. DATA EXTRACTION: Models of care focused on comprehensive care based at least partially in a hospital setting. The main outcome measures were the proportions of studies demonstrating improvement in the Institute of Medicine's quality-of-care domains (effectiveness of care, efficiency of care, patient or family centeredness, patient safety, timeliness of care, and equity of care). DATA SYNTHESIS: Thirty-three unique programs were included, 13 (39%) of which were randomized controlled trials. Improved outcomes most commonly reported were efficiency of care (64% [49 of 76 outcomes]), effectiveness of care (60% [57 of 95 outcomes]), and patient or family centeredness (53% [10 of 19 outcomes). Outcomes less commonly evaluated were patient safety (9% [3 of 33 programs]), timeliness of care (6% [2 of 33 programs]), and equity of care (0%). Randomized controlled trials occurred more frequently in studies evaluating categorical vs noncategorical disease populations (11 of 17 [65%] vs 2 of 16 [17%], P = .008). CONCLUSIONS: Although positive, the evidence supporting comprehensive hospital-based programs for children with special health care needs is restricted primarily to nonexperimental studies of children with categorical diseases and is limited by inadequate outcome measures. Additional high-quality evidence with appropriate comparative groups and broad outcomes is necessary to justify continued development and growth of programs for broad groups of children with special health care needs.
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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 | 0.006 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".