Using Artificial Intelligence to Scale Quality Assurance Monitoring of Home Health Wound Care Program

May 16, 2024|Published Research

HealingIndex SAWC Spring 2024

This poster was featured at SAWC Spring 2024 in Orlando, Florida.

Authors: Rober D. J. Fraser, Rishabh Gupta, Kathleen Corcoran, Angela Graham, Shivika Singal, Kyle Lavergne, HebaTallah Mohammed, Amy Cassata 

Introduction: A pilot study was conducted by CenterWell to enhance the quality of wound care using Swift Medical’s HealingIndex™, an AI tool using deep learning and predictive features to identify healing trajectories to flag deteriorating wounds.  

Objective and methods: The pilot study aimed to identify wounds that exhibited deteriorating characteristics despite being documented as improving. A report then flagged the wound evaluations for further review by branch managers. 595 wound evaluations marked as improving were scanned by HealingIndex™ and 4.5% of the assessments were sent for further review. Additionally, an online survey collected feedback from clinicians and branch managers to assess their satisfaction. 


  • 52% of the escalation reports were confirmed by reviewing clinicians that the wound was deteriorating rather than improving. 
  • 33% of the escalation reports highlighted the need for quality improvement, such as additional education for the clinician on documentation. 
  • The home health staff reported 86% satisfaction with the overall experience, 86% believed the reports contributed to the efficiency of patient care and 86% believed the reports contributed to more effective care coordination. 

To learn more about the research conducted for this poster, or to speak with the Swift Medical team about digital wound care, contact us

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