Literature DB >> 9357622

Evaluating the potential effectiveness of using computerized information systems to prevent adverse drug events.

J G Anderson1, S J Jay, M Anderson, T J Hunt.   

Abstract

In this study a dynamic computer simulation model is used to estimate the effectiveness of various information systems applications designed to detect and prevent medication errors that result in adverse drug events (ADEs). The model simulates the four stages of the drug ordering and delivery system: prescribing, transcribing, dispensing and administering drugs. In this study we simulated interventions that have been demonstrated in prior studies to decrease error rates. The results demonstrated that a computerized information system that detected 26% of medication errors and prevented associated ADEs could save 1,226 days of excess hospitalization and $1.4 million in hospital costs annually. Those results suggest that such systems are potentially a cost-effective means of preventing ADEs in hospitals. The results demonstrated the importance of viewing adverse drug events from a systems perspective. Prevention efforts that focus on a single stage of the process had limited impact on the overall error rate. This study suggests that system-wide changes to the drug-ordering and delivery system are required to significantly reduce adverse drug events in a hospital setting.

Mesh:

Year:  1997        PMID: 9357622      PMCID: PMC2233438     

Source DB:  PubMed          Journal:  Proc AMIA Annu Fall Symp        ISSN: 1091-8280


  13 in total

1.  The nature of adverse events in hospitalized patients. Results of the Harvard Medical Practice Study II.

Authors:  L L Leape; T A Brennan; N Laird; A G Lawthers; A R Localio; B A Barnes; L Hebert; J P Newhouse; P C Weiler; H Hiatt
Journal:  N Engl J Med       Date:  1991-02-07       Impact factor: 91.245

2.  Error in medicine.

Authors:  L L Leape
Journal:  JAMA       Date:  1994-12-21       Impact factor: 56.272

3.  Incidence of adverse drug events and potential adverse drug events. Implications for prevention. ADE Prevention Study Group.

Authors:  D W Bates; D J Cullen; N Laird; L A Petersen; S D Small; D Servi; G Laffel; B J Sweitzer; B F Shea; R Hallisey
Journal:  JAMA       Date:  1995-07-05       Impact factor: 56.272

4.  An interdisciplinary method of classifying and monitoring medication errors.

Authors:  R P Betz; H B Levy
Journal:  Am J Hosp Pharm       Date:  1985-08

5.  Adverse drug events in hospitalized patients. Excess length of stay, extra costs, and attributable mortality.

Authors:  D C Classen; S L Pestotnik; R S Evans; J F Lloyd; J P Burke
Journal:  JAMA       Date:  1997 Jan 22-29       Impact factor: 56.272

6.  The costs of adverse drug events in hospitalized patients. Adverse Drug Events Prevention Study Group.

Authors:  D W Bates; N Spell; D J Cullen; E Burdick; N Laird; L A Petersen; S D Small; B J Sweitzer; L L Leape
Journal:  JAMA       Date:  1997 Jan 22-29       Impact factor: 56.272

7.  Physician reporting compared with medical-record review to identify adverse medical events.

Authors:  A C O'Neil; L A Petersen; E F Cook; D W Bates; T H Lee; T A Brennan
Journal:  Ann Intern Med       Date:  1993-09-01       Impact factor: 25.391

8.  Potential identifiability and preventability of adverse events using information systems.

Authors:  D W Bates; A C O'Neil; D Boyle; J Teich; G M Chertow; A L Komaroff; T A Brennan
Journal:  J Am Med Inform Assoc       Date:  1994 Sep-Oct       Impact factor: 4.497

9.  Computerized surveillance of adverse drug events in hospital patients.

Authors:  D C Classen; S L Pestotnik; R S Evans; J P Burke
Journal:  JAMA       Date:  1991-11-27       Impact factor: 56.272

10.  Systems analysis of adverse drug events. ADE Prevention Study Group.

Authors:  L L Leape; D W Bates; D J Cullen; J Cooper; H J Demonaco; T Gallivan; R Hallisey; J Ives; N Laird; G Laffel
Journal:  JAMA       Date:  1995-07-05       Impact factor: 56.272

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  10 in total

1.  Cost-benefit analysis of the detection of prescribing errors by hospital pharmacy staff.

Authors:  Patrica M L A van den Bemt; Maarten J Postma; Eric N van Roon; Man-Chie C Chow; Roel Fijn; Jacobus R B J Brouwers
Journal:  Drug Saf       Date:  2002       Impact factor: 5.606

2.  Developing a taxonomy for research in adverse drug events: potholes and signposts.

Authors:  J R Nebeker; J F Hurdle; J Hoffman; B Roth; C R Weir; M H Samore
Journal:  Proc AMIA Symp       Date:  2001

3.  A conceptual framework for evaluating outpatient electronic prescribing systems based on their functional capabilities.

Authors:  Douglas S Bell; Shan Cretin; Richard S Marken; Adam B Landman
Journal:  J Am Med Inform Assoc       Date:  2003-10-05       Impact factor: 4.497

4.  Retrospective analysis of the frequency and recognition of adverse drug reactions by means of automatically recorded laboratory signals.

Authors:  I Tegeder; M Levy; U Muth-Selbach; R Oelkers; F Neumann; H Dormann; T Azaz-Livshits; M Criegee-Rieck; H T Schneider; E Hahn; K Brune; G Geisslinger
Journal:  Br J Clin Pharmacol       Date:  1999-05       Impact factor: 4.335

Review 5.  Drug-related problems in hospitalised patients.

Authors:  P M van den Bemt; T C Egberts; L T de Jong-van den Berg; J R Brouwers
Journal:  Drug Saf       Date:  2000-04       Impact factor: 5.606

6.  Incidence and costs of adverse drug reactions during hospitalisation: computerised monitoring versus stimulated spontaneous reporting.

Authors:  H Dormann; U Muth-Selbach; S Krebs; M Criegee-Rieck; I Tegeder; H T Schneider; E G Hahn; M Levy; K Brune; G Geisslinger
Journal:  Drug Saf       Date:  2000-02       Impact factor: 5.606

7.  The effects of an Electronic Medical Record on patient care: clinician attitudes in a large HMO.

Authors:  P D Marshall; H L Chin
Journal:  Proc AMIA Symp       Date:  1998

Review 8.  Prevalence, incidence and nature of prescribing errors in hospital inpatients: a systematic review.

Authors:  Penny J Lewis; Tim Dornan; David Taylor; Mary P Tully; Val Wass; Darren M Ashcroft
Journal:  Drug Saf       Date:  2009       Impact factor: 5.606

9.  Description and pilot evaluation of the Metabolic Irregularities Narrowing down Device software: a case analysis of physician programming.

Authors:  Markos G Kashiouris; Miloš Miljković; Vitaly Herasevich; Andrew D Goldberg; Charles Albrecht
Journal:  J Community Hosp Intern Med Perspect       Date:  2015-02-03

Review 10.  Electronic prescription system requirements: a scoping review.

Authors:  Marjan Vejdani; Mehdi Varmaghani; Marziyhe Meraji; Jamshid Jamali; Elaheh Hooshmand; Ali Vafaee-Najar
Journal:  BMC Med Inform Decis Mak       Date:  2022-09-03       Impact factor: 3.298

  10 in total

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