Literature DB >> 6702674

Miscoding of hospital discharges as acute myocardial infarction: implications for surveillance programs aimed at elucidating trends in coronary artery disease.

G T Kennedy, M P Stern, M H Crawford.   

Abstract

The current decline in coronary artery disease mortality (CAD) may be a result of a declining population risk or of a declining case-fatality rate. Information on incidence trends for myocardial infarction (MI) could be used to distinguish between these 2 possibilities. Hospital discharge codes for MI (ICDCM-410) could be used as a convenient proxy for incidence trends, provided that coding of hospital discharges is sufficiently accurate. To evaluate the accuracy of medical records coding of patients signed out with an acute MI code (ICDCM-410), we compared them to an independent cardiology surveillance study of all patients with acute MI admitted to a large county teaching hospital. Over a 12-month period, 110 patients were coded as ICDCM-410 by medical records, but only 67 of these were detected by cardiology surveillance. The charts of the 43 patients not detected by surveillance were reviewed. In none of the 43 was evidence of acute MI found. In 28 of the 43, the discharge summaries listed rule out MI or status post-MI readmitted for further diagnostic workup, but were miscoded as ICDCM-410. Twelve of the 43 patients had cardiac arrests but were coded as ICDCM-410, even though there was no evidence of MI. Therefore, erroneous coding of patients as acute MI (ICDCM-410) may conceal a true downward trend in the incidence of CAD.

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Year:  1984        PMID: 6702674     DOI: 10.1016/0002-9149(84)90625-8

Source DB:  PubMed          Journal:  Am J Cardiol        ISSN: 0002-9149            Impact factor:   2.778


  8 in total

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2.  The development of a disease classification system, based on the International Classification of Diseases, for use by neurologists.

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

Authors:  Paul C Tang; Mary Ralston; Michelle Fernandez Arrigotti; Lubna Qureshi; Justin Graham
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4.  Positive predictive value of the diagnosis of acute myocardial infarction in an administrative database.

Authors:  L A Petersen; S Wright; S L Normand; J Daley
Journal:  J Gen Intern Med       Date:  1999-09       Impact factor: 5.128

5.  Case definitions for acute myocardial infarction in administrative databases and their impact on in-hospital mortality rates.

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Journal:  Health Serv Res       Date:  2012-06-28       Impact factor: 3.402

6.  Validity of coronary heart diseases and heart failure based on hospital discharge and mortality data in the Netherlands using the cardiovascular registry Maastricht cohort study.

Authors:  Audrey H H Merry; Jolanda M A Boer; Leo J Schouten; Edith J M Feskens; W M Monique Verschuren; Anton P M Gorgels; Piet A van den Brandt
Journal:  Eur J Epidemiol       Date:  2009-04-01       Impact factor: 8.082

7.  Use of diagnostic likelihood ratio of outcome to evaluate misclassification bias in the planning of database studies.

Authors:  Yoichi Ii; Shintaro Hiro; Yoshiomi Nakazuru
Journal:  BMC Med Inform Decis Mak       Date:  2022-01-21       Impact factor: 2.796

8.  Validity of myocardial infarction diagnoses in administrative databases: a systematic review.

Authors:  Natalie McCormick; Diane Lacaille; Vidula Bhole; J Antonio Avina-Zubieta
Journal:  PLoS One       Date:  2014-03-28       Impact factor: 3.240

  8 in total

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