Allan Cameron1, Alastair J Ireland2, Gerard A McKay1, Adam Stark3, David J Lowe2,4. 1. Acute Medicine Unit, Glasgow Royal Infirmary, Glasgow, UK. 2. Emergency Department, Glasgow Royal Infirmary, Glasgow, UK. 3. Medical School, University of Glasgow, Glasgow, UK. 4. Academic Unit of Anaesthesia, Pain and Critical Care Medicine, School of Medicine, University of Glasgow, Glasgow, UK.
Abstract
AIM: We compared two methods of predicting hospital admission from ED triage: probabilities estimated by triage nurses and probabilities calculated by the Glasgow Admission Prediction Score (GAPS). METHODS: In this single-centre prospective study, triage nurses estimated the probability of admission using a 100 mm visual analogue scale (VAS), and GAPS was generated automatically from triage data. We compared calibration using rank sum tests, discrimination using area under receiver operating characteristic curves (AUC) and accuracy with McNemar's test. RESULTS: Of 1829 attendances, 745 (40.7%) were admitted, not significantly different from GAPS' prediction of 750 (41.0%, p=0.678). In contrast, the nurses' mean VAS predicted 865 admissions (47.3%), overestimating by 6.6% (p<0.0001). GAPS discriminated between admission and discharge as well as nurses, its AUC 0.876 compared with 0.875 for VAS (p=0.93). As a binary predictor, its accuracy was 80.6%, again comparable with VAS (79.0%), p=0.18. In the minority of attendances, when nurses felt at least 95% certain of the outcome, VAS' accuracy was excellent, at 92.4%. However, in the remaining majority, GAPS significantly outperformed VAS on calibration (+1.2% vs +9.2%, p<0.0001), discrimination (AUC 0.810 vs 0.759, p=0.001) and accuracy (75.1% vs 68.9%, p=0.0009). When we used GAPS, but 'over-ruled' it when clinical certainty was ≥95%, this significantly outperformed either method, with AUC 0.891 (0.877-0.907) and accuracy 82.5% (80.7%-84.2%). CONCLUSIONS: GAPS, a simple clinical score, is a better predictor of admission than triage nurses, unless the nurse is sure about the outcome, in which case their clinical judgement should be respected. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.
AIM: We compared two methods of predicting hospital admission from ED triage: probabilities estimated by triage nurses and probabilities calculated by the Glasgow Admission Prediction Score (GAPS). METHODS: In this single-centre prospective study, triage nurses estimated the probability of admission using a 100 mm visual analogue scale (VAS), and GAPS was generated automatically from triage data. We compared calibration using rank sum tests, discrimination using area under receiver operating characteristic curves (AUC) and accuracy with McNemar's test. RESULTS: Of 1829 attendances, 745 (40.7%) were admitted, not significantly different from GAPS' prediction of 750 (41.0%, p=0.678). In contrast, the nurses' mean VAS predicted 865 admissions (47.3%), overestimating by 6.6% (p<0.0001). GAPS discriminated between admission and discharge as well as nurses, its AUC 0.876 compared with 0.875 for VAS (p=0.93). As a binary predictor, its accuracy was 80.6%, again comparable with VAS (79.0%), p=0.18. In the minority of attendances, when nurses felt at least 95% certain of the outcome, VAS' accuracy was excellent, at 92.4%. However, in the remaining majority, GAPS significantly outperformed VAS on calibration (+1.2% vs +9.2%, p<0.0001), discrimination (AUC 0.810 vs 0.759, p=0.001) and accuracy (75.1% vs 68.9%, p=0.0009). When we used GAPS, but 'over-ruled' it when clinical certainty was ≥95%, this significantly outperformed either method, with AUC 0.891 (0.877-0.907) and accuracy 82.5% (80.7%-84.2%). CONCLUSIONS: GAPS, a simple clinical score, is a better predictor of admission than triage nurses, unless the nurse is sure about the outcome, in which case their clinical judgement should be respected. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.
Authors: Dominic Jones; Allan Cameron; David J Lowe; Suzanne M Mason; Colin A O'Keeffe; Eilidh Logan Journal: BMJ Open Date: 2019-08-10 Impact factor: 2.692
Authors: Daniel Trotzky; Noaa Shopen; Jonathan Mosery; Neta Negri Galam; Yizhaq Mimran; Daniel Edward Fordham; Shiran Avisar; Aya Cohen; Malka Katz Shalhav; Gal Pachys Journal: BMJ Open Date: 2021-12-09 Impact factor: 2.692