Triage through telemedicine in paediatric emergency care—Results of a concordance study
Bibliographic record
Abstract
BACKGROUND: In the German health care system, parents with an acutely ill child can visit an emergency room (ER) 24 hours a day, seven days a week. At the ER, the patient receives a medical consultation. Many parents use these facilities as they do not know how urgently their child requires medical attention. In recent years, paediatric departments in smaller hospitals have been closed, particularly in rural regions. As a result of this, the distances that patients must travel to paediatric care facilities in these regions are increasing, causing more children to visit an ER for adults. However, paediatric expertise is often required in order to assess how quickly the patient requires treatment and select an adequate treatment. This decision is made by a doctor in German ERs. We have examined whether remote paediatricians can perform a standardised urgency assessment (triage) using a video conferencing system. METHODS: Only acutely ill patients who were brought to a paediatric emergency room (paedER) by their parents or carers, without prior medical consultation, have been included in this study. First, an on-site paediatrician assessed the urgency of each case using a standardised triage. In order to do this, the Paediatric Canadian Triage and Acuity Scale (PaedCTAS) was translated into German and adapted for use in a standardised IT-based data collection tool. After the initial on-site triage, a telemedicine paediatrician, based in a different hospital, repeated the triage using a video conferencing system. Both paediatricians used the same triage procedure. The primary outcome was the degree of concordance and interobserver agreement, measured using Cohen's kappa, between the two paediatricians. We have also included patient and assessor demographics. RESULTS: A total of 266 patients were included in the study. Of these, 227 cases were eligible for the concordance analysis. In n = 154 cases (68%), there was concordance between the on-site paediatrician's and telemedicine paediatrician's urgency assessments. In n = 50 cases (22%), the telemedicine paediatrician rated the urgency of the patient's condition higher (overtriage); in 23 cases (10%), the assessment indicated a lower urgency (undertriage). Nineteen medical doctors were included in the study, mostly trained paediatric specialists. Some of them acted as an on-site doctor and telemedicine doctor. Cohen's weighted kappa was 0.64 (95% CI: 0.49-0.79), indicating a substantial agreement between the specialists. CONCLUSIONS: Telemedical triage can assist in providing acute paediatric care in regions with a low density of paediatric care facilities. The next steps are further developing the triage tool and implementing telemedicine urgency assessment in a larger network of hospitals in order to improve the integration of telemedicine into hospitals' organisational processes. The processes should include intensive training for the doctors involved in telemedical triage. TRIAL REGISTRATION: DRKS00013207.
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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 | 0.011 | 0.058 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".