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

> **NIH NIH R44** · ARTISIGHT, INC. · 2021 · $837,789

## 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 organization:** ARTISIGHT, INC.
- **Principal Investigator:** Andrew Gostine
- **Activity code:** R44 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $837,789
- **Award type:** 2
- **Project period:** 2019-08-01 → 2023-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10319306

## Citation

> US National Institutes of Health, RePORTER application 10319306, Whiteboard Coordinator: Intelligent Sensor Network and Machine Learning toImprove Operating Room Outcomes and Efficiency (2R44LM013026-02A1). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10319306. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*