Literature DB >> 20962129

Drug safety surveillance using de-identified EMR and claims data: issues and challenges.

Prakash M Nadkarni1.   

Abstract

The author discusses the challenges of pharmacovigilance using electronic medical record and claims data. Use of ICD-9 encoded data has low sensitivity for detection of adverse drug events (ADEs), because it requires that an ADE escalate to major-complaint level before it can be identified, and because clinical symptomatology is relatively under-represented in ICD-9. A more appropriate vocabulary for ADE identification, SNOMED CT, awaits wider deployment. The narrative-text record of progress notes can potentially be used for more sensitive ADE detection. More effective surveillance will require the ability to grade ADEs by severity. Finally, access to online drug information that includes both a reliable hierarchy of drug families as well as structured information on existing ADEs can improve the focus and predictive ability of surveillance efforts.

Mesh:

Year:  2010        PMID: 20962129      PMCID: PMC3000764          DOI: 10.1136/jamia.2010.008607

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


  15 in total

1.  Using SNOMED CT in combination with MedDRA for reporting signal detection and adverse drug reactions reporting.

Authors:  Olivier Bodenreider
Journal:  AMIA Annu Symp Proc       Date:  2009-11-14

2.  Appraisal of the MedDRA conceptual structure for describing and grouping adverse drug reactions.

Authors:  Cédric Bousquet; Georges Lagier; Agnès Lillo-Le Louët; Christine Le Beller; Alain Venot; Marie-Christine Jaulent
Journal:  Drug Saf       Date:  2005       Impact factor: 5.606

3.  Active computerized pharmacovigilance using natural language processing, statistics, and electronic health records: a feasibility study.

Authors:  Xiaoyan Wang; George Hripcsak; Marianthi Markatou; Carol Friedman
Journal:  J Am Med Inform Assoc       Date:  2009-03-04       Impact factor: 4.497

4.  Heterogeneous but "standard" coding systems for adverse events: Issues in achieving interoperability between apples and oranges.

Authors:  Rachel L Richesson; Kin Wah Fung; Jeffrey P Krischer
Journal:  Contemp Clin Trials       Date:  2008-03-05       Impact factor: 2.226

5.  The MedDRA paradox.

Authors:  Gary H Merrill
Journal:  AMIA Annu Symp Proc       Date:  2008-11-06

6.  Just-in-time coding of the problem list in a clinical environment.

Authors:  J J Warren; J Collins; C Sorrentino; J R Campbell
Journal:  Proc AMIA Symp       Date:  1998

Review 7.  Desiderata for controlled medical vocabularies in the twenty-first century.

Authors:  J J Cimino
Journal:  Methods Inf Med       Date:  1998-11       Impact factor: 2.176

8.  The content coverage of clinical classifications. For The Computer-Based Patient Record Institute's Work Group on Codes & Structures.

Authors:  C G Chute; S P Cohn; K E Campbell; D E Oliver; J R Campbell
Journal:  J Am Med Inform Assoc       Date:  1996 May-Jun       Impact factor: 4.497

9.  The Unified Medical Language System.

Authors:  D A Lindberg; B L Humphreys; A T McCray
Journal:  Methods Inf Med       Date:  1993-08       Impact factor: 2.176

10.  Standardizing assessment and reporting of adverse effects in rheumatology clinical trials II: the Rheumatology Common Toxicity Criteria v.2.0.

Authors:  Thasia Woodworth; Daniel E Furst; Rieke Alten; Clifton O Bingham; Clifton Bingham; David Yocum; Victor Sloan; Wayne Tsuji; Randall Stevens; James Fries; James Witter; Kent Johnson; Marissa Lassere; Peter Brooks
Journal:  J Rheumatol       Date:  2007-06       Impact factor: 4.666

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  22 in total

1.  Cross-terminology mapping challenges: a demonstration using medication terminological systems.

Authors:  Himali Saitwal; David Qing; Stephen Jones; Elmer V Bernstam; Christopher G Chute; Todd R Johnson
Journal:  J Biomed Inform       Date:  2012-06-28       Impact factor: 6.317

2.  Text mining for adverse drug events: the promise, challenges, and state of the art.

Authors:  Rave Harpaz; Alison Callahan; Suzanne Tamang; Yen Low; David Odgers; Sam Finlayson; Kenneth Jung; Paea LePendu; Nigam H Shah
Journal:  Drug Saf       Date:  2014-10       Impact factor: 5.606

3.  A study of deep learning approaches for medication and adverse drug event extraction from clinical text.

Authors:  Qiang Wei; Zongcheng Ji; Zhiheng Li; Jingcheng Du; Jingqi Wang; Jun Xu; Yang Xiang; Firat Tiryaki; Stephen Wu; Yaoyun Zhang; Cui Tao; Hua Xu
Journal:  J Am Med Inform Assoc       Date:  2020-01-01       Impact factor: 4.497

4.  Comparative assessment of manual chart review and ICD claims data in evaluating immunotherapy-related adverse events.

Authors:  Andrew Nashed; Shijun Zhang; Chien-Wei Chiang; M Zitu; Gregory A Otterson; Carolyn J Presley; Kari Kendra; Sandip H Patel; Andrew Johns; Mingjia Li; Madison Grogan; Gabrielle Lopez; Dwight H Owen; Lang Li
Journal:  Cancer Immunol Immunother       Date:  2021-02-24       Impact factor: 6.968

Review 5.  Natural Language Processing for EHR-Based Pharmacovigilance: A Structured Review.

Authors:  Yuan Luo; William K Thompson; Timothy M Herr; Zexian Zeng; Mark A Berendsen; Siddhartha R Jonnalagadda; Matthew B Carson; Justin Starren
Journal:  Drug Saf       Date:  2017-11       Impact factor: 5.606

6.  Computational Drug Repositioning Using Continuous Self-Controlled Case Series.

Authors:  Zhaobin Kuang; James Thomson; Michael Caldwell; Peggy Peissig; Ron Stewart; David Page
Journal:  KDD       Date:  2016-08

7.  Development of an algorithm to link electronic health record prescriptions with pharmacy dispense claims.

Authors:  Megan Hoopes; Heather Angier; Lewis A Raynor; Andrew Suchocki; John Muench; Miguel Marino; Pedro Rivera; Nathalie Huguet
Journal:  J Am Med Inform Assoc       Date:  2018-10-01       Impact factor: 4.497

Review 8.  Translational bioinformatics embraces big data.

Authors:  N H Shah
Journal:  Yearb Med Inform       Date:  2012

9.  A Machine-Learning-Based Drug Repurposing Approach Using Baseline Regularization.

Authors:  Zhaobin Kuang; Yujia Bao; James Thomson; Michael Caldwell; Peggy Peissig; Ron Stewart; Rebecca Willett; David Page
Journal:  Methods Mol Biol       Date:  2019

10.  Pharmacovigilance using clinical notes.

Authors:  P LePendu; S V Iyer; A Bauer-Mehren; R Harpaz; J M Mortensen; T Podchiyska; T A Ferris; N H Shah
Journal:  Clin Pharmacol Ther       Date:  2013-03-04       Impact factor: 6.875

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