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dc.contributor.advisorWilliam T. Lester.en_US
dc.contributor.authorMeyer, Mark A. (Mark Aaron)en_US
dc.contributor.otherHarvard University--MIT Division of Health Sciences and Technology.en_US
dc.date.accessioned2007-01-10T16:30:47Z
dc.date.available2007-01-10T16:30:47Z
dc.date.copyright2006en_US
dc.date.issued2006en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/35517
dc.descriptionThesis (S.M.)--Harvard-MIT Division of Health Sciences and Technology, 2006.en_US
dc.descriptionIncludes bibliographical references (leaves 33-35).en_US
dc.description.abstractLocation tracking systems in healthcare produce a wealth of data applicable across many aspects of care and management. However, since dedicated location tracking systems, such as the oft mentioned RFID tracking system, are still sparsely deployed, a number of other data sources may be utilized to serve as a proxy for physical location, such as barcodes and manual timestamp entry, and may be better suited to indicate progress through clinical workflows. INCOMING!, a web-based platform that monitors and tracks patient progress from the operating room to the post-anesthesia care unit (PACU), is one such system that utilizes manual timestamps routinely entered as standard process of care in the operating room in order to track a patient's progress through the post-operative period. This integrated real time system facilitates patient flow between the PACU and the surgical ward and eases PACU workload by reducing the effort of discharging patients.en_US
dc.description.abstract(cont.) We have also developed a larger-scale integrated system for perioperative processes that integrates perioperative data from anesthesia and surgical devices and operating room (OR) / hospital information systems, and projects the real-time integrated data as a single, unified, easy to visualize display. The need to optimize perioperative throughput creates a demand for integration of the datastreams and for timely data presentation. The system provides improved context-sensitive information display, improved real-time monitoring of physiological data, real-time access to readiness information, and improved workflow management. These systems provide improved data access and utilization, providing context-aware applications in healthcare that are aware of a user's location, environment, needs, and goals.en_US
dc.description.statementofresponsibilityby Mark A. Meyer.en_US
dc.format.extent35 leavesen_US
dc.format.extent3044532 bytes
dc.format.extent3042483 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypeapplication/pdf
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582
dc.subjectHarvard University--MIT Division of Health Sciences and Technology.en_US
dc.titleUse of location data for the surveillance, analysis, and optimization of clinical processesen_US
dc.typeThesisen_US
dc.description.degreeS.M.en_US
dc.contributor.departmentHarvard University--MIT Division of Health Sciences and Technology
dc.identifier.oclc71824247en_US


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