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Using Clinical Data Standards to Measure Quality: A New Approach
Background Value-based payment for care requires the consistent, objective calculation of care quality. Previous initiatives to calculate ambulatory quality measures have relied on billing data or individual electronic health records (EHRs) to calculate and report performance. New methods for quali...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Schattauer GmbH
2018
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5999523/ https://www.ncbi.nlm.nih.gov/pubmed/29898468 http://dx.doi.org/10.1055/s-0038-1656548 |
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author | D'Amore, John D. Li, Chun McCrary, Laura Niloff, Jonathan M. Sittig, Dean F. McCoy, Allison B. Wright, Adam |
author_facet | D'Amore, John D. Li, Chun McCrary, Laura Niloff, Jonathan M. Sittig, Dean F. McCoy, Allison B. Wright, Adam |
author_sort | D'Amore, John D. |
collection | PubMed |
description | Background Value-based payment for care requires the consistent, objective calculation of care quality. Previous initiatives to calculate ambulatory quality measures have relied on billing data or individual electronic health records (EHRs) to calculate and report performance. New methods for quality measure calculation promoted by federal regulations allow qualified clinical data registries to report quality outcomes based on data aggregated across facilities and EHRs using interoperability standards. Objective This research evaluates the use of clinical document interchange standards as the basis for quality measurement. Methods Using data on 1,100 patients from 11 ambulatory care facilities and 5 different EHRs, challenges to quality measurement are identified and addressed for 17 certified quality measures. Results Iterative solutions were identified for 14 measures that improved patient inclusion and measure calculation accuracy. Findings validate this approach to improving measure accuracy while maintaining measure certification. Conclusion Organizations that report care quality should be aware of how identified issues affect quality measure selection and calculation. Quality measure authors should consider increasing real-world validation and the consistency of measure logic in respect to issues identified in this research. |
format | Online Article Text |
id | pubmed-5999523 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Schattauer GmbH |
record_format | MEDLINE/PubMed |
spelling | pubmed-59995232019-04-01 Using Clinical Data Standards to Measure Quality: A New Approach D'Amore, John D. Li, Chun McCrary, Laura Niloff, Jonathan M. Sittig, Dean F. McCoy, Allison B. Wright, Adam Appl Clin Inform Background Value-based payment for care requires the consistent, objective calculation of care quality. Previous initiatives to calculate ambulatory quality measures have relied on billing data or individual electronic health records (EHRs) to calculate and report performance. New methods for quality measure calculation promoted by federal regulations allow qualified clinical data registries to report quality outcomes based on data aggregated across facilities and EHRs using interoperability standards. Objective This research evaluates the use of clinical document interchange standards as the basis for quality measurement. Methods Using data on 1,100 patients from 11 ambulatory care facilities and 5 different EHRs, challenges to quality measurement are identified and addressed for 17 certified quality measures. Results Iterative solutions were identified for 14 measures that improved patient inclusion and measure calculation accuracy. Findings validate this approach to improving measure accuracy while maintaining measure certification. Conclusion Organizations that report care quality should be aware of how identified issues affect quality measure selection and calculation. Quality measure authors should consider increasing real-world validation and the consistency of measure logic in respect to issues identified in this research. Schattauer GmbH 2018-04 2018-06-13 /pmc/articles/PMC5999523/ /pubmed/29898468 http://dx.doi.org/10.1055/s-0038-1656548 Text en 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 | D'Amore, John D. Li, Chun McCrary, Laura Niloff, Jonathan M. Sittig, Dean F. McCoy, Allison B. Wright, Adam Using Clinical Data Standards to Measure Quality: A New Approach |
title | Using Clinical Data Standards to Measure Quality: A New Approach |
title_full | Using Clinical Data Standards to Measure Quality: A New Approach |
title_fullStr | Using Clinical Data Standards to Measure Quality: A New Approach |
title_full_unstemmed | Using Clinical Data Standards to Measure Quality: A New Approach |
title_short | Using Clinical Data Standards to Measure Quality: A New Approach |
title_sort | using clinical data standards to measure quality: a new approach |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5999523/ https://www.ncbi.nlm.nih.gov/pubmed/29898468 http://dx.doi.org/10.1055/s-0038-1656548 |
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