SBIR-STTR Award

Hospital operating rooms (OR) are currently under tremendous pressure to maximize patient outcomes and safety while reducing costs. Hospitals that focus on disadvantaged socioeconomic populations are often further burdened to meet these growing demands with a significant lack of resources. The U.S. spent $2.6 trillion on healthcare in 2010 with 56% comprised of healthcare worker wages. Unlike virtually all other sectors, healthcare has experienced no gains in labor productivity over the last 20 years. A healthcare productivity crisis exists, as changing regulatory and insurance standards are complicating delivery of care and increasing documentation burden. Therefore, technology solutions, which use intelligent sensors to reduce manual burden and intelligent algorithms to navigate the complex healthcare operations and logistics, can solve significant unmet productivity challenges and allow clinical staff to focus on patient care, safety, and outcomes. Operating rooms require a complex set of resources, planning, data entry and logistics. Accuracy, speed, and accessibility of information to support real-time changes to planned logistics and operational decision- making significantly impact patient outcomes and safety, clinician and patient satisfaction, and efficiency and cost savings. The operational target is to ensure the patient, surgeon, anesthesiologist, technicians, nurses, janitorial staff, equipment, instruments, supplies, rooms and beds are available at required times and locations. High stress clinical environments, which require dynamic information across stakeholders and resources to make timely and accurate decisions, can significantly benefit from automated sensor inputs and artificial intelligence to minimize manual burden. Therefore, the objective is to develop Whiteboard Coordinator (WC), a software command and control system for hospital operating rooms to reduce manual clinician burden, optimize efficiency, and allow a patient care focus. The technology will integrate sensors and machine learning to detect and track resources for planned surgical events, recognize deviations and delays, and update human, equipment, and facility resource allocation in real-time to maximize efficiency and information accessibility. Significant innovation will differentiate WC from existing dashboard and electronic medical record (EMR) apps. First, an intelligent camera network and machine vision algorithms will automatically detect and update availability and location of OR resources. Secondly, software will automate existing manual documentation procedures that currently take up to 50% of clinician time. Third, while other systems are reactionary and focus on billing documentation, WC machine learning algorithms will facilitate care coordination and parallel workflow to maximize efficient and resource allocation. Finally, WC information will quickly be disseminated to all OR stakeholders (surgeons, nurses, technicians, janitorial staff, etc.) across multiple platforms and devices. Additionally, technology to optimize human and equipment resources can level the playing field for socioeconomic disparate locations to maximize limited resources on patient care and safety. !

Public Health Relevance Statement:
Hospital operating rooms depend on accuracy, speed, and accessibility of information to support real-time changes to planned surgical logistics and operational decisions that significantly impact patient outcomes and safety, clinician and patient satisfaction, and efficiency and cost savings. The objective is to develop, deploy, and demonstrate feasibility of Whiteboard Coordinator, a software command and control system for hospital operating rooms to reduce manual clinician burden, optimize efficiency, and allow a patient care focus. The technology will integrate sensors and machine learning to detect and track resources for planned surgical events, recognize deviations and delays, and update human, equipment, and facility resource allocation in real-time to maximize efficiency and information accessibility.

NIH Spending Category:
Basic Behavioral and Social Science; Behavioral and Social Science; Bioengineering; Clinical Research; Health Disparities; Health Services; Machine Learning and Artificial Intelligence; Networking and Information Technology R&D (NITRD); Patient Safety

Project Terms:
Algorithm Design; Algorithms; Anesthesia procedures; Artificial Intelligence; Attention; Automation; base; Beds; care coordination; care delivery; Caring; Charge; Client satisfaction; Clinical; Complex; Computer software; Computerized Medical Record; cost; Cost Savings; dashboard; Data; Data Set; Day Surgery; Decision Making; Detection; Devices; digital; Documentation; economic impact; Economics; Ensure; Environment; Equipment; Event; experience; Fatigue; feeding; Foundations; Funding Agency; Generations; Health Personnel; Health Services Accessibility; Health system; Healthcare; Hospitals; Human; Human Resources; improved; Individual; innovation; instrument; Insurance; Intelligence; Interruption; Job Satisfaction; Location; Logistics; Machine Learning; machine learning algorithm; machine vision; Manuals; Monitor; Nature; Nurses; Operating Rooms; operation; Operative Surgical Procedures; Outcome; Patient Care; Patient Focused Care; patient safety; Patient-Focused Outcomes; Patients; Phase; Play; Population; pressure; Procedures; Process; Productivity; prototype; Provider; Recommendation; Resource Allocation; Resources; Safety; satisfaction; scalpel; Schedule; sensor; socioeconomic disadvantage; socioeconomics; Speed; Sterility; Stress; success; Surgeon; surgery outcome; Surgical incisions; System; Technology; Testing; Time; tool; Underserved Population; Update; usability; virtual; Wages

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 impactsoutcomes, safety, satisfaction, & access to care. Additionally, increasing efficiency can have a significant positiveeconomic impact, an important implication for all hospitals. Therefore, automation of manual documentation andtask 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'slocal network. It communicates with the existing electronic medical record (EMR) to import the day's surgeryschedule and assigned resources. Once OR workflow begins, an intelligent network of sensors and camerasemploying machine vision algorithms record locations and times of patients, equipment, and supplies. As clinicalactivities begin, the software automatically alerts all stakeholders of important events via text and paging tocoordinate clinical processes. Information is also disseminated on digital displays throughout stakeholderlocations, 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 feedensures all providers are effortlessly informed, allowing all stakeholders to synchronize independent, but parallelworkflows. The intelligent sensor network of cameras and machine vision algorithms automatically detects andupdates 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 featuresto fully support user workflow and efficiency across all OR stakeholders. Targeted updates will focus onconnected data domains and cross platform integration, user interface workflows and automated reports, andvoice command integration. Second, the AI suite will be significantly updated with novel tools that build uponthe 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 beentechnically verified and validated, the supporting infrastructure and production ecosystem will be scaled tosupport commercial release. This includes formal quality functions, operations, support and staging/productionenvironments. The Whiteboard Coordinator platform and production environment will be validated against qualitysystem requirements, then deployed in a large-scale field study to document OR effectiveness and utility.

Public Health Relevance Statement:
The objective is to enhance, scale, and commercially deploy Whiteboard Coordinator, an artificial intelligence (AI) driven software platform for hospital operating rooms (OR) that reduces documentation burden, optimizes workflows and resource planning, and allows clinicians to focus on patient care. The objective is to ensure patient, surgeon, anesthesiologist, technicians, nurses, janitorial staff, equipment, instruments, supplies, rooms and beds are available at required times and locations. Given the number of inputs, complexity of processes, and dynamic temporal adjustments, this high stress clinical environment can strongly benefit from automated monitoring and AI driven coordination.

Project Terms: