Literature DB >> 11248601

A computerized method for identifying incidents associated with adverse drug events in outpatients.

B Honigman1, P Light, R M Pulling, D W Bates.   

Abstract

INTRODUCTION: In inpatients, computer monitors have been used to improve the detection of adverse drug events (ADEs). However, similar programs have not been available in outpatients.
OBJECTIVE: To describe an approach for detecting incidents suggesting that an ADE may have occurred in outpatients by adapting methods from inpatient computer monitoring and developing terminology searches of electronic medical records.
METHODS: One year of information from the outpatient electronic medical record (EMR) at one hospital and its clinics was reviewed. Altogether, 23064 patients and 88514 visits were identified. Patient demographics, medical problem lists, ICD-9 claims, patient allergies, medication history and all clinic visit notes were extracted and merged. We then searched for incidents suggesting that an ADE might be present using four methods: ICD-9 claims, new allergies, computer rules linking laboratory data to known medication exposures, and a medical terminology lexicon (M2D2). In this report, we describe how these search methods were developed to allow for ADE identification.
CONCLUSION: The ability to carry out such quality-related work is an example of the benefits of the outpatient EMR that may not be apparent to those institutions considering adopting it.

Entities:  

Mesh:

Year:  2001        PMID: 11248601     DOI: 10.1016/s1386-5056(00)00131-3

Source DB:  PubMed          Journal:  Int J Med Inform        ISSN: 1386-5056            Impact factor:   4.046


  16 in total

1.  Automated evaluation of electronic discharge notes to assess quality of care for cardiovascular diseases using Medical Language Extraction and Encoding System (MedLEE).

Authors:  Jung-Hsien Chiang; Jou-Wei Lin; Chen-Wei Yang
Journal:  J Am Med Inform Assoc       Date:  2010 May-Jun       Impact factor: 4.497

2.  David Westfall Bates, MD: a conversation with the editor on improving patient safety, quality of care, and outcomes by using information technology. Interview by William Clifford Roberts.

Authors:  David Westfall Bates
Journal:  Proc (Bayl Univ Med Cent)       Date:  2005-04

3.  Using computerized data to identify adverse drug events in outpatients.

Authors:  B Honigman; J Lee; J Rothschild; P Light; R M Pulling; T Yu; D W Bates
Journal:  J Am Med Inform Assoc       Date:  2001 May-Jun       Impact factor: 4.497

Review 4.  A systematic review of the performance characteristics of clinical event monitor signals used to detect adverse drug events in the hospital setting.

Authors:  Steven M Handler; Richard L Altman; Subashan Perera; Joseph T Hanlon; Stephanie A Studenski; James E Bost; Melissa I Saul; Douglas B Fridsma
Journal:  J Am Med Inform Assoc       Date:  2007-04-25       Impact factor: 4.497

5.  Evidence-based staffing: potential roles for informatics.

Authors:  Sookyung Hyun; Suzanne Bakken; Kathy Douglas; Patricia W Stone
Journal:  Nurs Econ       Date:  2008 May-Jun       Impact factor: 1.085

6.  Computerized surveillance for adverse drug events in a pediatric hospital.

Authors:  Peter M Kilbridge; Laura A Noirot; Richard M Reichley; Kathleen M Berchelmann; Cortney Schneider; Kevin M Heard; Miranda Nelson; Thomas C Bailey
Journal:  J Am Med Inform Assoc       Date:  2009-06-30       Impact factor: 4.497

Review 7.  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

Review 8.  Improving patient safety through the systematic evaluation of patient outcomes.

Authors:  Alan J Forster; Geoff Dervin; Claude Martin; Steven Papp
Journal:  Can J Surg       Date:  2012-12       Impact factor: 2.089

9.  Strategies for detecting adverse drug events among older persons in the ambulatory setting.

Authors:  Terry S Field; Jerry H Gurwitz; Leslie R Harrold; Jeffrey M Rothschild; Kristin Debellis; Andrew C Seger; Leslie S Fish; Lawrence Garber; Michael Kelleher; David W Bates
Journal:  J Am Med Inform Assoc       Date:  2004-08-06       Impact factor: 4.497

10.  Exploring the ability of natural language processing to extract data from nursing narratives.

Authors:  Sookyung Hyun; Stephen B Johnson; Suzanne Bakken
Journal:  Comput Inform Nurs       Date:  2009 Jul-Aug       Impact factor: 1.985

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