Literature DB >> 21926280

How good are the data? Feasible approach to validation of metrics of quality derived from an outpatient electronic health record.

Andrea L Benin1, Ada Fenick, Jeph Herrin, Grace Vitkauskas, John Chen, Cynthia Brandt.   

Abstract

Although electronic health records (EHRs) promise to be efficient resources for measuring metrics of quality, they are not designed for such population-based analyses. Thus, extracting meaningful clinical data from them is not straightforward. To avoid poorly executed measurements, standardized methods to measure and to validate metrics of quality are needed. This study provides and evaluates a use case for a generally applicable approach to validating quality metrics measured electronically from EHR-based data. The authors iteratively refined and validated 4 outpatient quality metrics and classified errors in measurement. Multiple iterations of validation and measurement resulted in high levels of sensitivity and agreement versus the "gold standard" of manual review. In contrast, substantial differences remained for measurement based on coded billing data. Measuring quality metrics using an EHR-based electronic process requires validation to ensure accuracy; approaches to validation such as those described in this study should be used by organizations measuring quality from EHR-based information.

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Year:  2011        PMID: 21926280     DOI: 10.1177/1062860611403136

Source DB:  PubMed          Journal:  Am J Med Qual        ISSN: 1062-8606            Impact factor:   1.852


  9 in total

1.  Effects of Common Data Errors in Electronic Health Records on Emergency Department Operational Performance Metrics: A Monte Carlo Simulation.

Authors:  Michael J Ward; Wesley H Self; Craig M Froehle
Journal:  Acad Emerg Med       Date:  2015-08-20       Impact factor: 3.451

Review 2.  Innovative uses of electronic health records and social media for public health surveillance.

Authors:  Emma M Eggleston; Elissa R Weitzman
Journal:  Curr Diab Rep       Date:  2014-03       Impact factor: 4.810

3.  Automating the Capture of Structured Pathology Data for Prostate Cancer Clinical Care and Research.

Authors:  Anobel Y Odisho; Mark Bridge; Mitchell Webb; Niloufar Ameli; Renu S Eapen; Frank Stauf; Janet E Cowan; Samuel L Washington; Annika Herlemann; Peter R Carroll; Matthew R Cooperberg
Journal:  JCO Clin Cancer Inform       Date:  2019-07

4.  Caveats for the use of operational electronic health record data in comparative effectiveness research.

Authors:  William R Hersh; Mark G Weiner; Peter J Embi; Judith R Logan; Philip R O Payne; Elmer V Bernstam; Harold P Lehmann; George Hripcsak; Timothy H Hartzog; James J Cimino; Joel H Saltz
Journal:  Med Care       Date:  2013-08       Impact factor: 2.983

5.  The Analytic Information Warehouse (AIW): a platform for analytics using electronic health record data.

Authors:  Andrew R Post; Tahsin Kurc; Sharath Cholleti; Jingjing Gao; Xia Lin; William Bornstein; Dedra Cantrell; David Levine; Sam Hohmann; Joel H Saltz
Journal:  J Biomed Inform       Date:  2013-02-09       Impact factor: 6.317

6.  Health information technology: use it well, or don't! Findings from the use of a decision support system for breast cancer management.

Authors:  Jacques Bouaud; Brigitte Blaszka-Jaulerry; Laurent Zelek; Jean-Philippe Spano; Jean-Pierre Lefranc; Isabelle Cojean-Zelek; Axel Durieux; Christophe Tournigand; Alexandra Rousseau; Brigitte Séroussi
Journal:  AMIA Annu Symp Proc       Date:  2014-11-14

7.  Accessing primary care Big Data: the development of a software algorithm to explore the rich content of consultation records.

Authors:  J MacRae; B Darlow; L McBain; O Jones; M Stubbe; N Turner; A Dowell
Journal:  BMJ Open       Date:  2015-08-21       Impact factor: 2.692

8.  PIE: A prior knowledge guided integrated likelihood estimation method for bias reduction in association studies using electronic health records data.

Authors:  Jing Huang; Rui Duan; Rebecca A Hubbard; Yonghui Wu; Jason H Moore; Hua Xu; Yong Chen
Journal:  J Am Med Inform Assoc       Date:  2018-03-01       Impact factor: 4.497

9.  Private Hospital Workflow Optimization via Secure k-Means Clustering.

Authors:  Gabriele Spini; Maran van Heesch; Thijs Veugen; Supriyo Chatterjea
Journal:  J Med Syst       Date:  2019-11-29       Impact factor: 4.460

  9 in total

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