{"id":{"repo_id":"gmu","oai_identifier":"oai:MARS:1920/8353"},"canonical_url":"https://search.dev.ndltd.org/etd/gmu/oai:MARS:1920/8353","repository":{"repo_id":"gmu","name":"George Mason University","base_url":"https://mars.gmu.edu/server/oai/request"},"display":{"title":"Integrating Telemedicine For Disaster Response: Testing The Emergency Telemedicine Technology Acceptance Model","abstract":"There is little evidence that technology acceptance is well understood in healthcare. The hospital environment is complex and dynamic creating a challenge when new technology is introduced because it impacts current processes and workflows which can significantly affect patient care delivery and outcomes. This study tested the effect of the Emergency Telemedicine Technology Acceptance Model (ETTAM) to predict technology acceptance scores. Managing surge capacity, a sudden increase of severely injured patients during a disaster, is a critical global issue. Mobile telemedicine was introduced into emergency departments in multiple hospital systems for activation during a simulated mass casualty incident (MCI) to leverage clinical expertise and to manage surge capacity. The success of this program was dependent on the user's acceptance of the technology. The Simulation Telemedicine Acceptance Tool (STAT) was adapted to measure technology acceptance scores.","abstract_html":"There is little evidence that technology acceptance is well understood in healthcare. The hospital environment is complex and dynamic creating a challenge when new technology is introduced because it impacts current processes and workflows which can significantly affect patient care delivery and outcomes. This study tested the effect of the Emergency Telemedicine Technology Acceptance Model (ETTAM) to predict technology acceptance scores. Managing surge capacity, a sudden increase of severely injured patients during a disaster, is a critical global issue. Mobile telemedicine was introduced into emergency departments in multiple hospital systems for activation during a simulated mass casualty incident (MCI) to leverage clinical expertise and to manage surge capacity. The success of this program was dependent on the user's acceptance of the technology. The Simulation Telemedicine Acceptance Tool (STAT) was adapted to measure technology acceptance scores.","abstract_has_math":false,"creators":["Davis, Theresa Marie"],"institution":null,"degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2013,"date_issued":"2013-08","date_published":"2013-08","updated_at":"2026-07-27T19:51:46Z","subjects":["Educational technology","Health sciences","Biomedical engineering","Diffusion of Innovation","Disaster Response","Mass Casualty Incident","Technology Acceptance Model","TeleICU","Telemedicine"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["hdl:1920/8353"],"render_values":[{"text":"hdl:1920/8353","href":null,"code":true}]}]},"links":{"outbound_url":null,"outbound_label":null,"outbound_source":null},"metadata_groups":[{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.issued","label":"Date","values":["2013-08"]},{"key":"dc:type","label":"Dc Type","values":["Dissertation"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Educational technology","Health sciences","Biomedical engineering","Diffusion of Innovation","Disaster Response","Mass Casualty Incident","Technology Acceptance Model","TeleICU","Telemedicine"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["hdl:1920/8353"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.other","label":"Dc Description Other","values":["There is little evidence that technology acceptance is well understood in healthcare. The hospital environment is complex and dynamic creating a challenge when new technology is introduced because it impacts current processes and workflows which can significantly affect patient care delivery and outcomes. This study tested the effect of the Emergency Telemedicine Technology Acceptance Model (ETTAM) to predict technology acceptance scores. Managing surge capacity, a sudden increase of severely injured patients during a disaster, is a critical global issue. Mobile telemedicine was introduced into emergency departments in multiple hospital systems for activation during a simulated mass casualty incident (MCI) to leverage clinical expertise and to manage surge capacity. The success of this program was dependent on the user's acceptance of the technology. The Simulation Telemedicine Acceptance Tool (STAT) was adapted to measure technology acceptance scores."]},{"key":"dc:title","label":"Title","values":["Integrating Telemedicine For Disaster Response: Testing The Emergency Telemedicine Technology Acceptance Model"]}]}],"canonical_facts":{"dc:date.issued":["2013-08"],"dc:description.other":["There is little evidence that technology acceptance is well understood in healthcare. The hospital environment is complex and dynamic creating a challenge when new technology is introduced because it impacts current processes and workflows which can significantly affect patient care delivery and outcomes. This study tested the effect of the Emergency Telemedicine Technology Acceptance Model (ETTAM) to predict technology acceptance scores. Managing surge capacity, a sudden increase of severely injured patients during a disaster, is a critical global issue. Mobile telemedicine was introduced into emergency departments in multiple hospital systems for activation during a simulated mass casualty incident (MCI) to leverage clinical expertise and to manage surge capacity. The success of this program was dependent on the user's acceptance of the technology. The Simulation Telemedicine Acceptance Tool (STAT) was adapted to measure technology acceptance scores."],"dc:identifier":["hdl:1920/8353"],"dc:subject":["Educational technology","Health sciences","Biomedical engineering","Diffusion of Innovation","Disaster Response","Mass Casualty Incident","Technology Acceptance Model","TeleICU","Telemedicine"],"dc:title":["Integrating Telemedicine For Disaster Response: Testing The Emergency Telemedicine Technology Acceptance Model"],"dc:type":["Dissertation"]},"updated_at":"2026-07-27T19:51:46Z"}