Development and Validation of Quality Criteria for Providing Patient- and Family-centered Injury Care
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to develop and evaluate the content validity of quality criteria for providing patient- and family-centered injury care. BACKGROUND: Quality criteria have been developed for clinical injury care, but not patient- and family-centered injury care. METHODS: Using a modified Research AND Development Corporation (RAND)/University of California, Los Angeles (UCLA) Appropriateness Methodology, a panel of 16 patients, family members, injury and quality of care experts serially rated and revised criteria for patient- and family-centered injury care identified from patient and family focus groups. The criteria were then sent to 384 verified trauma centers in the United States, Canada, Australia, and New Zealand for evaluation. RESULTS: A total of 46 criteria were rated and revised by the panel over 4 rounds of review producing 14 criteria related to clinical care (n = 4; transitions of care, pain management, patient safety, provider competence), communication (n = 3; information for patients/families; communication of discharge plans to patients/families, communication between hospital and community providers), holistic care (n = 4; patient hygiene, kindness and respect, family access to patient, social and spiritual support) and end-of-life care (n = 3; decision making, end-of-life care, family follow-up). Medical directors, managers, or coordinators representing 254 trauma centers (66% response rate) rated 12 criteria to be important (95% of responses) for patient- and family-centered injury care. Fewer centers rated family access to the patient (80%) and family follow-up after patient death (65%) to be important criteria. CONCLUSIONS: Fourteen-candidate quality criteria for patient- and family-centered injury care were developed and shown to have content validity. These may be used to guide quality improvement practices.
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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 | 0.112 | 0.283 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".