Literature DB >> 31407587

Computerized Adjudication of Coronary Heart Disease Events Using the Electronic Medical Record in HIV Clinical Research: Possibilities and Challenges Ahead.

Michelle Floris-Moore1,2, Andrew Edmonds3, Sonia Napravnik1,2, Adaora A Adimora1,2,3.   

Abstract

This pilot study assessed feasibility of computer-assisted electronic medical record (EMR) abstraction to ascertain coronary heart disease (CHD) event hospitalizations. We included a sample of 87 hospitalization records from participants the University of North Carolina (UNC) site of the Women's Interagency HIV Study (WIHS) and UNC Center for AIDS Research (CFAR) HIV Clinical Cohort who were hospitalized within UNC Healthcare System from July 2004 to July 2015. We compared a computer algorithm utilizing diagnosis/procedure codes, medications, and cardiac enzyme levels to adjudicate CHD events [myocardial infarction (MI)/coronary revascularization] from the EMR to standardized manual chart adjudication. Of 87 hospitalizations, 42 were classified as definite, 25 probable, and 20 non-CHD events by manual chart adjudication. A computer algorithm requiring presence of ≥1 CHD-related International Classification of Diseases, 9th Revision (ICD-9)/Current Procedural Terminology (CPT) code correctly identified 24 of 42 definite (57%), 29 of 67 probable/definite CHD (43%), and 95% of non-CHD events; additionally requiring clinically defined cardiac enzyme levels or administration of MI-related medications correctly identified 55%, 42%, and 95% of such events, respectively. Requiring any one of the ICD-9/CPT or cardiac enzyme criteria correctly identified 98% of definite, 97% of probable/definite CHD, and 85% of non-CHD events. Challenges included difficulty matching hospitalization dates, incomplete diagnosis code data, and multiple field names/locations of laboratory/medication data. Computer algorithms comprising only ICD-9/CPT codes failed to identify a sizable proportion of CHD events. Using a less restrictive algorithm yielded fewer missed events but increased the false-positive rate. Despite potential benefits of EMR-based research, there remain several challenges to fully computerized adjudication of CHD events.

Entities:  

Keywords:  HIV; computer phenotype; computerized event adjudication; coronary heart disease; electronic medical record

Mesh:

Year:  2019        PMID: 31407587      PMCID: PMC7185364          DOI: 10.1089/AID.2019.0036

Source DB:  PubMed          Journal:  AIDS Res Hum Retroviruses        ISSN: 0889-2229            Impact factor:   2.205


  18 in total

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Journal:  J Am Med Inform Assoc       Date:  2012 Mar-Apr       Impact factor: 4.497

2.  Universal definition of myocardial infarction.

Authors:  Kristian Thygesen; Joseph S Alpert; Harvey D White; Allan S Jaffe; Fred S Apple; Marcello Galvani; Hugo A Katus; L Kristin Newby; Jan Ravkilde; Bernard Chaitman; Peter M Clemmensen; Mikael Dellborg; Hanoch Hod; Pekka Porela; Richard Underwood; Jeroen J Bax; George A Beller; Robert Bonow; Ernst E Van der Wall; Jean-Pierre Bassand; William Wijns; T Bruce Ferguson; Philippe G Steg; Barry F Uretsky; David O Williams; Paul W Armstrong; Elliott M Antman; Keith A Fox; Christian W Hamm; E Magnus Ohman; Maarten L Simoons; Philip A Poole-Wilson; Enrique P Gurfinkel; José-Luis Lopez-Sendon; Prem Pais; Shanti Mendis; Jun-Ren Zhu; Lars C Wallentin; Francisco Fernández-Avilés; Kim M Fox; Alexander N Parkhomenko; Silvia G Priori; Michal Tendera; Liisa-Maria Voipio-Pulkki; Alec Vahanian; A John Camm; Raffaele De Caterina; Veronica Dean; Kenneth Dickstein; Gerasimos Filippatos; Christian Funck-Brentano; Irene Hellemans; Steen Dalby Kristensen; Keith McGregor; Udo Sechtem; Sigmund Silber; Michal Tendera; Petr Widimsky; José Luis Zamorano; Joao Morais; Sorin Brener; Robert Harrington; David Morrow; Michael Lim; Marco A Martinez-Rios; Steve Steinhubl; Glen N Levine; W Brian Gibler; David Goff; Marco Tubaro; Darek Dudek; Nawwar Al-Attar
Journal:  Circulation       Date:  2007-10-19       Impact factor: 29.690

3.  Transition to the ICD-10 in the United States: An Emerging Data Chasm.

Authors:  Rohan Khera; Karen B Dorsey; Harlan M Krumholz
Journal:  JAMA       Date:  2018-07-10       Impact factor: 56.272

