Eintrag weiter verarbeiten
Understanding optimisation processes of electronic health records (EHRs) in select leading hospitals: a qualitative study
Gespeichert in:
Zeitschriftentitel: | BMJ Health & Care Informatics |
---|---|
Personen und Körperschaften: | , , |
In: | BMJ Health & Care Informatics, 25, 2018, 2, S. 109-125 |
Medientyp: | E-Article |
Sprache: | Englisch |
veröffentlicht: |
BMJ
|
Schlagwörter: |
author_facet |
Moon, Mark Chun Hills, Rebecca Demiris, George Moon, Mark Chun Hills, Rebecca Demiris, George |
---|---|
author |
Moon, Mark Chun Hills, Rebecca Demiris, George |
spellingShingle |
Moon, Mark Chun Hills, Rebecca Demiris, George BMJ Health & Care Informatics Understanding optimisation processes of electronic health records (EHRs) in select leading hospitals: a qualitative study Health Information Management Health Informatics Computer Science Applications |
author_sort |
moon, mark chun |
spelling |
Moon, Mark Chun Hills, Rebecca Demiris, George 2632-1009 BMJ Health Information Management Health Informatics Computer Science Applications http://dx.doi.org/10.14236/jhi.v25i2.1011 <jats:sec><jats:title>Background</jats:title><jats:p>Little is known about optimisation of electronic health records (EHRs) systems in the hospital setting while adoption of EHR systems continues in the United States.</jats:p></jats:sec><jats:sec><jats:title>Objective</jats:title><jats:p>To understand optimisation processes of EHR systems undertaken in leading healthcare organisations in the United States.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>Informed by a grounded theory approach, a qualitative study was undertaken that involved 11 in-depth interviews and a focus group with the EHR experts from the high performing healthcare organisations across the United States.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>The study describes EHR optimisation processes characterised by prioritising exponentially increasing requests with predominant focus on improving efficiency of EHR, building optimisation teams or advisory groups and standardisation. The study discusses 16 types of optimisation that interdependently produced 16 results along with identifying 11 barriers and 20 facilitators to optimisation.</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>The study describes overall experiences of optimising EHRs in select high performing healthcare organisations in the US. The findings highlight the importance of optimising the EHR after, and even before, go-live and dedicating resources exclusively for optimisation.</jats:p></jats:sec> Understanding optimisation processes of electronic health records (EHRs) in select leading hospitals: a qualitative study BMJ Health & Care Informatics |
doi_str_mv |
10.14236/jhi.v25i2.1011 |
facet_avail |
Online Free |
finc_class_facet |
Medizin Informatik |
format |
ElectronicArticle |
fullrecord |
blob:ai-49-aHR0cDovL2R4LmRvaS5vcmcvMTAuMTQyMzYvamhpLnYyNWkyLjEwMTE |
id |
ai-49-aHR0cDovL2R4LmRvaS5vcmcvMTAuMTQyMzYvamhpLnYyNWkyLjEwMTE |
institution |
DE-Zwi2 DE-D161 DE-Gla1 DE-Zi4 DE-15 DE-Rs1 DE-Pl11 DE-105 DE-14 DE-Ch1 DE-L229 DE-D275 DE-Bn3 DE-Brt1 |
imprint |
BMJ, 2018 |
imprint_str_mv |
BMJ, 2018 |
issn |
2632-1009 |
issn_str_mv |
2632-1009 |
language |
English |
mega_collection |
BMJ (CrossRef) |
match_str |
moon2018understandingoptimisationprocessesofelectronichealthrecordsehrsinselectleadinghospitalsaqualitativestudy |
publishDateSort |
2018 |
publisher |
BMJ |
recordtype |
ai |
record_format |
ai |
series |
BMJ Health & Care Informatics |
source_id |
49 |
title |
Understanding optimisation processes of electronic health records (EHRs) in select leading hospitals: a qualitative study |
title_unstemmed |
Understanding optimisation processes of electronic health records (EHRs) in select leading hospitals: a qualitative study |
title_full |
Understanding optimisation processes of electronic health records (EHRs) in select leading hospitals: a qualitative study |
title_fullStr |
Understanding optimisation processes of electronic health records (EHRs) in select leading hospitals: a qualitative study |
title_full_unstemmed |
Understanding optimisation processes of electronic health records (EHRs) in select leading hospitals: a qualitative study |
title_short |
Understanding optimisation processes of electronic health records (EHRs) in select leading hospitals: a qualitative study |
title_sort |
understanding optimisation processes of electronic health records (ehrs) in select leading hospitals: a qualitative study |
topic |
Health Information Management Health Informatics Computer Science Applications |
url |
http://dx.doi.org/10.14236/jhi.v25i2.1011 |
publishDate |
