Validity of electronic health record-derived quality measurement for performance monitoring

Amanda S. Parsons, Colleen McCullough, Jason Wang, Sarah Shih

Research output: Contribution to journalArticle

76 Citations (Scopus)

Abstract

Background Since 2007, New York City's primary care information project has assisted over 3000 providers to adopt and use a prevention-oriented electronic health record (EHR). Participating practices were taught to readjust their workflows to use the EHR built-in population health monitoring tools, including automated quality measures, patient registries and a clinical decision support system. Practices received a comprehensive suite of technical assistance, which included quality improvement, EHR customization and configuration, privacy and security training, and revenue cycle optimization. These services were aimed at helping providers understand how to use their EHR to track and improve the quality of care delivered to patients. Materials and Methods Retrospective electronic chart reviews of 4081 patient records across 57 practices were analyzed to determine the validity of EHR-derived quality measures and documented preventive services. Results Results from this study show that workflow and documentation habits have a profound impact on EHR-derived quality measures. Compared with the manual review of electronic charts, EHR-derived measures can undercount practice performance, with a disproportionately negative impact on the number of patients captured as receiving a clinical preventive service or meeting a recommended treatment goal. Conclusion This study provides a cautionary note in using EHR-derived measurement for public reporting of provider performance or use for payment.

Original languageEnglish (US)
Pages (from-to)604-609
Number of pages6
JournalJournal of the American Medical Informatics Association
Volume19
Issue number4
DOIs
StatePublished - Jul 2012
Externally publishedYes

Fingerprint

Electronic Health Records
Workflow
Clinical Decision Support Systems
Quality of Health Care
Privacy
Quality Improvement
Documentation
Habits
Registries
Primary Health Care
Health
Population

ASJC Scopus subject areas

  • Health Informatics

Cite this

Validity of electronic health record-derived quality measurement for performance monitoring. / Parsons, Amanda S.; McCullough, Colleen; Wang, Jason; Shih, Sarah.

In: Journal of the American Medical Informatics Association, Vol. 19, No. 4, 07.2012, p. 604-609.

Research output: Contribution to journalArticle

@article{d7bb6125988645f79ff35458fab8e9fd,
title = "Validity of electronic health record-derived quality measurement for performance monitoring",
abstract = "Background Since 2007, New York City's primary care information project has assisted over 3000 providers to adopt and use a prevention-oriented electronic health record (EHR). Participating practices were taught to readjust their workflows to use the EHR built-in population health monitoring tools, including automated quality measures, patient registries and a clinical decision support system. Practices received a comprehensive suite of technical assistance, which included quality improvement, EHR customization and configuration, privacy and security training, and revenue cycle optimization. These services were aimed at helping providers understand how to use their EHR to track and improve the quality of care delivered to patients. Materials and Methods Retrospective electronic chart reviews of 4081 patient records across 57 practices were analyzed to determine the validity of EHR-derived quality measures and documented preventive services. Results Results from this study show that workflow and documentation habits have a profound impact on EHR-derived quality measures. Compared with the manual review of electronic charts, EHR-derived measures can undercount practice performance, with a disproportionately negative impact on the number of patients captured as receiving a clinical preventive service or meeting a recommended treatment goal. Conclusion This study provides a cautionary note in using EHR-derived measurement for public reporting of provider performance or use for payment.",
author = "Parsons, {Amanda S.} and Colleen McCullough and Jason Wang and Sarah Shih",
year = "2012",
month = "7",
doi = "10.1136/amiajnl-2011-000557",
language = "English (US)",
volume = "19",
pages = "604--609",
journal = "Journal of the American Medical Informatics Association : JAMIA",
issn = "1067-5027",
publisher = "Oxford University Press",
number = "4",

}

TY - JOUR

T1 - Validity of electronic health record-derived quality measurement for performance monitoring

AU - Parsons, Amanda S.

AU - McCullough, Colleen

AU - Wang, Jason

AU - Shih, Sarah

PY - 2012/7

Y1 - 2012/7

N2 - Background Since 2007, New York City's primary care information project has assisted over 3000 providers to adopt and use a prevention-oriented electronic health record (EHR). Participating practices were taught to readjust their workflows to use the EHR built-in population health monitoring tools, including automated quality measures, patient registries and a clinical decision support system. Practices received a comprehensive suite of technical assistance, which included quality improvement, EHR customization and configuration, privacy and security training, and revenue cycle optimization. These services were aimed at helping providers understand how to use their EHR to track and improve the quality of care delivered to patients. Materials and Methods Retrospective electronic chart reviews of 4081 patient records across 57 practices were analyzed to determine the validity of EHR-derived quality measures and documented preventive services. Results Results from this study show that workflow and documentation habits have a profound impact on EHR-derived quality measures. Compared with the manual review of electronic charts, EHR-derived measures can undercount practice performance, with a disproportionately negative impact on the number of patients captured as receiving a clinical preventive service or meeting a recommended treatment goal. Conclusion This study provides a cautionary note in using EHR-derived measurement for public reporting of provider performance or use for payment.

AB - Background Since 2007, New York City's primary care information project has assisted over 3000 providers to adopt and use a prevention-oriented electronic health record (EHR). Participating practices were taught to readjust their workflows to use the EHR built-in population health monitoring tools, including automated quality measures, patient registries and a clinical decision support system. Practices received a comprehensive suite of technical assistance, which included quality improvement, EHR customization and configuration, privacy and security training, and revenue cycle optimization. These services were aimed at helping providers understand how to use their EHR to track and improve the quality of care delivered to patients. Materials and Methods Retrospective electronic chart reviews of 4081 patient records across 57 practices were analyzed to determine the validity of EHR-derived quality measures and documented preventive services. Results Results from this study show that workflow and documentation habits have a profound impact on EHR-derived quality measures. Compared with the manual review of electronic charts, EHR-derived measures can undercount practice performance, with a disproportionately negative impact on the number of patients captured as receiving a clinical preventive service or meeting a recommended treatment goal. Conclusion This study provides a cautionary note in using EHR-derived measurement for public reporting of provider performance or use for payment.

UR - http://www.scopus.com/inward/record.url?scp=84865174655&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84865174655&partnerID=8YFLogxK

U2 - 10.1136/amiajnl-2011-000557

DO - 10.1136/amiajnl-2011-000557

M3 - Article

C2 - 22249967

AN - SCOPUS:84865174655

VL - 19

SP - 604

EP - 609

JO - Journal of the American Medical Informatics Association : JAMIA

JF - Journal of the American Medical Informatics Association : JAMIA

SN - 1067-5027

IS - 4

ER -