Do callers of young children with fever follow the self-care recommendations given by a nursing triage line?
Bibliographic record
Abstract
IntroductionThe management of fever can be a stressful situation for caregivers of young children. Accessing emergency departments and urgent care centres (ED/UCCs) due to concerns about fever and the potential consequences of child fever is common, despite fever rarely being considered a medical emergency.
 Objectives and ApproachDetermine the non-compliance rate with public health advice for self-care at home for young children (3-35 months) with a fever. Non-compliance was defined based on the presence of a record of healthcare use within 72 hours following a call to a nurse telephone triage line, Health Link (HL), and receiving a self-care recommendation. Callers between October 2015-March 2016 were identified and linked with four databases: registry files, National Ambulatory Care Reporting System; Inpatient-Discharge Abstract Database and Physician Claims (N = 879). Overall non-compliance rate and descriptive analysis by child age, caregiver age, geography, and call time were completed.
 ResultsThe overall non-compliance rate with HL advice was 35.6%. Among callers, 17.5% visited an ED/UCC, 1.1% had an inpatient hospital admission, and 21.3% visited a physician’s office. Among the patients that utilized health care services after the HL call, 13.6% only visited ED/UCC, 18% only visited a physician’s office, and 4% utilized more than one type of health care service. Callers in rural and rural remote areas had lower odds of visiting a physician’s office compared to the urban areas (p-value <0.01). No significant differences were found by child age, caregiver age or time of call.
 Conclusion/ImplicationsFindings of this study suggest that approximately one-third of callers are not following the telephone triage advice, potentially leading to unnecessary increased burden on the healthcare system. Further study is warranted to examine reasons for non-compliance. Strategies to increase compliance in caregivers should be explored.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".