4.  Third universal definition of myocardial infarction.

Authors:  Kristian Thygesen; Joseph S Alpert; Allan S Jaffe; Maarten L Simoons; Bernard R Chaitman; Harvey D White; Hugo A Katus; Bertil Lindahl; David A Morrow; Peter M Clemmensen; Per Johanson; Hanoch Hod; Richard Underwood; Jeroen J Bax; Robert O Bonow; Fausto Pinto; Raymond J Gibbons; Keith A Fox; Dan Atar; L Kristin Newby; Marcello Galvani; Christian W Hamm; Barry F Uretsky; Ph Gabriel Steg; William Wijns; Jean-Pierre Bassand; Phillippe Menasché; Jan Ravkilde; E Magnus Ohman; Elliott M Antman; Lars C Wallentin; Paul W Armstrong; Maarten L Simoons; James L Januzzi; Markku S Nieminen; Mihai Gheorghiade; Gerasimos Filippatos; Russell V Luepker; Stephen P Fortmann; Wayne D Rosamond; Dan Levy; David Wood; Sidney C Smith; Dayi Hu; José-Luis Lopez-Sendon; Rose Marie Robertson; Douglas Weaver; Michal Tendera; Alfred A Bove; Alexander N Parkhomenko; Elena J Vasilieva; Shanti Mendis
Journal:  Circulation       Date:  2012-08-24       Impact factor: 29.690

5.  Validation of electronic medical record-based phenotyping algorithms: results and lessons learned from the eMERGE network.

Authors:  Katherine M Newton; Peggy L Peissig; Abel Ngo Kho; Suzette J Bielinski; Richard L Berg; Vidhu Choudhary; Melissa Basford; Christopher G Chute; Iftikhar J Kullo; Rongling Li; Jennifer A Pacheco; Luke V Rasmussen; Leslie Spangler; Joshua C Denny
Journal:  J Am Med Inform Assoc       Date:  2013-03-26       Impact factor: 4.497

6.  What's in a Name? The New ICD-10 (10th Revision of the International Statistical Classification of Diseases and Related Health Problems) Codes and Type 2 Myocardial Infarction.

Authors:  Abhinav Goyal; Tyler J Gluckman; James E Tcheng
Journal:  Circulation       Date:  2017-09-26       Impact factor: 29.690

7.  Naïve Electronic Health Record phenotype identification for Rheumatoid arthritis.

Authors:  Robert J Carroll; Anne E Eyler; Joshua C Denny
Journal:  AMIA Annu Symp Proc       Date:  2011-10-22

8.  Design patterns for the development of electronic health record-driven phenotype extraction algorithms.

Authors:  Luke V Rasmussen; Will K Thompson; Jennifer A Pacheco; Abel N Kho; David S Carrell; Jyotishman Pathak; Peggy L Peissig; Gerard Tromp; Joshua C Denny; Justin B Starren
Journal:  J Biomed Inform       Date:  2014-06-21       Impact factor: 6.317

9.  Development of diagnostic criteria for serious non-AIDS events in HIV clinical trials.

Authors:  Alan R Lifson; Waldo H Belloso; Richard T Davey; Daniel Duprez; Jose M Gatell; Jennifer F Hoy; Eric A Krum; Ray Nelson; Court Pedersen; George Perez; Richard W Price; Ronald J Prineas; Frank S Rhame; James H Sampson; John Worley
Journal:  HIV Clin Trials       Date:  2010 Jul-Aug

Review 10.  A review of approaches to identifying patient phenotype cohorts using electronic health records.

Authors:  Chaitanya Shivade; Preethi Raghavan; Eric Fosler-Lussier; Peter J Embi; Noemie Elhadad; Stephen B Johnson; Albert M Lai
Journal:  J Am Med Inform Assoc       Date:  2013-11-07       Impact factor: 4.497

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  2 in total

1.  Comparison of algorithms for identifying people with HIV from electronic medical records in a large, multi-site database.

Authors:  Jessica P Ridgway; Joseph A Mason; Eleanor E Friedman; Samantha Devlin; Junlan Zhou; David Meltzer; John Schneider
Journal:  JAMIA Open       Date:  2022-05-17

Review 2.  A Systematic Review Exploring the Effect of Human Immunodeficiency Virus on Cardiac Diseases.

Authors:  Mohammed J Alzubaidee; Raga Sruthi Dwarampudi; Sheena Mathew; Sumahitha Bichenapally; Vahe Khachatryan; Asmaa Muazzam; Chandani Hamal; Lakshmi Sai Deepak Reddy Velugoti; Godfrey Tabowei; Greeshma N Gaddipati; Maria Mukhtar; Safeera Khan
Journal:  Cureus       Date:  2022-09-08
  2 in total

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