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dc.contributor.advisorThomas Heldt.en_US
dc.contributor.authorHensley, Sarah (Sarah L.)en_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.en_US
dc.date.accessioned2019-01-03T20:55:53Z
dc.date.available2019-01-03T20:55:53Z
dc.date.copyright2018en_US
dc.date.issued2018en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/119844
dc.descriptionThesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.en_US
dc.descriptionThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.en_US
dc.descriptionCataloged from student-submitted PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 71-73).en_US
dc.description.abstractBecause the vast majority of monitoring alarms in the adult intensive care unit (ICU) do not require intervention, care providers are slow to respond to all alarms, endangering patients. We collect, characterize, and analyze alarms, alarm annotations provided by clinical staff while responding to alarms, and physiological data from a community hospital ICU. In order to suggest opportunities for suppressing irrelevant alarms, we examine monitoring device coverage across patients and analyze the alarms observed by device, priority, and type. On average, we observe 196.3 alarms per patient-day, for a total of 23,057 alarms. From these, the electrocardiogram and pulse plethysmogram produce 86.1% of all alarms. The lowest priority alarms represent 81.1% of all alarms, while the highest priority alarms compose just 5.5% of the total. While the rate of annotations is low, also just 5.5% of possible alarms, it is comparable to the rate of care provider interactions with alarms, as measured by alarm silencing, at 9.6%. Using these annotations, we find -- surprisingly -- that the annotated nuisance threshold-violation alarms tend to have higher excursions than actionable and advisory alarms, offering a statistic for separation. When focusing on threshold-crossing alarms, we find that 22.5% of Heart Rate Low alarms may actually indicate device error. Among ST segment alarms, 44.4% occur simultaneously with at least one other ST segment alarm, producing redundant alarms. Addressing these issues represent strategies for reducing excessive alarms in this community hospital cohort of ICU patients.en_US
dc.description.statementofresponsibilityby Sarah Hensley.en_US
dc.format.extent73 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectElectrical Engineering and Computer Science.en_US
dc.titleCharacterization of monitoring alarms in a community hospital intensive care uniten_US
dc.typeThesisen_US
dc.description.degreeM. Eng.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.identifier.oclc1078699106en_US


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