Literature DB >> 10121426

Description of a computerized adverse drug event monitor using a hospital information system.

D C Classen1, S L Pestotnik, R S Evans, J P Burke.   

Abstract

To improve the detection and characterization of adverse drug events (ADEs) in hospitalized patients, a computerized adverse drug event monitor was developed. Computer programs were written to allow for voluntary as well as automated detection of adverse drug events using the HELP hospital information system, a large integrated hospital database containing computerized patient medical records and a knowledge base allowing for automated medical decisions. Programs were created to allow simple computer entry of potential adverse drug events by physicians, pharmacists, and nurses. Automated detection of potential adverse drug events relied on signals such as sudden medication stop orders, "antidote" orders, and selected abnormal laboratory values. Each day a list of all potential adverse drug events from these sources was generated and a pharmacist reviewed the medical records and interviewed healthcare personnel associated with patients identified as having potential adverse drug events. This process allowed for characterization of the event, causality assessment, and follow-up of the resulting clinical course by the pharmacist. The permanent storage of these results in the computerized patient medical record permits their future retrieval to prevent adverse drug events during subsequent hospital care. The authors conclude that fully integrated hospital systems will permit the further development and evaluation of computer-assisted methods for the detection of adverse drug events in hospitalized patients.

Entities:  

Mesh:

Year:  1992        PMID: 10121426

Source DB:  PubMed          Journal:  Hosp Pharm        ISSN: 0018-5787


  25 in total

1.  Methodology and rationale for the measurement of harm with trigger tools.

Authors:  R K Resar; J D Rozich; D Classen
Journal:  Qual Saf Health Care       Date:  2003-12

2.  Using an anesthesia information management system to prove a deficit in voluntary reporting of adverse events in a quality assurance program.

Authors:  M Benson; A Junger; C Fuchs; L Quinzio; S Böttger; A Jost; D Uphus; G Hempelmann
Journal:  J Clin Monit Comput       Date:  2000       Impact factor: 2.502

3.  Improvement in the detection of adverse drug events by the use of electronic health and prescription records: an evaluation of two trigger tools.

Authors:  Ugochi Nwulu; Krishnarajah Nirantharakumar; Rachel Odesanya; Sarah E McDowell; Jamie J Coleman
Journal:  Eur J Clin Pharmacol       Date:  2012-06-17       Impact factor: 2.953

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.  Risk perception and reasons for noncompliance in pharmacovigilance: a qualitative study conducted in Canada.

Authors:  Vincent Nichols; Isabelle Thériault-Dubé; Julie Touzin; Jean-François Delisle; Denis Lebel; Jean-François Bussières; Benoît Bailey; Johanne Collin
Journal:  Drug Saf       Date:  2009       Impact factor: 5.606

6.  Identifying and quantifying medication errors: evaluation of rapidly discontinued medication orders submitted to a computerized physician order entry system.

Authors:  Ross Koppel; Charles E Leonard; A Russell Localio; Abigail Cohen; Ruthann Auten; Brian L Strom
Journal:  J Am Med Inform Assoc       Date:  2008-04-24       Impact factor: 4.497

7.  The impact of electronic medical records data sources on an adverse drug event quality measure.

Authors:  Michael G Kahn; Daksha Ranade
Journal:  J Am Med Inform Assoc       Date:  2010 Mar-Apr       Impact factor: 4.497

8.  "I meant that med for Baylee not Bailey!": a mixed method study to identify incidence and risk factors for CPOE patient misidentification.

Authors:  Hannah I Levin; James E Levin; Steven G Docimo
Journal:  AMIA Annu Symp Proc       Date:  2012-11-03

9.  E-pharmacovigilance: development and implementation of a computable knowledge base to identify adverse drug reactions.

Authors:  Antje Neubert; Harald Dormann; Hans-Ulrich Prokosch; Thomas Bürkle; Wolfgang Rascher; Reinhold Sojer; Kay Brune; Manfred Criegee-Rieck
Journal:  Br J Clin Pharmacol       Date:  2013-09       Impact factor: 4.335

10.  Comparing the effectiveness of computerized adverse drug event monitoring systems to enhance clinical decision support for hospitalized patients.

Authors:  G N Petratos; Y Kim; R S Evans; S D Williams; R M Gardner
Journal:  Appl Clin Inform       Date:  2010-09-01       Impact factor: 2.342

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.