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Quality assessment of functional status documentation in EHRs across different healthcare institutions

The secondary use of electronic health records (EHRs) faces challenges in the form of varying data quality-related issues. To address that, we retrospectively assessed the quality of functional status documentation in EHRs of persons participating in Mayo Clinic Study of Aging (MCSA). We used a conv...

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Autores principales: Fu, Sunyang, Vassilaki, Maria, Ibrahim, Omar A., Petersen, Ronald C., Pagali, Sandeep, St Sauver, Jennifer, Moon, Sungrim, Wang, Liwei, Fan, Jungwei W., Liu, Hongfang, Sohn, Sunghwan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9552292/
https://www.ncbi.nlm.nih.gov/pubmed/36238199
http://dx.doi.org/10.3389/fdgth.2022.958539
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author Fu, Sunyang
Vassilaki, Maria
Ibrahim, Omar A.
Petersen, Ronald C.
Pagali, Sandeep
St Sauver, Jennifer
Moon, Sungrim
Wang, Liwei
Fan, Jungwei W.
Liu, Hongfang
Sohn, Sunghwan
author_facet Fu, Sunyang
Vassilaki, Maria
Ibrahim, Omar A.
Petersen, Ronald C.
Pagali, Sandeep
St Sauver, Jennifer
Moon, Sungrim
Wang, Liwei
Fan, Jungwei W.
Liu, Hongfang
Sohn, Sunghwan
author_sort Fu, Sunyang
collection PubMed
description The secondary use of electronic health records (EHRs) faces challenges in the form of varying data quality-related issues. To address that, we retrospectively assessed the quality of functional status documentation in EHRs of persons participating in Mayo Clinic Study of Aging (MCSA). We used a convergent parallel design to collect quantitative and qualitative data and independently analyzed the findings. We discovered a heterogeneous documentation process, where the care practice teams, institutions, and EHR systems all play an important role in how text data is documented and organized. Four prevalent instrument-assisted documentation (iDoc) expressions were identified based on three distinct instruments: Epic smart form, questionnaire, and occupational therapy and physical therapy templates. We found strong differences in the usage, information quality (intrinsic and contextual), and naturality of language among different type of iDoc expressions. These variations can be caused by different source instruments, information providers, practice settings, care events and institutions. In addition, iDoc expressions are context specific and thus shall not be viewed and processed uniformly. We recommend conducting data quality assessment of unstructured EHR text prior to using the information.
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spelling pubmed-95522922022-10-12 Quality assessment of functional status documentation in EHRs across different healthcare institutions Fu, Sunyang Vassilaki, Maria Ibrahim, Omar A. Petersen, Ronald C. Pagali, Sandeep St Sauver, Jennifer Moon, Sungrim Wang, Liwei Fan, Jungwei W. Liu, Hongfang Sohn, Sunghwan Front Digit Health Digital Health The secondary use of electronic health records (EHRs) faces challenges in the form of varying data quality-related issues. To address that, we retrospectively assessed the quality of functional status documentation in EHRs of persons participating in Mayo Clinic Study of Aging (MCSA). We used a convergent parallel design to collect quantitative and qualitative data and independently analyzed the findings. We discovered a heterogeneous documentation process, where the care practice teams, institutions, and EHR systems all play an important role in how text data is documented and organized. Four prevalent instrument-assisted documentation (iDoc) expressions were identified based on three distinct instruments: Epic smart form, questionnaire, and occupational therapy and physical therapy templates. We found strong differences in the usage, information quality (intrinsic and contextual), and naturality of language among different type of iDoc expressions. These variations can be caused by different source instruments, information providers, practice settings, care events and institutions. In addition, iDoc expressions are context specific and thus shall not be viewed and processed uniformly. We recommend conducting data quality assessment of unstructured EHR text prior to using the information. Frontiers Media S.A. 2022-09-27 /pmc/articles/PMC9552292/ /pubmed/36238199 http://dx.doi.org/10.3389/fdgth.2022.958539 Text en © 2022 Fu, Vassilaki, Ibrahim, Petersen, Pagali, St Sauver, Moon, Wang, Fan, Liu and Sohn. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (https://creativecommons.org/licenses/by/4.0/) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Digital Health
Fu, Sunyang
Vassilaki, Maria
Ibrahim, Omar A.
Petersen, Ronald C.
Pagali, Sandeep
St Sauver, Jennifer
Moon, Sungrim
Wang, Liwei
Fan, Jungwei W.
Liu, Hongfang
Sohn, Sunghwan
Quality assessment of functional status documentation in EHRs across different healthcare institutions
title Quality assessment of functional status documentation in EHRs across different healthcare institutions
title_full Quality assessment of functional status documentation in EHRs across different healthcare institutions
title_fullStr Quality assessment of functional status documentation in EHRs across different healthcare institutions
title_full_unstemmed Quality assessment of functional status documentation in EHRs across different healthcare institutions
title_short Quality assessment of functional status documentation in EHRs across different healthcare institutions
title_sort quality assessment of functional status documentation in ehrs across different healthcare institutions
topic Digital Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9552292/
https://www.ncbi.nlm.nih.gov/pubmed/36238199
http://dx.doi.org/10.3389/fdgth.2022.958539
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