| Title: |
Real-time prediction of patient disposition and the impact of reporter confidence on mid-level triage accuracies: an observational study in Israel |
| Authors: |
Daniel Trotzky; Noaa Shopen; Jonathan Mosery; Neta Negri Galam; Yizhaq Mimran; Daniel Edward Fordham; Shiran Avisar; Aya Cohen; Malka Katz Shalhav; Gal Pachys |
| Source: |
BMJ Open, Vol 11, Iss 12 (2021) |
| Publisher Information: |
BMJ Publishing Group |
| Publication Year: |
2021 |
| Collection: |
Directory of Open Access Journals: DOAJ Articles |
| Subject Terms: |
Medicine |
| Description: |
Aim The emergency department (ED) is the first port-of-call for most patients receiving hospital care and as such acts as a gatekeeper to the wards, directing patient flow through the hospital. ED overcrowding is a well-researched field and negatively affects patient outcome, staff well-being and hospital reputation. An accurate, real-time model capable of predicting ED overcrowding has obvious merit in a world becoming increasingly computational, although the complicated dynamics of the department have hindered international efforts to design such a model. Triage nurses’ assessments have been shown to be accurate predictors of patient disposition and could, therefore, be useful input for overcrowding and patient flow models.Methods In this study, we assess the prediction capabilities of triage nurses in a level 1 urban hospital in central Israeli. ED settings included both acute and ambulatory wings. Nurses were asked to predict admission or discharge for each patient over a 3-month period as well as exact admission destination. Prediction confidence was used as an optimisation variable.Result Triage nurses accurately predicted whether the patient would be admitted or discharged in 77% of patients in the acute wing, rising to 88% when their prediction certainty was high. Accuracies were higher still for patients in the ambulatory wing. In particular, negative predictive values for admission were highly accurate at 90%, irrespective of area or certainty levels.Conclusion Nurses prediction of disposition should be considered for input for real-time ED models. |
| Document Type: |
article in journal/newspaper |
| Language: |
English |
| Relation: |
https://bmjopen.bmj.com/content/11/12/e050026.full; https://doaj.org/toc/2044-6055; https://doaj.org/article/dd3023e9fa704a3a858a389f109fc13a |
| DOI: |
10.1136/bmjopen-2021-050026 |
| Availability: |
https://doi.org/10.1136/bmjopen-2021-050026; https://doaj.org/article/dd3023e9fa704a3a858a389f109fc13a |
| Accession Number: |
edsbas.EC573E1C |
| Database: |
BASE |