The Experience of Parents of Hospitalized Children Living With Medical Complexity
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Children living with medical complexity (CMC) experience frequent hospital admissions. Validated patient-reported experience measures may inform care improvements in this cohort. Our objectives were to examine the comprehensive inpatient experience of CMC by using a validated patient-reported experience measure and compare the results with all other respondents at 2 academic pediatric hospitals in a western Canadian province. METHODS: Parents completed the Child Hospital Consumer Assessment of Healthcare Providers and Systems survey. Surveys were linked with inpatient records, and an accepted case definition was used to extract records pertaining to CMC. Results were reported as percent in "top box," represented by the most positive answer choice to each measure. Odds of reporting a top box response were calculated while controlling for demographic and clinical features. RESULTS: From October 2015 to March 2019, 4197 surveys (1515 CMC; 2682 non-CMC) were collected. Among CMC, the highest-rated measures pertained to being kept informed while in the emergency department, a willingness to recommend the hospital, and parents having a clear understanding of their role in their child's care. The lowest-rated measures pertained to preventing mistakes and reporting concerns and the quietness of the hospital room at night. Compared with others, parents of CMC reported lower raw results on 20 of the 28 measures. They also reported lower a odds of reporting a top box score on 2 measures and higher odds on 1. CONCLUSIONS: Parents of CMC revealed many perceived gaps. These findings can be used to inform strategies to improve care among CMC and policies to support the care of CMC and their families.
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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 | 0.001 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".