Perceived potentially inappropriate treatment in the PICU: frequency, contributing factors and the distress it triggers
Bibliographic record
Abstract
Background: Potentially inappropriate treatment in critically ill adults is associated with healthcare provider distress and burnout. Knowledge regarding perceived potentially inappropriate treatment amongst pediatric healthcare providers is limited. Objectives: Determine the frequency and factors associated with potentially inappropriate treatment in critically ill children as perceived by providers, and describe the factors that providers report contribute to the distress they experience when providing treatment perceived as potentially inappropriate. Methods: Prospective observational mixed-methods study in a single tertiary level PICU conducted between March 2 and September 14, 2018. Patients 0-17 years inclusive with: (1) ≥1 organ system dysfunction (2) moderate to severe mental and physical disabilities, or (3) baseline dependence on medical technology were enrolled if they remained admitted to the PICU for ≥48 h, and were not medically fit for transfer/discharge. The frequency of perceived potentially inappropriate treatment was stratified into three groups based on degree of consensus (1, 2 or 3 providers) regarding the appropriateness of ongoing active treatment per enrolled patient. Distress was self-reported using a 100-point scale. Results: Of 374 patients admitted during the study, 133 satisfied the inclusion-exclusion criteria. Eighteen patients (unanimous - 3 patients, 2 providers - 7 patients; single provider - 8 patients) were perceived as receiving potentially inappropriate treatment; unanimous consensus was associated with 100% mortality on 3-month follow up post PICU discharge. Fifty-three percent of providers experienced distress secondary to providing treatment perceived as potentially inappropriate. Qualitative thematic analysis revealed five themes regarding factors associated with provider distress: (1) suffering including a sense of causing harm, (2) conflict, (3) quality of life, (4) resource utilization, and (5) uncertainty. Conclusions: While treatment perceived as potentially inappropriate was infrequent, provider distress was commonly observed. By identifying specific factor(s) contributing to perceived potentially inappropriate treatment and any associated provider distress, organizations can design, implement and assess targeted interventions.
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".