Artisight, Inc. — Department of Health and Human Services SBIR Phase I: NLM

Description

Hospital operating roomsORare currently under tremendous pressure to maximize patient outcomes and safety while reducing costsHospitals that focus on disadvantaged socioeconomic populations are often further burdened to meet these growing demands with a significant lack of resourcesThe U Sspent $trillion on healthcare inwithcomprised of healthcare worker wagesUnlike virtually all other sectorshealthcare has experienced no gains in labor productivity over the lastyearsA healthcare productivity crisis existsas changing regulatory and insurance standards are complicating delivery of care and increasing documentation burdenThereforetechnology solutionswhich use intelligent sensors to reduce manual burden and intelligent algorithms to navigate the complex healthcare operations and logisticscan solve significant unmet productivity challenges and allow clinical staff to focus on patient caresafetyand outcomesOperating rooms require a complex set of resourcesplanningdata entry and logisticsAccuracyspeedand accessibility of information to support real time changes to planned logistics and operational decisionmaking significantly impact patient outcomes and safetyclinician and patient satisfactionand efficiency and cost savingsThe operational target is to ensure the patientsurgeonanesthesiologisttechniciansnursesjanitorial staffequipmentinstrumentssuppliesrooms and beds are available at required times and locationsHigh stress clinical environmentswhich require dynamic information across stakeholders and resources to make timely and accurate decisionscan significantly benefit from automated sensor inputs and artificial intelligence to minimize manual burdenThereforethe objective is to develop Whiteboard CoordinatorWCa software command and control system for hospital operating rooms to reduce manual clinician burdenoptimize efficiencyand allow a patient care focusThe technology will integrate sensors and machine learning to detect and track resources for planned surgical eventsrecognize deviations and delaysand update humanequipmentand facility resource allocation in real time to maximize efficiency and information accessibilitySignificant innovation will differentiate WC from existing dashboard and electronic medical recordEMRappsFirstan intelligent camera network and machine vision algorithms will automatically detect and update availability and location of OR resourcesSecondlysoftware will automate existing manual documentation procedures that currently take up toof clinician timeThirdwhile other systems are reactionary and focus on billing documentationWC machine learning algorithms will facilitate care coordination and parallel workflow to maximize efficient and resource allocationFinallyWC information will quickly be disseminated to all OR stakeholderssurgeonsnursestechniciansjanitorial staffetcacross multiple platforms and devicesAdditionallytechnology to optimize human and equipment resources can level the playing field for socioeconomic disparate locations to maximize limited resources on patient care and safety!Hospital operating rooms depend on accuracyspeedand accessibility of information to support real time changes to planned surgical logistics and operational decisions that significantly impact patient outcomes and safetyclinician and patient satisfactionand efficiency and cost savingsThe objective is to developdeployand demonstrate feasibility of Whiteboard Coordinatora software command and control system for hospital operating rooms to reduce manual clinician burdenoptimize efficiencyand allow a patient care focusThe technology will integrate sensors and machine learning to detect and track resources for planned surgical eventsrecognize deviations and delaysand update humanequipmentand facility resource allocation in real time to maximize efficiency and information accessibility