2018 |
physical |
109-125 |
description |
<jats:sec><jats:title>Background</jats:title><jats:p>Little is known about optimisation of electronic health records (EHRs) systems in the hospital setting while adoption of EHR systems continues in the United States.</jats:p></jats:sec><jats:sec><jats:title>Objective</jats:title><jats:p>To understand optimisation processes of EHR systems undertaken in leading healthcare organisations in the United States.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>Informed by a grounded theory approach, a qualitative study was undertaken that involved 11 in-depth interviews and a focus group with the EHR experts from the high performing healthcare organisations across the United States.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>The study describes EHR optimisation processes characterised by prioritising exponentially increasing requests with predominant focus on improving efficiency of EHR, building optimisation teams or advisory groups and standardisation. The study discusses 16 types of optimisation that interdependently produced 16 results along with identifying 11 barriers and 20 facilitators to optimisation.</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>The study describes overall experiences of optimising EHRs in select high performing healthcare organisations in the US. The findings highlight the importance of optimising the EHR after, and even before, go-live and dedicating resources exclusively for optimisation.</jats:p></jats:sec> |
container_issue |
2 |
container_start_page |
109 |
container_title |
BMJ Health & Care Informatics |
container_volume |
25 |
format_de105 |
Article, E-Article |
format_de14 |
Article, E-Article |
format_de15 |
Article, E-Article |
format_de520 |
Article, E-Article |
format_de540 |
Article, E-Article |
format_dech1 |
Article, E-Article |
format_ded117 |
Article, E-Article |
format_degla1 |
E-Article |
format_del152 |
Buch |
format_del189 |
Article, E-Article |
format_dezi4 |
Article |
format_dezwi2 |
Article, E-Article |
format_finc |
Article, E-Article |
format_nrw |
Article, E-Article |
_version_ |
1792339265364951041 |
geogr_code |
not assigned |
last_indexed |
2024-03-01T15:45:21.311Z |
geogr_code_person |
not assigned |
openURL |
url_ver=Z39.88-2004&ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fvufind.svn.sourceforge.net%3Agenerator&rft.title=Understanding+optimisation+processes+of+electronic+health+records+%28EHRs%29+in+select+leading+hospitals%3A+a+qualitative+study&rft.date=2018-04-01&genre=article&issn=2632-1009&volume=25&issue=2&spage=109&epage=125&pages=109-125&jtitle=BMJ+Health+%26+Care+Informatics&atitle=Understanding+optimisation+processes+of+electronic+health+records+%28EHRs%29+in+select+leading+hospitals%3A+a+qualitative+study&aulast=Demiris&aufirst=George&rft_id=info%3Adoi%2F10.14236%2Fjhi.v25i2.1011&rft.language%5B0%5D=eng |
SOLR | |
_version_ | 1792339265364951041 |
author | Moon, Mark Chun, Hills, Rebecca, Demiris, George |
author_facet | Moon, Mark Chun, Hills, Rebecca, Demiris, George, Moon, Mark Chun, Hills, Rebecca, Demiris, George |
author_sort | moon, mark chun |
container_issue | 2 |
container_start_page | 109 |
container_title | BMJ Health & Care Informatics |
container_volume | 25 |
description | <jats:sec><jats:title>Background</jats:title><jats:p>Little is known about optimisation of electronic health records (EHRs) systems in the hospital setting while adoption of EHR systems continues in the United States.</jats:p></jats:sec><jats:sec><jats:title>Objective</jats:title><jats:p>To understand optimisation processes of EHR systems undertaken in leading healthcare organisations in the United States.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>Informed by a grounded theory approach, a qualitative study was undertaken that involved 11 in-depth interviews and a focus group with the EHR experts from the high performing healthcare organisations across the United States.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>The study describes EHR optimisation processes characterised by prioritising exponentially increasing requests with predominant focus on improving efficiency of EHR, building optimisation teams or advisory groups and standardisation. The study discusses 16 types of optimisation that interdependently produced 16 results along with identifying 11 barriers and 20 facilitators to optimisation.</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>The study describes overall experiences of optimising EHRs in select high performing healthcare organisations in the US. The findings highlight the importance of optimising the EHR after, and even before, go-live and dedicating resources exclusively for optimisation.</jats:p></jats:sec> |
