Use of artificial intelligence for reverse referral between a hospital emergency department and a primary urgent care center.

IF 3.2 Q1 HEALTH CARE SCIENCES & SERVICES

Frontiers in digital health Pub Date : 2025-03-03 eCollection Date: 2025-01-01 DOI:10.3389/fdgth.2025.1546467

Yolanda Taules, Silvia Gros, Maria Viladrosa, Natàlia Llorens, Sílvia Solis, Oriol Yuguero

{"title":"Use of artificial intelligence for reverse referral between a hospital emergency department and a primary urgent care center.","authors":"Yolanda Taules, Silvia Gros, Maria Viladrosa, Natàlia Llorens, Sílvia Solis, Oriol Yuguero","doi":"10.3389/fdgth.2025.1546467","DOIUrl":null,"url":null,"abstract":"Background: The demand for immediate care in emergency departments (EDs) has risen since the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic.Objective: Test the ability of AI to promote reverse referral and to provide patient education.Methods: Pilot study that included patients presenting to our Hospital Emergency Department (HED) with a non severe disease and who met the inclusion criteria. The participants were asked to answer a series of questions using an electronic device and receive a recommendation for health attention. Then, patients could choose to either remain in the hospital or leave.Results: 427 patients finally participated in the pilot study. Within this population, 49.5% were women, and the mean patient age was 37.5 years. Mediktor recommended reverse referral to urgent care in 43.6%. Our results demonstrate that the tool is safe and provides accurate patient screening, correctly distinguishing between those who should continue to wait for HED care and those for whom an urgent care center is adequate.","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":"7 ","pages":"1546467"},"PeriodicalIF":3.2000,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11911458/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in digital health","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3389/fdgth.2025.1546467","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}

引用次数: 0

Abstract

Background: The demand for immediate care in emergency departments (EDs) has risen since the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic.

Objective: Test the ability of AI to promote reverse referral and to provide patient education.

Methods: Pilot study that included patients presenting to our Hospital Emergency Department (HED) with a non severe disease and who met the inclusion criteria. The participants were asked to answer a series of questions using an electronic device and receive a recommendation for health attention. Then, patients could choose to either remain in the hospital or leave.

Results: 427 patients finally participated in the pilot study. Within this population, 49.5% were women, and the mean patient age was 37.5 years. Mediktor recommended reverse referral to urgent care in 43.6%. Our results demonstrate that the tool is safe and provides accurate patient screening, correctly distinguishing between those who should continue to wait for HED care and those for whom an urgent care center is adequate.

查看原文本刊更多论文

使用人工智能在医院急诊科和初级紧急护理中心之间进行反向转诊。

背景：自严重急性呼吸综合征冠状病毒2 （SARS-CoV-2）大流行以来，急诊科（EDs）的即时护理需求有所上升。目的：检验人工智能促进逆向转诊和患者教育的能力。方法：初步研究纳入到我院急诊科（HED）就诊的非严重疾病且符合纳入标准的患者。参与者被要求使用电子设备回答一系列问题，并收到有关健康注意的建议。然后，患者可以选择留在医院或离开。结果：427例患者最终参与了前期研究。在该人群中，49.5%为女性，患者平均年龄为37.5岁。医生建议转介到紧急护理的占43.6%。我们的研究结果表明，该工具是安全的，并提供准确的患者筛选，正确区分那些应该继续等待HED护理的患者和那些需要紧急护理中心的患者。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