Whiteboard Coordinator: Intelligent Sensor Network and Machine Learning toImprove Operating Room Outcomes and Efficiency

NIH RePORTER · NIH · R44 · $837,789 · view on reporter.nih.gov ↗

Abstract

Caring for patients in the operating room (OR) requires a complex set of resources, personnel, and logistics. Improving the accuracy, speed, and granularity of information exchange in this environment significantly impacts outcomes, safety, satisfaction, & access to care. Additionally, increasing efficiency can have a significant positive economic impact, an important implication for all hospitals. Therefore, automation of manual documentation and task coordination can enhance productivity, safety, and profitability, as well as job satisfaction for clinicians. The Whiteboard Coordinator (WC) platform solves these market challenges through artificial intelligence (AI) driven OR workflows and resource management. The platform is deployed on a virtual server within a hospital’s local network. It communicates with the existing electronic medical record (EMR) to import the day’s surgery schedule and assigned resources. Once OR workflow begins, an intelligent network of sensors and cameras employing machine vision algorithms record locations and times of patients, equipment, and supplies. As clinical activities begin, the software automatically alerts all stakeholders of important events via text and paging to coordinate clinical processes. Information is also disseminated on digital displays throughout stakeholder locations, such as the OR, preoperative holding, post anesthesia care unit, sterile supply, high-traffic hallways, and break rooms. Given the unpredictable nature of surgical procedures, this automated information feed ensures all providers are effortlessly informed, allowing all stakeholders to synchronize independent, but parallel workflows. The intelligent sensor network of cameras and machine vision algorithms automatically detects and updates availability and location of resources. The software automates existing manual logistics documentation. Finally, WC rapidly disseminates detailed information in a targeted manner (i.e. to specific surgeons, nurses, technicians, janitorial staff, etc.) to eliminate alarm fatigue and enhance productivity. The project includes four main aims. First, the Phase I prototype platform will be enhanced with new features to fully support user workflow and efficiency across all OR stakeholders. Targeted updates will focus on connected data domains and cross platform integration, user interface workflows and automated reports, and voice command integration. Second, the AI suite will be significantly updated with novel tools that build upon the Phase I framework including detection of novel surgery types & events, detection of surgical supplies & inventory management, and a simulation toolbox for resource planning. Once all platform updates have been technically verified and validated, the supporting infrastructure and production ecosystem will be scaled to support commercial release. This includes formal quality functions, operations, support and staging/production environments. The Whiteboard Coordinator pl...

Key facts

NIH application ID
10319306
Project number
2R44LM013026-02A1
Recipient
ARTISIGHT, INC.
Principal Investigator
Andrew Gostine
Activity code
R44
Funding institute
NIH
Fiscal year
2021
Award amount
$837,789
Award type
2
Project period
2019-08-01 → 2023-07-31