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Electronic medical record implementation in tertiary care: factors influencing adoption of an electronic medical record in a cancer centre
BACKGROUND: Electronic Medical Records (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, researchers and other key stakeholders. However, effective...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7789279/ https://www.ncbi.nlm.nih.gov/pubmed/33407449 http://dx.doi.org/10.1186/s12913-020-06015-6 |
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author | Janssen, Anna Donnelly, Candice Elder, Elisabeth Pathmanathan, Nirmala Shaw, Tim |
author_facet | Janssen, Anna Donnelly, Candice Elder, Elisabeth Pathmanathan, Nirmala Shaw, Tim |
author_sort | Janssen, Anna |
collection | PubMed |
description | BACKGROUND: Electronic Medical Records (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, researchers and other key stakeholders. However, effective implementation has proved challenging. METHODS: A qualitative methodology was used in the study. Interviews were conducted with 12 clinical and administrative staff of a cancer centre at one-month pre-launch and eight clinical and administrative staff at 12-months post-launch of an EMR. Data from the interviews was collected via audio recording. Audio recordings were transcribed, de-identified and analysed to identify staff experiences with the EMR. RESULTS: Data from the pre-implementation interviews were grouped into four categories: 1) Awareness and understanding of EMR; 2) Engagement in launch process; 3) Standardisation and completeness of data; 4) Effect on workload. Data from the post-launch interviews were grouped into six categories: 1) Standardisation 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. Two categories: Standardisation and completeness of data and effect on workload were common across pre and post-implementation interviews. CONCLUSION: 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 once the EMR has launched, health professional perception the EMR increases workload, and the learning curve for staff adequately familiarize themselves with using the EMR. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-020-06015-6. |
format | Online Article Text |
id | pubmed-7789279 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-77892792021-01-07 Electronic medical record implementation in tertiary care: factors influencing adoption of an electronic medical record in a cancer centre Janssen, Anna Donnelly, Candice Elder, Elisabeth Pathmanathan, Nirmala Shaw, Tim BMC Health Serv Res Research Article BACKGROUND: Electronic Medical Records (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, researchers and other key stakeholders. However, effective implementation has proved challenging. METHODS: A qualitative methodology was used in the study. Interviews were conducted with 12 clinical and administrative staff of a cancer centre at one-month pre-launch and eight clinical and administrative staff at 12-months post-launch of an EMR. Data from the interviews was collected via audio recording. Audio recordings were transcribed, de-identified and analysed to identify staff experiences with the EMR. RESULTS: Data from the pre-implementation interviews were grouped into four categories: 1) Awareness and understanding of EMR; 2) Engagement in launch process; 3) Standardisation and completeness of data; 4) Effect on workload. Data from the post-launch interviews were grouped into six categories: 1) Standardisation 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. Two categories: Standardisation and completeness of data and effect on workload were common across pre and post-implementation interviews. CONCLUSION: 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 once the EMR has launched, health professional perception the EMR increases workload, and the learning curve for staff adequately familiarize themselves with using the EMR. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-020-06015-6. BioMed Central 2021-01-06 /pmc/articles/PMC7789279/ /pubmed/33407449 http://dx.doi.org/10.1186/s12913-020-06015-6 Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Janssen, Anna Donnelly, Candice Elder, Elisabeth Pathmanathan, Nirmala Shaw, Tim Electronic medical record implementation in tertiary care: factors influencing adoption of an electronic medical record in a cancer centre |
title | Electronic medical record implementation in tertiary care: factors influencing adoption of an electronic medical record in a cancer centre |
title_full | Electronic medical record implementation in tertiary care: factors influencing adoption of an electronic medical record in a cancer centre |
title_fullStr | Electronic medical record implementation in tertiary care: factors influencing adoption of an electronic medical record in a cancer centre |
title_full_unstemmed | Electronic medical record implementation in tertiary care: factors influencing adoption of an electronic medical record in a cancer centre |
title_short | Electronic medical record implementation in tertiary care: factors influencing adoption of an electronic medical record in a cancer centre |
title_sort | electronic medical record implementation in tertiary care: factors influencing adoption of an electronic medical record in a cancer centre |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7789279/ https://www.ncbi.nlm.nih.gov/pubmed/33407449 http://dx.doi.org/10.1186/s12913-020-06015-6 |
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