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Assessing the quality of electronic medical records as a platform for resident education

BACKGROUND: Previous studies have assessed note quality and the use of electronic medical record (EMR) as a part of medical training. However, a generalized and user-friendly note quality assessment tool is required for quick clinical assessment. We held a medical record writing competition and deve...

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Autores principales: Hung, Hsuan, Kueh, Ling-Ling, Tseng, Chin-Chung, Huang, Han-Wei, Wang, Shu-Yen, Hu, Yu-Ning, Lin, Pao-Yen, Wang, Jiun-Ling, Chen, Po-Fan, Liu, Ching-Chuan, Roan, Jun-Neng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8590775/
https://www.ncbi.nlm.nih.gov/pubmed/34774027
http://dx.doi.org/10.1186/s12909-021-03011-0
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author Hung, Hsuan
Kueh, Ling-Ling
Tseng, Chin-Chung
Huang, Han-Wei
Wang, Shu-Yen
Hu, Yu-Ning
Lin, Pao-Yen
Wang, Jiun-Ling
Chen, Po-Fan
Liu, Ching-Chuan
Roan, Jun-Neng
author_facet Hung, Hsuan
Kueh, Ling-Ling
Tseng, Chin-Chung
Huang, Han-Wei
Wang, Shu-Yen
Hu, Yu-Ning
Lin, Pao-Yen
Wang, Jiun-Ling
Chen, Po-Fan
Liu, Ching-Chuan
Roan, Jun-Neng
author_sort Hung, Hsuan
collection PubMed
description BACKGROUND: Previous studies have assessed note quality and the use of electronic medical record (EMR) as a part of medical training. However, a generalized and user-friendly note quality assessment tool is required for quick clinical assessment. We held a medical record writing competition and developed a checklist for assessing the note quality of participants’ medical records. Using the checklist, this study aims to explore note quality between residents of different specialties and offer pedagogical implications. METHODS: The authors created an inpatient checklist that examined fundamental EMR requirements through six note types and twenty items. A total of 149 records created by residents from 32 departments/stations were randomly selected. Seven senior physicians rated the EMRs using a checklist. Medical records were grouped as general medicine, surgery, paediatric, obstetrics and gynaecology, and other departments. The overall and group performances were analysed using analysis of variance (ANOVA). RESULTS: Overall performance was rated as fair to good. Regarding the six note types, discharge notes (0.81) gained the highest scores, followed by admission notes (0.79), problem list (0.73), overall performance (0.73), progress notes (0.71), and weekly summaries (0.66). Among the five groups, other departments (80.20) had the highest total score, followed by obstetrics and gynaecology (78.02), paediatrics (77.47), general medicine (75.58), and surgery (73.92). CONCLUSIONS: This study suggested that duplication in medical notes and the documentation abilities of residents affect the quality of medical records in different departments. Further research is required to apply the insights obtained in this study to improve the quality of notes and, thereby, the effectiveness of resident training. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12909-021-03011-0.
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spelling pubmed-85907752021-11-15 Assessing the quality of electronic medical records as a platform for resident education Hung, Hsuan Kueh, Ling-Ling Tseng, Chin-Chung Huang, Han-Wei Wang, Shu-Yen Hu, Yu-Ning Lin, Pao-Yen Wang, Jiun-Ling Chen, Po-Fan Liu, Ching-Chuan Roan, Jun-Neng BMC Med Educ Research BACKGROUND: Previous studies have assessed note quality and the use of electronic medical record (EMR) as a part of medical training. However, a generalized and user-friendly note quality assessment tool is required for quick clinical assessment. We held a medical record writing competition and developed a checklist for assessing the note quality of participants’ medical records. Using the checklist, this study aims to explore note quality between residents of different specialties and offer pedagogical implications. METHODS: The authors created an inpatient checklist that examined fundamental EMR requirements through six note types and twenty items. A total of 149 records created by residents from 32 departments/stations were randomly selected. Seven senior physicians rated the EMRs using a checklist. Medical records were grouped as general medicine, surgery, paediatric, obstetrics and gynaecology, and other departments. The overall and group performances were analysed using analysis of variance (ANOVA). RESULTS: Overall performance was rated as fair to good. Regarding the six note types, discharge notes (0.81) gained the highest scores, followed by admission notes (0.79), problem list (0.73), overall performance (0.73), progress notes (0.71), and weekly summaries (0.66). Among the five groups, other departments (80.20) had the highest total score, followed by obstetrics and gynaecology (78.02), paediatrics (77.47), general medicine (75.58), and surgery (73.92). CONCLUSIONS: This study suggested that duplication in medical notes and the documentation abilities of residents affect the quality of medical records in different departments. Further research is required to apply the insights obtained in this study to improve the quality of notes and, thereby, the effectiveness of resident training. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12909-021-03011-0. BioMed Central 2021-11-13 /pmc/articles/PMC8590775/ /pubmed/34774027 http://dx.doi.org/10.1186/s12909-021-03011-0 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://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
Hung, Hsuan
Kueh, Ling-Ling
Tseng, Chin-Chung
Huang, Han-Wei
Wang, Shu-Yen
Hu, Yu-Ning
Lin, Pao-Yen
Wang, Jiun-Ling
Chen, Po-Fan
Liu, Ching-Chuan
Roan, Jun-Neng
Assessing the quality of electronic medical records as a platform for resident education
title Assessing the quality of electronic medical records as a platform for resident education
title_full Assessing the quality of electronic medical records as a platform for resident education
title_fullStr Assessing the quality of electronic medical records as a platform for resident education
title_full_unstemmed Assessing the quality of electronic medical records as a platform for resident education
title_short Assessing the quality of electronic medical records as a platform for resident education
title_sort assessing the quality of electronic medical records as a platform for resident education
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8590775/
https://www.ncbi.nlm.nih.gov/pubmed/34774027
http://dx.doi.org/10.1186/s12909-021-03011-0
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