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Assessing the completeness of periodontal disease documentation in the EHR: a first step in measuring the quality of care

BACKGROUND: Our objective was to measure the proportion of patients for which comprehensive periodontal charting, periodontal disease risk factors (diabetes status, tobacco use, and oral home care compliance), and periodontal diagnoses were documented in the electronic health record (EHR). We develo...

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Autores principales: Mullins, Joanna, Yansane, Alfa, Kumar, Shwetha V., Bangar, Suhasini, Neumann, Ana, Johnson, Todd R., Olson, Gregory W., Kookal, Krishna Kumar, Sedlock, Emily, Kim, Aram, Mertz, Elizabeth, Brandon, Ryan, Simmons, Kristen, White, Joel M., Kalenderian, Elsbeth, Walji, Muhammad F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8164293/
https://www.ncbi.nlm.nih.gov/pubmed/34051781
http://dx.doi.org/10.1186/s12903-021-01633-w
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author Mullins, Joanna
Yansane, Alfa
Kumar, Shwetha V.
Bangar, Suhasini
Neumann, Ana
Johnson, Todd R.
Olson, Gregory W.
Kookal, Krishna Kumar
Sedlock, Emily
Kim, Aram
Mertz, Elizabeth
Brandon, Ryan
Simmons, Kristen
White, Joel M.
Kalenderian, Elsbeth
Walji, Muhammad F.
author_facet Mullins, Joanna
Yansane, Alfa
Kumar, Shwetha V.
Bangar, Suhasini
Neumann, Ana
Johnson, Todd R.
Olson, Gregory W.
Kookal, Krishna Kumar
Sedlock, Emily
Kim, Aram
Mertz, Elizabeth
Brandon, Ryan
Simmons, Kristen
White, Joel M.
Kalenderian, Elsbeth
Walji, Muhammad F.
author_sort Mullins, Joanna
collection PubMed
description BACKGROUND: Our objective was to measure the proportion of patients for which comprehensive periodontal charting, periodontal disease risk factors (diabetes status, tobacco use, and oral home care compliance), and periodontal diagnoses were documented in the electronic health record (EHR). We developed an EHR-based quality measure to assess how well four dental institutions documented periodontal disease-related information. An automated database script was developed and implemented in the EHR at each institution. The measure was validated by comparing the findings from the measure with a manual review of charts. RESULTS: The overall measure scores varied significantly across the four institutions (institution 1 = 20.47%, institution 2 = 0.97%, institution 3 = 22.27% institution 4 = 99.49%, p-value < 0.0001). The largest gaps in documentation were related to periodontal diagnoses and capturing oral homecare compliance. A random sample of 1224 charts were manually reviewed and showed excellent validity when compared with the data generated from the EHR-based measure (Sensitivity, Specificity, PPV, and NPV > 80%). CONCLUSION: Our results demonstrate the feasibility of developing automated data extraction scripts using structured data from EHRs, and successfully implementing these to identify and measure the periodontal documentation completeness within and across different dental institutions.
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spelling pubmed-81642932021-06-01 Assessing the completeness of periodontal disease documentation in the EHR: a first step in measuring the quality of care Mullins, Joanna Yansane, Alfa Kumar, Shwetha V. Bangar, Suhasini Neumann, Ana Johnson, Todd R. Olson, Gregory W. Kookal, Krishna Kumar Sedlock, Emily Kim, Aram Mertz, Elizabeth Brandon, Ryan Simmons, Kristen White, Joel M. Kalenderian, Elsbeth Walji, Muhammad F. BMC Oral Health Research BACKGROUND: Our objective was to measure the proportion of patients for which comprehensive periodontal charting, periodontal disease risk factors (diabetes status, tobacco use, and oral home care compliance), and periodontal diagnoses were documented in the electronic health record (EHR). We developed an EHR-based quality measure to assess how well four dental institutions documented periodontal disease-related information. An automated database script was developed and implemented in the EHR at each institution. The measure was validated by comparing the findings from the measure with a manual review of charts. RESULTS: The overall measure scores varied significantly across the four institutions (institution 1 = 20.47%, institution 2 = 0.97%, institution 3 = 22.27% institution 4 = 99.49%, p-value < 0.0001). The largest gaps in documentation were related to periodontal diagnoses and capturing oral homecare compliance. A random sample of 1224 charts were manually reviewed and showed excellent validity when compared with the data generated from the EHR-based measure (Sensitivity, Specificity, PPV, and NPV > 80%). CONCLUSION: Our results demonstrate the feasibility of developing automated data extraction scripts using structured data from EHRs, and successfully implementing these to identify and measure the periodontal documentation completeness within and across different dental institutions. BioMed Central 2021-05-29 /pmc/articles/PMC8164293/ /pubmed/34051781 http://dx.doi.org/10.1186/s12903-021-01633-w 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
Mullins, Joanna
Yansane, Alfa
Kumar, Shwetha V.
Bangar, Suhasini
Neumann, Ana
Johnson, Todd R.
Olson, Gregory W.
Kookal, Krishna Kumar
Sedlock, Emily
Kim, Aram
Mertz, Elizabeth
Brandon, Ryan
Simmons, Kristen
White, Joel M.
Kalenderian, Elsbeth
Walji, Muhammad F.
Assessing the completeness of periodontal disease documentation in the EHR: a first step in measuring the quality of care
title Assessing the completeness of periodontal disease documentation in the EHR: a first step in measuring the quality of care
title_full Assessing the completeness of periodontal disease documentation in the EHR: a first step in measuring the quality of care
title_fullStr Assessing the completeness of periodontal disease documentation in the EHR: a first step in measuring the quality of care
title_full_unstemmed Assessing the completeness of periodontal disease documentation in the EHR: a first step in measuring the quality of care
title_short Assessing the completeness of periodontal disease documentation in the EHR: a first step in measuring the quality of care
title_sort assessing the completeness of periodontal disease documentation in the ehr: a first step in measuring the quality of care
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8164293/
https://www.ncbi.nlm.nih.gov/pubmed/34051781
http://dx.doi.org/10.1186/s12903-021-01633-w
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