Literature DB >> 17068349

Comparison of methodologies for calculating quality measures based on administrative data versus clinical data from an electronic health record system: implications for performance measures.

Paul C Tang1, Mary Ralston, Michelle Fernandez Arrigotti, Lubna Qureshi, Justin Graham.   

Abstract

New reimbursement policies and pay-for-performance programs to reward providers for producing better outcomes are proliferating. Although electronic health record (EHR) systems could provide essential clinical data upon which to base quality measures, most metrics in use were derived from administrative claims data. We compared commonly used quality measures calculated from administrative data to those derived from clinical data in an EHR based on a random sample of 125 charts of Medicare patients with diabetes. Using standard definitions based on administrative data (which require two visits with an encounter diagnosis of diabetes during the measurement period), only 75% of diabetics determined by manually reviewing the EHR (the gold standard) were identified. In contrast, 97% of diabetics were identified using coded information in the EHR. The discrepancies in identified patients resulted in statistically significant differences in the quality measures for frequency of HbA1c testing, control of blood pressure, frequency of testing for urine protein, and frequency of eye exams for diabetic patients. New development of standardized quality measures should shift from claims-based measures to clinically based measures that can be derived from coded information in an EHR. Using data from EHRs will also leverage their clinical content without adding burden to the care process.

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Year:  2006        PMID: 17068349      PMCID: PMC2215069          DOI: 10.1197/jamia.M2198

Source DB:  PubMed          Journal:  J Am Med Inform Assoc        ISSN: 1067-5027            Impact factor:   4.497


  17 in total

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Journal:  Qual Manag Health Care       Date:  1994       Impact factor: 0.926

2.  Medical groups' adoption of electronic health records and information systems.

Authors:  David Gans; John Kralewski; Terry Hammons; Bryan Dowd
Journal:  Health Aff (Millwood)       Date:  2005 Sep-Oct       Impact factor: 6.301

3.  Use of computer-based records, completeness of documentation, and appropriateness of documented clinical decisions.

Authors:  P C Tang; M P LaRosa; S M Gorden
Journal:  J Am Med Inform Assoc       Date:  1999 May-Jun       Impact factor: 4.497

4.  Five years after To Err Is Human: what have we learned?

Authors:  Lucian L Leape; Donald M Berwick
Journal:  JAMA       Date:  2005-05-18       Impact factor: 56.272

5.  The missing link: bridging the patient-provider health information gap.

Authors:  Paul C Tang; David Lansky
Journal:  Health Aff (Millwood)       Date:  2005 Sep-Oct       Impact factor: 6.301

6.  Validity of using an electronic medical record for assessing quality of care in an outpatient setting.

Authors:  Andrea L Benin; Grace Vitkauskas; Elizabeth Thornquist; Eugene D Shapiro; John Concato; Mihaela Aslan; Harlan M Krumholz
Journal:  Med Care       Date:  2005-07       Impact factor: 2.983

7.  The long road to patient safety: a status report on patient safety systems.

Authors:  Daniel R Longo; John E Hewett; Bin Ge; Shari Schubert
Journal:  JAMA       Date:  2005-12-14       Impact factor: 56.272

8.  Assessing the accuracy of administrative data in health information systems.

Authors:  John W Peabody; Jeff Luck; Sharad Jain; Dan Bertenthal; Peter Glassman
Journal:  Med Care       Date:  2004-11       Impact factor: 2.983

9.  Use of computerized clinical support systems in medical settings: United States, 2001-03.

Authors:  Catharine W Burt; Esther Hing
Journal:  Adv Data       Date:  2005-03-02

10.  Discordance of databases designed for claims payment versus clinical information systems. Implications for outcomes research.

Authors:  J G Jollis; M Ancukiewicz; E R DeLong; D B Pryor; L H Muhlbaier; D B Mark
Journal:  Ann Intern Med       Date:  1993-10-15       Impact factor: 25.391

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  76 in total

1.  Developing a natural language processing application for measuring the quality of colonoscopy procedures.

Authors:  Henk Harkema; Wendy W Chapman; Melissa Saul; Evan S Dellon; Robert E Schoen; Ateev Mehrotra
Journal:  J Am Med Inform Assoc       Date:  2011-09-21       Impact factor: 4.497

2.  International classification of diseases, 10th edition, clinical modification and procedure coding system: descriptive overview of the next generation HIPAA code sets.

Authors:  Steven J Steindel
Journal:  J Am Med Inform Assoc       Date:  2010 May-Jun       Impact factor: 4.497

3.  The Clinical Outcomes Assessment Toolkit: a framework to support automated clinical records-based outcomes assessment and performance measurement research.

Authors:  Leonard W D'Avolio; Alex A T Bui
Journal:  J Am Med Inform Assoc       Date:  2008-02-28       Impact factor: 4.497

Review 4.  The importance of clinical pathways and protocols in pediatric nephrology.

Authors:  Cherry Mammen; Douglas G Matsell; Kevin V Lemley
Journal:  Pediatr Nephrol       Date:  2013-08-18       Impact factor: 3.714

5.  Mining Electronic Health Records to Extract Patient-Centered Outcomes Following Prostate Cancer Treatment.

Authors:  Tina Hernandez-Boussard; Panagiotis D Kourdis; Tina Seto; Michelle Ferrari; Douglas W Blayney; Daniel Rubin; James D Brooks
Journal:  AMIA Annu Symp Proc       Date:  2018-04-16

6.  The impact of electronic medical records data sources on an adverse drug event quality measure.

Authors:  Michael G Kahn; Daksha Ranade
Journal:  J Am Med Inform Assoc       Date:  2010 Mar-Apr       Impact factor: 4.497

7.  Tracking the delivery of prevention-oriented care among primary care providers who have adopted electronic health records.

Authors:  Samantha F De Leon; Sarah C Shih
Journal:  J Am Med Inform Assoc       Date:  2011-08-19       Impact factor: 4.497

8.  Data standards in diabetes patient registries.

Authors:  Rachel L Richesson
Journal:  J Diabetes Sci Technol       Date:  2011-05-01

9.  Measuring Preventive Care Delivery: Comparing Rates Across Three Data Sources.

Authors:  Steffani R Bailey; John D Heintzman; Miguel Marino; Megan J Hoopes; Brigit A Hatch; Rachel Gold; Stuart C Cowburn; Christine A Nelson; Heather E Angier; Jennifer E DeVoe
Journal:  Am J Prev Med       Date:  2016-08-10       Impact factor: 5.043

10.  Patient completion of laboratory tests to monitor medication therapy: a mixed-methods study.

Authors:  Shira H Fischer; Terry S Field; Shawn J Gagne; Kathleen M Mazor; Peggy Preusse; George Reed; Daniel Peterson; Jerry H Gurwitz; Jennifer Tjia
Journal:  J Gen Intern Med       Date:  2012-11-15       Impact factor: 5.128

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