{"response":{"award":[{"abstractText":"The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is widespread adoption of a technology with a direct cost-­savings in healthcare. It is estimated that nearly 5,000 patients are harmed each year due to wrong-patient errors in medical imaging. Additionally, even a 10% improvement in efficiency in radiologists' performance would translate to ~$900 million savings to the overall health care budget. Finally, an indirect, but impactful outcome is the potential to improve the relevance and accuracy of medical imaging reports. It is anticipated that pairing the medical imaging studies to the patient photographs of the patient's face and upper body, where tubes and wires are often located, can provide important clinical information in a rapid and efficient manner. In the broadest terms, this novel technology can be translated to provide patient authentication and identification for the digital data that is being generated by hundreds of new medical devices. \r\n\r\nThe proposed project concerns the seamless integration of a patient Identification system in hospitals to improve patient safety and radiology throughput. The intellectual merit of this work is a transformative approach overcoming the failure of existing patient identification methods while harnessing the power of an embedded camera system to improve patient care. Toward this goal this work will develop an imaging synchronization technology that automatically obtains and embeds a photograph of the patient's face and upper body onto the x-ray taken during an imaging examination. To test and establish feasibility, the initial target of this technology will be portable x-ray machines brought to the patient's bedside in high volume settings. Specifically, the proposed work will 1) incorporate face-­tracking technology to ensure the patient's face and torso are always captured by the camera, 2) conduct a feasibly study in a real-world setting by deploying the technology on ~6 portable radiography machines at a large academic hospital where it will be integrated with the hospital's Picture Archiving and Communication System (PACS), and 3) perform preliminary workflow studies. The long term objectives are to 1) increase the detection rate of wrong-­patient errors by embedding an intrinsic, externally visible biometric identifier with medical imaging studies; and 2) decrease turn-­around time by decreasing interpretation time.","activeAwd":"false","agency":"NSF","awardAgencyCode":"4900","awardee":"CAMERAD TECHNOLOGIES, LLC","awardeeAddress":"2098 SYLVANIA DR","awardeeCity":"DECATUR","awardeeCountryCode":"US","awardeeDistrict":"04","awardeeDistrictCode":"GA04","awardeeName":"Camerad Technologies, LLC","awardeePhone":"7349457692","awardeeStateCode":"GA","awardeeZipCode":"30033","cfdaNumber":"47.084","date":"12/14/2016","dirAbbr":"TIP","divAbbr":"TI","estimatedTotalAmt":"225000","expDate":"06/30/2018","fundAgencyCode":"4900","fundProgramName":"SBIR Phase I","fundsObligated":["FY 2017 = $225,000.00"],"fundsObligatedAmt":"225000","histAwd":"false","id":"1647687","initAmendmentDate":"12/14/2016","latestAmendmentDate":"04/27/2018","managingPec":"537100","orgCodeDir":"15000000","orgCodeDiv":"15030000","orgLongName":"Directorate for Technology, Innovation, and Partnerships","orgLongName2":"Translational Impacts","orgUrl":"https://beta.nsf.gov/tip/ti","parentUeiNumber":"","pdPIName":"Carson A Wick","perfAddress":"537 S WESTMINSTER WAY NE","perfCity":"ATLANTA","perfCountryCode":"US","perfDistrict":"05","perfDistrictCode":"GA05","perfLocation":"Camerad Technologies, LLC","perfStateCode":"GA","perfZipCode":"303071190","pi":["Carson A Wick carsonwick@gmail.com"],"piEmail":"carsonwick@gmail.com","piFirstName":"Carson","piId":"269985259","piLastName":"Wick","piMiddeInitial":"A","poEmail":"","poName":"Nancy Kamei","poPhone":"","primaryProgram":["01001718DB NSF RESEARCH & RELATED ACTIVIT"],"progEleCode":"537100","program":"SMALL BUSINESS PHASE I, Smart and Connected Health, Health Care Enterprise Systems, Software Services and Applications, Health and Safety","progRefCode":"5371, 8018, 8023, 8032, 8042","projectOutComesReport":"
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Medical errors will cause roughly 12% of the deaths in the US this year. To place this in context, 0.1% of deaths annually are caused by motor vehicle crashes. Within the field of medical imaging or radiology, “wrong-patient” errors—where one patient’s imaging studies are placed in another patient’s electronic health record—can lead to serious problems for both patients. Furthermore, wrong-patient errors expose healthcare providers to severe litigation risks and reputational damage.

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Intellectual Merit: Camerad Technologies, through its PatCam system, provides radiologists with additional patient identification (ID) in the form of a facial and chest photograph. As a result of the SBIR Phase I effort, a PatCam prototype was developed that automatically captures the patient’s photo simultaneously with his/her X-ray, securely transmits the photographs, and adds these photographs to portable X-Ray studies for view by the radiologist. Through integration with a live radiology workflow at the Emory University Hospital, Atlanta, GA, radiologists and X-Ray technologists experienced the utility of PatCam. Within the first 8,000 combined X-Ray and photograph examinations, two wrong-patient errors were uncovered, and the photographs were useful in identifying the correct patient. In addition, radiologists identified numerous additional use cases where the technology will provide information that was not previously readily available to them during interpretation. This information is obtained from point-of-care patient photographs that were, until now, non-existent.

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Broader Impacts: The PatCam is scalable and has been built as a plug-and-play system. Its initial deployment is a direct fit to existing portable X-ray machines in carefully selected potential beta sites at a range of medical centers in the US, which are likely to be early adopters. Extending the use of PatCam to additional medical imaging applications, a proof-of-concept PatCam for integration with Computed Tomography equipment was pursued during the award.

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It is very encouraging that the PatCam system was useful in identifying and rectifying two wrong-patient errors in the initial pilot testing, suggesting that the problem of wrong-patient errors is a substantial problem and PatCam can effectively address it. In addition, the photographs provide image-related clinical context, which can influence X-ray interpretation and thus impact patient care.


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\n\t\t\t\t \tLast Modified: 07/18/2018
\n\t\t\t\t\tModified by: Carson A Wick

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    The X-ray PatCam installed: (a) Raspberry Pi Zero W and wide-angle camera, (b) X-ray PatCam, (c) PatCam installed on X-ray head, and (d) PatCam trigger unit.
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    The PatCam
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    Example of synchronously-acquired patient X-ray and photograph as viewed by radiologists on a workstation. This is only an example and X-rays and photographs can be viewed on any workstation. Note, the patient?s face is blurred here for privacy reasons but not in clinical deployment.
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    Camerad Technologies, LLC
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    Example Radiologist Workstation View
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","publicAccessMandate":"1","startDate":"12/15/2016","title":"SBIR Phase I: Integrating Patient Photographs with Medical Imaging Examinations to Reduce Medical Errors","transType":"Standard Grant","ueiNumber":"GE7MEN1LVLR9"}],"metadata":{"offset":0,"rpp":25,"totalCount":1}}}