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Caries Risk Documentation And Prevention: eMeasures For Dental Electronic Health Records

Background  Longitudinal patient level data available in the electronic health record (EHR) allows for the development, implementation, and validations of dental quality measures (eMeasures). Objective  We report the feasibility and validity of implementing two eMeasures. The eMeasures determined th...

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Autores principales: Bangar, Suhasini, Neumann, Ana, White, Joel M., Yansane, Alfa, Johnson, Todd R., Olson, Gregory W., Kumar, Shwetha V., Kookal, Krishna K., Kim, Aram, Obadan-Udoh, Enihomo, Mertz, Elizabeth, Simmons, Kristen, Mullins, Joanna, Brandon, Ryan, Walji, Muhammad F., Kalenderian, Elsbeth
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Georg Thieme Verlag KG 2022
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8769809/
https://www.ncbi.nlm.nih.gov/pubmed/35045582
http://dx.doi.org/10.1055/s-0041-1740920
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author Bangar, Suhasini
Neumann, Ana
White, Joel M.
Yansane, Alfa
Johnson, Todd R.
Olson, Gregory W.
Kumar, Shwetha V.
Kookal, Krishna K.
Kim, Aram
Obadan-Udoh, Enihomo
Mertz, Elizabeth
Simmons, Kristen
Mullins, Joanna
Brandon, Ryan
Walji, Muhammad F.
Kalenderian, Elsbeth
author_facet Bangar, Suhasini
Neumann, Ana
White, Joel M.
Yansane, Alfa
Johnson, Todd R.
Olson, Gregory W.
Kumar, Shwetha V.
Kookal, Krishna K.
Kim, Aram
Obadan-Udoh, Enihomo
Mertz, Elizabeth
Simmons, Kristen
Mullins, Joanna
Brandon, Ryan
Walji, Muhammad F.
Kalenderian, Elsbeth
author_sort Bangar, Suhasini
collection PubMed
description Background  Longitudinal patient level data available in the electronic health record (EHR) allows for the development, implementation, and validations of dental quality measures (eMeasures). Objective  We report the feasibility and validity of implementing two eMeasures. The eMeasures determined the proportion of patients receiving a caries risk assessment (eCRA) and corresponding appropriate risk-based preventative treatments for patients at elevated risk of caries (appropriateness of care [eAoC]) in two academic institutions and one accountable care organization, in the 2019 reporting year. Methods  Both eMeasures define the numerator and denominator beginning at the patient level, populations' specifications, and validated the automated queries. For eCRA, patients who completed a comprehensive or periodic oral evaluation formed the denominator, and patients of any age who received a CRA formed the numerator. The eAoC evaluated the proportion of patients at elevated caries risk who received the corresponding appropriate risk-based preventative treatments. Results  EHR automated queries identified in three sites 269,536 patients who met the inclusion criteria for receiving a CRA. The overall proportion of patients who received a CRA was 94.4% (eCRA). In eAoC, patients at elevated caries risk levels (moderate, high, or extreme) received fluoride preventive treatment ranging from 56 to 93.8%. For patients at high and extreme risk, antimicrobials were prescribed more frequently site 3 (80.6%) than sites 2 (16.7%) and 1 (2.9%). Conclusion  Patient-level data available in the EHRs can be used to implement process-of-care dental eCRA and AoC, eAoC measures identify gaps in clinical practice. EHR-based measures can be useful in improving delivery of evidence-based preventative treatments to reduce risk, prevent tooth decay, and improve oral health.
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spelling pubmed-87698092022-01-21 Caries Risk Documentation And Prevention: eMeasures For Dental Electronic Health Records Bangar, Suhasini Neumann, Ana White, Joel M. Yansane, Alfa Johnson, Todd R. Olson, Gregory W. Kumar, Shwetha V. Kookal, Krishna K. Kim, Aram Obadan-Udoh, Enihomo Mertz, Elizabeth Simmons, Kristen Mullins, Joanna Brandon, Ryan Walji, Muhammad F. Kalenderian, Elsbeth Appl Clin Inform Background  Longitudinal patient level data available in the electronic health record (EHR) allows for the development, implementation, and validations of dental quality measures (eMeasures). Objective  We report the feasibility and validity of implementing two eMeasures. The eMeasures determined the proportion of patients receiving a caries risk assessment (eCRA) and corresponding appropriate risk-based preventative treatments for patients at elevated risk of caries (appropriateness of care [eAoC]) in two academic institutions and one accountable care organization, in the 2019 reporting year. Methods  Both eMeasures define the numerator and denominator beginning at the patient level, populations' specifications, and validated the automated queries. For eCRA, patients who completed a comprehensive or periodic oral evaluation formed the denominator, and patients of any age who received a CRA formed the numerator. The eAoC evaluated the proportion of patients at elevated caries risk who received the corresponding appropriate risk-based preventative treatments. Results  EHR automated queries identified in three sites 269,536 patients who met the inclusion criteria for receiving a CRA. The overall proportion of patients who received a CRA was 94.4% (eCRA). In eAoC, patients at elevated caries risk levels (moderate, high, or extreme) received fluoride preventive treatment ranging from 56 to 93.8%. For patients at high and extreme risk, antimicrobials were prescribed more frequently site 3 (80.6%) than sites 2 (16.7%) and 1 (2.9%). Conclusion  Patient-level data available in the EHRs can be used to implement process-of-care dental eCRA and AoC, eAoC measures identify gaps in clinical practice. EHR-based measures can be useful in improving delivery of evidence-based preventative treatments to reduce risk, prevent tooth decay, and improve oral health. Georg Thieme Verlag KG 2022-01-19 /pmc/articles/PMC8769809/ /pubmed/35045582 http://dx.doi.org/10.1055/s-0041-1740920 Text en The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. ( https://creativecommons.org/licenses/by-nc-nd/4.0/ ) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License, which permits unrestricted reproduction and distribution, for non-commercial purposes only; and use and reproduction, but not distribution, of adapted material for non-commercial purposes only, provided the original work is properly cited.
spellingShingle Bangar, Suhasini
Neumann, Ana
White, Joel M.
Yansane, Alfa
Johnson, Todd R.
Olson, Gregory W.
Kumar, Shwetha V.
Kookal, Krishna K.
Kim, Aram
Obadan-Udoh, Enihomo
Mertz, Elizabeth
Simmons, Kristen
Mullins, Joanna
Brandon, Ryan
Walji, Muhammad F.
Kalenderian, Elsbeth
Caries Risk Documentation And Prevention: eMeasures For Dental Electronic Health Records
title Caries Risk Documentation And Prevention: eMeasures For Dental Electronic Health Records
title_full Caries Risk Documentation And Prevention: eMeasures For Dental Electronic Health Records
title_fullStr Caries Risk Documentation And Prevention: eMeasures For Dental Electronic Health Records
title_full_unstemmed Caries Risk Documentation And Prevention: eMeasures For Dental Electronic Health Records
title_short Caries Risk Documentation And Prevention: eMeasures For Dental Electronic Health Records
title_sort caries risk documentation and prevention: emeasures for dental electronic health records
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8769809/
https://www.ncbi.nlm.nih.gov/pubmed/35045582
http://dx.doi.org/10.1055/s-0041-1740920
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