doi_str_mv | 10.14236/jhi.v25i2.1011 |
facet_avail | Online, Free |
finc_class_facet | Medizin, Informatik |
format | ElectronicArticle |
format_de105 | Article, E-Article |
format_de14 | Article, E-Article |
format_de15 | Article, E-Article |
format_de520 | Article, E-Article |
format_de540 | Article, E-Article |
format_dech1 | Article, E-Article |
format_ded117 | Article, E-Article |
format_degla1 | E-Article |
format_del152 | Buch |
format_del189 | Article, E-Article |
format_dezi4 | Article |
format_dezwi2 | Article, E-Article |
format_finc | Article, E-Article |
format_nrw | Article, E-Article |
geogr_code | not assigned |
geogr_code_person | not assigned |
id | ai-49-aHR0cDovL2R4LmRvaS5vcmcvMTAuMTQyMzYvamhpLnYyNWkyLjEwMTE |
imprint | BMJ, 2018 |
imprint_str_mv | BMJ, 2018 |
institution | DE-Zwi2, DE-D161, DE-Gla1, DE-Zi4, DE-15, DE-Rs1, DE-Pl11, DE-105, DE-14, DE-Ch1, DE-L229, DE-D275, DE-Bn3, DE-Brt1 |
issn | 2632-1009 |
issn_str_mv | 2632-1009 |
language | English |
last_indexed | 2024-03-01T15:45:21.311Z |
match_str | moon2018understandingoptimisationprocessesofelectronichealthrecordsehrsinselectleadinghospitalsaqualitativestudy |
mega_collection | BMJ (CrossRef) |
physical | 109-125 |
publishDate | 2018 |
publishDateSort | 2018 |
publisher | BMJ |
record_format | ai |
recordtype | ai |
series | BMJ Health & Care Informatics |
source_id | 49 |
spelling | Moon, Mark Chun Hills, Rebecca Demiris, George 2632-1009 BMJ Health Information Management Health Informatics Computer Science Applications http://dx.doi.org/10.14236/jhi.v25i2.1011 <jats:sec><jats:title>Background</jats:title><jats:p>Little is known about optimisation of electronic health records (EHRs) systems in the hospital setting while adoption of EHR systems continues in the United States.</jats:p></jats:sec><jats:sec><jats:title>Objective</jats:title><jats:p>To understand optimisation processes of EHR systems undertaken in leading healthcare organisations in the United States.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>Informed by a grounded theory approach, a qualitative study was undertaken that involved 11 in-depth interviews and a focus group with the EHR experts from the high performing healthcare organisations across the United States.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>The study describes EHR optimisation processes characterised by prioritising exponentially increasing requests with predominant focus on improving efficiency of EHR, building optimisation teams or advisory groups and standardisation. The study discusses 16 types of optimisation that interdependently produced 16 results along with identifying 11 barriers and 20 facilitators to optimisation.</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>The study describes overall experiences of optimising EHRs in select high performing healthcare organisations in the US. The findings highlight the importance of optimising the EHR after, and even before, go-live and dedicating resources exclusively for optimisation.</jats:p></jats:sec> Understanding optimisation processes of electronic health records (EHRs) in select leading hospitals: a qualitative study BMJ Health & Care Informatics |
spellingShingle | Moon, Mark Chun, Hills, Rebecca, Demiris, George, BMJ Health & Care Informatics, Understanding optimisation processes of electronic health records (EHRs) in select leading hospitals: a qualitative study, Health Information Management, Health Informatics, Computer Science Applications |
title | Understanding optimisation processes of electronic health records (EHRs) in select leading hospitals: a qualitative study |
title_full | Understanding optimisation processes of electronic health records (EHRs) in select leading hospitals: a qualitative study |
title_fullStr | Understanding optimisation processes of electronic health records (EHRs) in select leading hospitals: a qualitative study |
title_full_unstemmed | Understanding optimisation processes of electronic health records (EHRs) in select leading hospitals: a qualitative study |
title_short | Understanding optimisation processes of electronic health records (EHRs) in select leading hospitals: a qualitative study |
title_sort | understanding optimisation processes of electronic health records (ehrs) in select leading hospitals: a qualitative study |
title_unstemmed | Understanding optimisation processes of electronic health records (EHRs) in select leading hospitals: a qualitative study |
topic | Health Information Management, Health Informatics, Computer Science Applications |
url | http://dx.doi.org/10.14236/jhi.v25i2.1011 |