Literature DB >> 17662100

Searching for a needle in a haystack: use of ICD-9-CM codes in drug-induced liver injury.

Kartik Jinjuvadia1, Wendy Kwan, Robert J Fontana.   

Abstract

OBJECTIVES: The aim of our study was to compare three search strategies using a computerized administrative database to identify cases of idiosyncratic drug-induced liver injury (DILI) due to amoxicillin/clavulanic acid, phenytoin, valproic acid, and isoniazid.
METHODS: In search 1, electronic medical records from patients seen between 1994 and 2004 with an ICD-9-CM code of acute liver injury were identified and cross-searched for the specific drug names in the dictation text. In search 2, all patients with an ICD-9-CM code of drug poisoning/overdose due to one of the four study drugs were identified. In search 3, patients with a poisoning code as well as an acute liver injury code were identified.
RESULTS: Review of the records from the 7,395 search 1 patients yielded 51 DILI cases (0.7%). In contrast, the 566 search 2 patients yielded only three DILI cases (0.5%). Finally, search 3 provided the greatest specificity but a low rate of detection with only two patients (3.9%) having DILI due to one of the four drugs.
CONCLUSION: Acute liver injury ICD-9-CM codes combined with a text search of the dictated medical record yielded the greatest number of DILI cases but was less specific than crossing acute liver injury and poisoning codes. Use of ICD-9-CM codes to identify rare adverse events like DILI remains problematic and highlights the need for prospective surveillance networks.

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Year:  2007        PMID: 17662100     DOI: 10.1111/j.1572-0241.2007.01456.x

Source DB:  PubMed          Journal:  Am J Gastroenterol        ISSN: 0002-9270            Impact factor:   10.864


  27 in total

1.  A Text Searching Tool to Identify Patients with Idiosyncratic Drug-Induced Liver Injury.

Authors:  Lauren Heidemann; James Law; Robert J Fontana
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4.  How well do various health outcome definitions identify appropriate cases in observational studies?

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Journal:  Drug Saf       Date:  2013-10       Impact factor: 5.606

5.  Measuring the Information Gain of Diagnosis vs. Diagnosis Category Coding.

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Journal:  AMIA Annu Symp Proc       Date:  2010-11-13

6.  Data from clinical notes: a perspective on the tension between structure and flexible documentation.

Authors:  S Trent Rosenbloom; Joshua C Denny; Hua Xu; Nancy Lorenzi; William W Stead; Kevin B Johnson
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7.  Validity of diagnostic codes to identify cases of severe acute liver injury in the US Food and Drug Administration's Mini-Sentinel Distributed Database.

Authors:  Vincent Lo Re; Kevin Haynes; David Goldberg; Kimberly A Forde; Dena M Carbonari; Kimberly B F Leidl; Sean Hennessy; K Rajender Reddy; Pamala A Pawloski; Gregory W Daniel; T Craig Cheetham; Aarthi Iyer; Kara O Coughlin; Sengwee Toh; Denise M Boudreau; Nandini Selvam; William O Cooper; Mano S Selvan; Jeffrey J VanWormer; Mark I Avigan; Monika Houstoun; Gwen L Zornberg; Judith A Racoosin; Azadeh Shoaibi
Journal:  Pharmacoepidemiol Drug Saf       Date:  2013-06-25       Impact factor: 2.890

Review 8.  Practical guidelines for diagnosis and early management of drug-induced liver injury.

Authors:  Kazuto Tajiri; Yukihiro Shimizu
Journal:  World J Gastroenterol       Date:  2008-11-28       Impact factor: 5.742

9.  Automated summaries of serious adverse events in the hepatitis C antiviral long-term treatment against cirrhosis trial.

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Journal:  Clin Trials       Date:  2009-11-04       Impact factor: 2.486

10.  Assessment of case definitions for identifying acute liver injury in large observational databases.

Authors:  Aaron J Katz; Patrick B Ryan; Judith A Racoosin; Paul E Stang
Journal:  Drug Saf       Date:  2013-08       Impact factor: 5.606

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