{"id":{"repo_id":"unr","oai_identifier":"oai:scholarwolf.unr.edu:11714/2207"},"canonical_url":"https://search.dev.ndltd.org/etd/unr/oai:scholarwolf.unr.edu:11714/2207","repository":{"repo_id":"unr","name":"University of Nevada - Reno","base_url":"https://scholarwolf.unr.edu/server/oai/request"},"display":{"title":"Does Health Information Technology Improve Hospital Process Measures?","abstract":"The Health Information Technology for Economic and Clinical Health Act of 2009 (HITECH) incentivizes hospitals to utilize health information technology (HIT), including electronic medical records (EMR) and health information exchange (HIE). Hospitals have responded by increasing the implementation and utilization of these technologies. Numerous studies have analyzed the impact of increased EMR and the results have been mixed. In this paper, I use a fixed effects regression model and national administrative and survey data to also analyze the effect of increased HIE. The impacts of EMR and HIE vary by hospital type. These findings suggest that \"meaningful use\" standards are not optimally designed. Policymakers should change their regulatory approach to allow for variation in EMR and HIE impacts across different hospital types.","abstract_html":"The Health Information Technology for Economic and Clinical Health Act of 2009 (HITECH) incentivizes hospitals to utilize health information technology (HIT), including electronic medical records (EMR) and health information exchange (HIE). Hospitals have responded by increasing the implementation and utilization of these technologies. Numerous studies have analyzed the impact of increased EMR and the results have been mixed. In this paper, I use a fixed effects regression model and national administrative and survey data to also analyze the effect of increased HIE. The impacts of EMR and HIE vary by hospital type. These findings suggest that "meaningful use" standards are not optimally designed. Policymakers should change their regulatory approach to allow for variation in EMR and HIE impacts across different hospital types.","abstract_has_math":false,"creators":["Osborne, Nathan"],"institution":null,"degree_name":null,"degree_level":"Master's Degree","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Wendel, Jeanne"],"committee_chairs":[],"committee_members":["Mukhopadhyay, Sankar","Edberg, Dana"],"year":2015,"date_issued":"2015","date_published":"2015","updated_at":"2026-07-27T21:45:34Z","subjects":["Electronic Medical Records (EMR)","Fixed Effects","Health Information Exchange (HIE)","Health Information Technology (HIT)","Process Measures"],"languages":[],"rights":["In Copyright(All Rights Reserved)"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/11714/2207","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Wendel, Jeanne"]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Mukhopadhyay, Sankar","Edberg, Dana"]},{"key":"dc:creator","label":"Author","values":["Osborne, Nathan"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2017-10-25T17:19:40Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2017-10-25T17:19:40Z"]},{"key":"dc:date.issued","label":"Date","values":["2015"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Master's Degree"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Electronic Medical Records (EMR)","Fixed Effects","Health Information Exchange (HIE)","Health Information Technology (HIT)","Process Measures"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["In Copyright(All Rights Reserved)"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/11714/2207"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["The Health Information Technology for Economic and Clinical Health Act of 2009 (HITECH) incentivizes hospitals to utilize health information technology (HIT), including electronic medical records (EMR) and health information exchange (HIE). Hospitals have responded by increasing the implementation and utilization of these technologies. Numerous studies have analyzed the impact of increased EMR and the results have been mixed. In this paper, I use a fixed effects regression model and national administrative and survey data to also analyze the effect of increased HIE. The impacts of EMR and HIE vary by hospital type. These findings suggest that \"meaningful use\" standards are not optimally designed. Policymakers should change their regulatory approach to allow for variation in EMR and HIE impacts across different hospital types."]},{"key":"dc:format","label":"Dc Format","values":["PDF"]},{"key":"dc:title","label":"Title","values":["Does Health Information Technology Improve Hospital Process Measures?"]}]}],"canonical_facts":{"dc:contributor.advisor":["Wendel, Jeanne"],"dc:contributor.committeemember":["Mukhopadhyay, Sankar","Edberg, Dana"],"dc:creator":["Osborne, Nathan"],"dc:date.accessioned":["2017-10-25T17:19:40Z"],"dc:date.available":["2017-10-25T17:19:40Z"],"dc:date.issued":["2015"],"dc:description.abstract":["The Health Information Technology for Economic and Clinical Health Act of 2009 (HITECH) incentivizes hospitals to utilize health information technology (HIT), including electronic medical records (EMR) and health information exchange (HIE). Hospitals have responded by increasing the implementation and utilization of these technologies. Numerous studies have analyzed the impact of increased EMR and the results have been mixed. In this paper, I use a fixed effects regression model and national administrative and survey data to also analyze the effect of increased HIE. The impacts of EMR and HIE vary by hospital type. These findings suggest that \"meaningful use\" standards are not optimally designed. Policymakers should change their regulatory approach to allow for variation in EMR and HIE impacts across different hospital types."],"dc:format":["PDF"],"dc:identifier.uri":["http://hdl.handle.net/11714/2207"],"dc:rights":["In Copyright(All Rights Reserved)"],"dc:subject":["Electronic Medical Records (EMR)","Fixed Effects","Health Information Exchange (HIE)","Health Information Technology (HIT)","Process Measures"],"dc:title":["Does Health Information Technology Improve Hospital Process Measures?"],"dc:type":["Thesis"],"thesis:degree_level":["Master's Degree"]},"updated_at":"2026-07-27T21:45:34Z"}