Factors Influencing Implementation of an Electronic Medical Record in a Tertiary Cancer Centre.
Clinical informatics
EMR
evidence based practice
Journal
Studies in health technology and informatics
ISSN: 1879-8365
Titre abrégé: Stud Health Technol Inform
Pays: Netherlands
ID NLM: 9214582
Informations de publication
Date de publication:
08 Aug 2019
08 Aug 2019
Historique:
entrez:
10
8
2019
pubmed:
10
8
2019
medline:
11
9
2019
Statut:
ppublish
Résumé
EMRs are one of a range of digital health solutions that are key enablers of the data revolution transforming the health sector. They offer a wide range of benefits to health professionals, patients and other key stakeholders. However, effective implementation has proved challenging. A qualitative methodology was used in the study. Interviews were conducted with members of a cancer team 12 months post-implementation of an EMR. Data from the interviews was collected via audio recording. Audio recordings were transcribed, de-identified and analyzed to identify the experiences of staff with the EMR. Data was categorized in to six categories: 1) Standardisation of documentation and completeness of data; 2) Effect on workload; 3) Feature completeness and functionality; 4) Interaction with technical support; 5) Learning curve; 6) Buy-in from staff. Findings from this study contribute new knowledge on barriers and enablers to the implementation of EMRs in complex clinical settings. Barriers to successful implementation include lack of technical support, perceived increase in workload and a learning curve to fully familiarize with the feature set of the EMR.
Sections du résumé
BACKGROUND
BACKGROUND
EMRs are one of a range of digital health solutions that are key enablers of the data revolution transforming the health sector. They offer a wide range of benefits to health professionals, patients and other key stakeholders. However, effective implementation has proved challenging.
METHOD
METHODS
A qualitative methodology was used in the study. Interviews were conducted with members of a cancer team 12 months post-implementation of an EMR. Data from the interviews was collected via audio recording. Audio recordings were transcribed, de-identified and analyzed to identify the experiences of staff with the EMR.
FINDINGS
RESULTS
Data was categorized in to six categories: 1) Standardisation of documentation and completeness of data; 2) Effect on workload; 3) Feature completeness and functionality; 4) Interaction with technical support; 5) Learning curve; 6) Buy-in from staff.
CONCLUSIONS & IMPLICATIONS
CONCLUSIONS
Findings from this study contribute new knowledge on barriers and enablers to the implementation of EMRs in complex clinical settings. Barriers to successful implementation include lack of technical support, perceived increase in workload and a learning curve to fully familiarize with the feature set of the EMR.
Identifiants
pubmed: 31397308
pii: SHTI190779
doi: 10.3233/SHTI190779
doi:
Types de publication
Journal Article
Langues
eng