{"title":"Ardent Health: An AI-Enabled Virtual Care Model, from Pilot to Production.","authors":"Anika Gardenhire","doi":"10.1097/HAP.0000000000000243","DOIUrl":null,"url":null,"abstract":"<p><strong>Summary: </strong>Healthcare leaders face sustained uncertainty: workforce volatility, financial pressure, and accelerating technology change. In 2024-2025, Ardent Health advanced an AI-enabled virtual care model from pilot to production across multiple markets. The model integrates virtual nursing, virtual attending physicians and providers, virtual sitting, and hospital-to-home remote patient monitoring (RPM) into routine care, with artificial intelligence (AI), providing earlier risk detection and workflow relief. Specifically, AI systems (1) analyze video streams to detect fall risks and unsafe behaviors, prompting earlier alerts to staff; (2) continuously evaluate vital sign trends from wearable sensors to identify clinical deterioration sooner; and (3) support ambient documentation with speech recognition and natural language processing (NLP) that improves note quality and coding accuracy.At Ardent's East Texas location, five months of virtual nursing contributed to reductions in contract labor, a decrease in voluntary RN turnover, and improvements in salaries, wages, and benefits (SWB) per patient day despite an increase in volume. Meanwhile, virtual attending physicians and providers increased virtual patient consultations resulting in patient retention and, generated bed-day capacity; AI-assisted vitals monitoring correlated with lower mortality and shorter length of stay; and the RPM program improved discharge continuity and avoided readmissions.This article presents a case study and playbook to help leaders manage risk, scale safely, and measure value. Readiness includes updating consent form language; data-use and retention policies; training staff to obtain patient consent; establishing algorithm oversight with internal data, analytics, and data science capabilities; and investing in network, data center, and hardware upgrades. We close with lessons learned and an organizational performance tracking accountability structure.</p>","PeriodicalId":39916,"journal":{"name":"Frontiers of Health Services Management","volume":"42 3","pages":"26-32"},"PeriodicalIF":0.0000,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers of Health Services Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1097/HAP.0000000000000243","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 0
Abstract
Summary: Healthcare leaders face sustained uncertainty: workforce volatility, financial pressure, and accelerating technology change. In 2024-2025, Ardent Health advanced an AI-enabled virtual care model from pilot to production across multiple markets. The model integrates virtual nursing, virtual attending physicians and providers, virtual sitting, and hospital-to-home remote patient monitoring (RPM) into routine care, with artificial intelligence (AI), providing earlier risk detection and workflow relief. Specifically, AI systems (1) analyze video streams to detect fall risks and unsafe behaviors, prompting earlier alerts to staff; (2) continuously evaluate vital sign trends from wearable sensors to identify clinical deterioration sooner; and (3) support ambient documentation with speech recognition and natural language processing (NLP) that improves note quality and coding accuracy.At Ardent's East Texas location, five months of virtual nursing contributed to reductions in contract labor, a decrease in voluntary RN turnover, and improvements in salaries, wages, and benefits (SWB) per patient day despite an increase in volume. Meanwhile, virtual attending physicians and providers increased virtual patient consultations resulting in patient retention and, generated bed-day capacity; AI-assisted vitals monitoring correlated with lower mortality and shorter length of stay; and the RPM program improved discharge continuity and avoided readmissions.This article presents a case study and playbook to help leaders manage risk, scale safely, and measure value. Readiness includes updating consent form language; data-use and retention policies; training staff to obtain patient consent; establishing algorithm oversight with internal data, analytics, and data science capabilities; and investing in network, data center, and hardware upgrades. We close with lessons learned and an organizational performance tracking accountability structure.
期刊介绍:
Disaster preparedness. The future of health professions. Workforce shortages. Alternative medicine. You want to understand the latest trends, but you don"t always have time for books. Magazines don"t give you quite enough information. Keeping up doesn"t have to be difficult. Frontiers can bring you up to speed quickly. Frontiers" unique "bookazine" format gives you the deep understanding gained from books but in a shorter format, like a magazine. Each issue focuses on one healthcare management topic, providing you with the knowledge you need to understand and react to evolving trends. Frontiers is written by experts on the topic and includes commentary from the field.