Literature DB >> 22195188

Structured vs. unstructured: factors affecting adverse drug reaction documentation in an EMR repository.

Stephen Skentzos1, Maria Shubina, Jorge Plutzky, Alexander Turchin.   

Abstract

Adverse reactions to medications to which the patient was known to be intolerant are common. Electronic decision support can prevent them but only if history of adverse reactions to medications is recorded in structured format. We have conducted a retrospective study of 31,531 patients with adverse reactions to statins documented in the notes, as identified with natural language processing. The software identified statin adverse reactions with sensitivity of 86.5% and precision of 91.9%. Only 9020 of these patients had an adverse reaction to a statin recorded in structured format. In multivariable analysis the strongest predictor of structured documentation was utilization of EMR functionality that integrated the medication list with the structured medication adverse reaction repository (odds ratio 48.6, p < 0.0001). Integration of information flow between EMR modules can help improve documentation and potentially prevent adverse drug events.

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Year:  2011        PMID: 22195188      PMCID: PMC3243255     

Source DB:  PubMed          Journal:  AMIA Annu Symp Proc        ISSN: 1559-4076


  20 in total

Review 1.  Effects of computerized physician order entry and clinical decision support systems on medication safety: a systematic review.

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3.  The "meaningful use" regulation for electronic health records.

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Journal:  JAMA       Date:  1995-07-05       Impact factor: 56.272

6.  Adverse drug events in ambulatory care.

Authors:  Tejal K Gandhi; Saul N Weingart; Joshua Borus; Andrew C Seger; Josh Peterson; Elisabeth Burdick; Diane L Seger; Kirstin Shu; Frank Federico; Lucian L Leape; David W Bates
Journal:  N Engl J Med       Date:  2003-04-17       Impact factor: 91.245

7.  A computer-assisted management program for antibiotics and other antiinfective agents.

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9.  Effective drug-allergy checking: methodological and operational issues.

Authors:  Gilad J Kuperman; Tejal K Gandhi; David W Bates
Journal:  J Biomed Inform       Date:  2003 Feb-Apr       Impact factor: 6.317

10.  Simvastatin and side effects.

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  18 in total

1.  Extracting Healthcare Quality Information from Unstructured Data.

Authors:  Shervin Malmasi; Naoshi Hosomura; Lee-Shing Chang; C Justin Brown; Stephen Skentzos; Alexander Turchin
Journal:  AMIA Annu Symp Proc       Date:  2018-04-16

2.  Towards Drug Safety Surveillance and Pharmacovigilance: Current Progress in Detecting Medication and Adverse Drug Events from Electronic Health Records.

Authors:  Feifan Liu; Abhyuday Jagannatha; Hong Yu
Journal:  Drug Saf       Date:  2019-01       Impact factor: 5.606

3.  Agreement of Medicaid claims and electronic health records for assessing preventive care quality among adults.

Authors:  John Heintzman; Steffani R Bailey; Megan J Hoopes; Thuy Le; Rachel Gold; Jean P O'Malley; Stuart Cowburn; Miguel Marino; Alex Krist; Jennifer E DeVoe
Journal:  J Am Med Inform Assoc       Date:  2014-02-07       Impact factor: 4.497

4.  Effect of EHR user interface changes on internal prescription discrepancies.

Authors:  A Turchin; A Sawarkar; Y A Dementieva; E Breydo; H Ramelson
Journal:  Appl Clin Inform       Date:  2014-08-06       Impact factor: 2.342

5.  Discontinuation of statins in routine care settings: a cohort study.

Authors:  Huabing Zhang; Jorge Plutzky; Stephen Skentzos; Fritha Morrison; Perry Mar; Maria Shubina; Alexander Turchin
Journal:  Ann Intern Med       Date:  2013-04-02       Impact factor: 25.391

6.  Reasons for discontinuation of lipid-lowering medications in patients with chronic kidney disease.

Authors:  Fritha J R Morrison; Huabing Zhang; Stephen Skentzos; Maria Shubina; Rhonda Bentley-Lewis; Alexander Turchin
Journal:  Cardiorenal Med       Date:  2014-11-19       Impact factor: 2.041

Review 7.  Artificial Intelligence-Based Pharmacovigilance in the Setting of Limited Resources.

Authors:  Likeng Liang; Jifa Hu; Gang Sun; Na Hong; Ge Wu; Yuejun He; Yong Li; Tianyong Hao; Li Liu; Mengchun Gong
Journal:  Drug Saf       Date:  2022-05-17       Impact factor: 5.228

Review 8.  Natural language processing systems for capturing and standardizing unstructured clinical information: A systematic review.

Authors:  Kory Kreimeyer; Matthew Foster; Abhishek Pandey; Nina Arya; Gwendolyn Halford; Sandra F Jones; Richard Forshee; Mark Walderhaug; Taxiarchis Botsis
Journal:  J Biomed Inform       Date:  2017-07-17       Impact factor: 6.317

Review 9.  Overview of the First Natural Language Processing Challenge for Extracting Medication, Indication, and Adverse Drug Events from Electronic Health Record Notes (MADE 1.0).

Authors:  Abhyuday Jagannatha; Feifan Liu; Weisong Liu; Hong Yu
Journal:  Drug Saf       Date:  2019-01       Impact factor: 5.606

10.  An evaluation of a natural language processing tool for identifying and encoding allergy information in emergency department clinical notes.

Authors:  Foster R Goss; Joseph M Plasek; Jason J Lau; Diane L Seger; Frank Y Chang; Li Zhou
Journal:  AMIA Annu Symp Proc       Date:  2014-11-14
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