Ardent Health: An AI-Enabled Virtual Care Model, from Pilot to Production

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.

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Publication Details

Journal
Frontiers of Health Services Management
Published
2026-03-04
DOI
https://doi.org/10.1097/hap.0000000000000243
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Ardent Health: An AI-Enabled Virtual Care Model, from Pilot to Production

Anika Gardenhire
Frontiers of Health Services Management
Artificial Intelligence in Healthcare and Education
article

Ardent Health: An AI-Enabled Virtual Care Model, from Pilot to Production

Anika Gardenhire
article en

Abstract

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.

Frontiers of Health Services ManagementVol. 42(3)
Tennessee Department of Health (US)
Decent work and economic growth
Openalex Percentile: Top 37%
Artificial Intelligence in Healthcare and Education
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