Pediatric Ethics Consultation Services, Scope, and Staffing
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: National standards and guidelines call for a mechanism to address ethical concerns and conflicts in children's hospitals. The roles, responsibilities, and reach of pediatric ethics consultation services (PECS) remain unmeasured. The purpose of this study is to quantify staffing, structure, function, scope, training, and funding of PECS. METHODS: Cross-sectional online survey was shared with an ethics informant at 181 children's hospitals in the United States from March to June 2022. Data were summarized descriptively and with semantic content analyses. RESULTS: One hundred seventeen surveys were received from individual children's hospitals in 45 states and Washington DC (response rate 65%), with 104 qualifying for survey completion. Almost one-quarter of settings received 50 or more pediatric ethics consults in the past 12 months. On average, 7.4 people at each institution have responsibility for completing ethics consults. Estimated full-time equivalent salary support for ethics is on average 0.5 (range 0-3, median 0.25). One-third (33%) of facilities do not offer any salary support for ethics and three-quarters do not have an institutional budget for the ethics program. Clinical staff primarily initiate consults. End-of-life, benefits versus burdens of treatments, and staff moral distress were the most frequently consulted themes. Almost one-quarter (21%) of children's hospitals do not receive any consults from patients or families. CONLUSIONS: The findings from this study reveal wide variation in PECS practices and raise concern about the lack of financial support provided for PECS despite substantial workloads.
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 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 | 0.005 | 0.032 |
| 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 | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".