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Adoption Factors of the Electronic Health Record: A Systematic Review
BACKGROUND: The Health Information Technology for Economic and Clinical Health (HITECH) was a significant piece of legislation in America that served as a catalyst for the adoption of health information technology. Following implementation of the HITECH Act, Health Information Technology (HIT) exper...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4909978/ https://www.ncbi.nlm.nih.gov/pubmed/27251559 http://dx.doi.org/10.2196/medinform.5525 |
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author | Kruse, Clemens Scott Kothman, Krysta Anerobi, Keshia Abanaka, Lillian |
author_facet | Kruse, Clemens Scott Kothman, Krysta Anerobi, Keshia Abanaka, Lillian |
author_sort | Kruse, Clemens Scott |
collection | PubMed |
description | BACKGROUND: The Health Information Technology for Economic and Clinical Health (HITECH) was a significant piece of legislation in America that served as a catalyst for the adoption of health information technology. Following implementation of the HITECH Act, Health Information Technology (HIT) experienced broad adoption of Electronic Health Records (EHR), despite skepticism exhibited by many providers for the transition to an electronic system. A thorough review of EHR adoption facilitator and barriers provides ongoing support for the continuation of EHR implementation across various health care structures, possibly leading to a reduction in associated economic expenditures. OBJECTIVE: The purpose of this review is to compile a current and comprehensive list of facilitators and barriers to the adoption of the EHR in the United States. METHODS: Authors searched Cumulative Index of Nursing and Allied Health Literature (CINAHL) and MEDLINE, 01/01/2012–09/01/2015, core clinical/academic journals, MEDLINE full text, and evaluated only articles germane to our research objective. Team members selected a final list of articles through consensus meetings (n=31). Multiple research team members thoroughly read each article to confirm applicability and study conclusions, thereby increasing validity. RESULTS: Group members identified common facilitators and barriers associated with the EHR adoption process. In total, 25 adoption facilitators were identified in the literature occurring 109 times; the majority of which were efficiency, hospital size, quality, access to data, perceived value, and ability to transfer information. A total of 23 barriers to adoption were identified in the literature, appearing 95 times; the majority of which were cost, time consuming, perception of uselessness, transition of data, facility location, and implementation issues. CONCLUSIONS: The 25 facilitators and 23 barriers to the adoption of the EHR continue to reveal a preoccupation on cost, despite incentives in the HITECH Act. Limited financial backing and outdated technology were also common barriers frequently mentioned during data review. Future public policy should include incentives commensurate with those in the HITECH Act to maintain strong adoption rates. |
format | Online Article Text |
id | pubmed-4909978 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-49099782016-06-28 Adoption Factors of the Electronic Health Record: A Systematic Review Kruse, Clemens Scott Kothman, Krysta Anerobi, Keshia Abanaka, Lillian JMIR Med Inform Original Paper BACKGROUND: The Health Information Technology for Economic and Clinical Health (HITECH) was a significant piece of legislation in America that served as a catalyst for the adoption of health information technology. Following implementation of the HITECH Act, Health Information Technology (HIT) experienced broad adoption of Electronic Health Records (EHR), despite skepticism exhibited by many providers for the transition to an electronic system. A thorough review of EHR adoption facilitator and barriers provides ongoing support for the continuation of EHR implementation across various health care structures, possibly leading to a reduction in associated economic expenditures. OBJECTIVE: The purpose of this review is to compile a current and comprehensive list of facilitators and barriers to the adoption of the EHR in the United States. METHODS: Authors searched Cumulative Index of Nursing and Allied Health Literature (CINAHL) and MEDLINE, 01/01/2012–09/01/2015, core clinical/academic journals, MEDLINE full text, and evaluated only articles germane to our research objective. Team members selected a final list of articles through consensus meetings (n=31). Multiple research team members thoroughly read each article to confirm applicability and study conclusions, thereby increasing validity. RESULTS: Group members identified common facilitators and barriers associated with the EHR adoption process. In total, 25 adoption facilitators were identified in the literature occurring 109 times; the majority of which were efficiency, hospital size, quality, access to data, perceived value, and ability to transfer information. A total of 23 barriers to adoption were identified in the literature, appearing 95 times; the majority of which were cost, time consuming, perception of uselessness, transition of data, facility location, and implementation issues. CONCLUSIONS: The 25 facilitators and 23 barriers to the adoption of the EHR continue to reveal a preoccupation on cost, despite incentives in the HITECH Act. Limited financial backing and outdated technology were also common barriers frequently mentioned during data review. Future public policy should include incentives commensurate with those in the HITECH Act to maintain strong adoption rates. JMIR Publications 2016-06-01 /pmc/articles/PMC4909978/ /pubmed/27251559 http://dx.doi.org/10.2196/medinform.5525 Text en ©Clemens Scott Kruse, Krysta Kothman, Keshia Anerobi, Lillian Abanaka. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 01.06.2016. https://creativecommons.org/licenses/by/2.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/ (https://creativecommons.org/licenses/by/2.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Medical Informatics, is properly cited. The complete bibliographic information, a link to the original publication on http://medinform.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Kruse, Clemens Scott Kothman, Krysta Anerobi, Keshia Abanaka, Lillian Adoption Factors of the Electronic Health Record: A Systematic Review |
title | Adoption Factors of the Electronic Health Record: A Systematic Review |
title_full | Adoption Factors of the Electronic Health Record: A Systematic Review |
title_fullStr | Adoption Factors of the Electronic Health Record: A Systematic Review |
title_full_unstemmed | Adoption Factors of the Electronic Health Record: A Systematic Review |
title_short | Adoption Factors of the Electronic Health Record: A Systematic Review |
title_sort | adoption factors of the electronic health record: a systematic review |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4909978/ https://www.ncbi.nlm.nih.gov/pubmed/27251559 http://dx.doi.org/10.2196/medinform.5525 |
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