Literature DB >> 6688154

The Seattle evaluation of computerized drug profiles: effects on prescribing practices and resource use.

T D Koepsell, A L Gurtel, P H Diehr, N R Temkin, K H Helfand, M A Gleser, R K Tompkins.   

Abstract

Since 1979, all outpatient pharmacy transactions at the US Public Health Service Hospital in Seattle have been captured in a computer system which generates a profile of each patient's active and previously used drugs. We conducted a controlled trial in which patients were allocated to profile or no-profile groups while the computer continued to collect data on everyone. In all, 41,572 clinic visits made by 6,186 patients were studied. The incidence of preventable drug-drug interactions and redundancies was very low and was unaffected by profiles. For unclear reasons, prescription of two interacting drugs on the same visit was significantly more common for patients with profiles. The duration of drug-drug interaction episodes was significantly shorter for profile group patients, perhaps due to earlier detection of the error on subsequent visits. Profiles had no effect on prescribing volume or coordination of drug refill and visit schedules, but profile group patients made about 5 per cent fewer clinic visits than those in the no-profile group. In this setting, it appears that the prescribing of interacting or redundant drugs is more often due to inadequate provider knowledge than to inaccessible patient-specific drug data. Prevention of such errors would thus require a more active educational or monitoring program.

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Year:  1983        PMID: 6688154      PMCID: PMC1651110          DOI: 10.2105/ajph.73.8.850

Source DB:  PubMed          Journal:  Am J Public Health        ISSN: 0090-0036            Impact factor:   9.308


  4 in total

1.  Examining physicians' drug order recording behavior.

Authors:  R E Johnson; D J Azevedo; W H Campbell; D B Christensen
Journal:  Med Care       Date:  1978-05       Impact factor: 2.983

2.  An analysis for transient states with application to tumor shrinkage.

Authors:  N R Temkin
Journal:  Biometrics       Date:  1978-12       Impact factor: 2.571

3.  Studying the impact of patient drug profiles in an HMO.

Authors:  R E Johnson; W H Campbell; D J Azevedo; D B Christensen
Journal:  Med Care       Date:  1976-10       Impact factor: 2.983

4.  The Seattle evaluation of computerized drug profiles: effect on provider activities.

Authors:  T D Koepsell; K H Helfand; P H Diehr; A L Gurtel; M A Gleser; R K Tompkins
Journal:  Med Care       Date:  1983-05       Impact factor: 2.983

  4 in total
  7 in total

1.  Changing doctor prescribing behaviour.

Authors:  P S Gill; M Mäkelä; K M Vermeulen; N Freemantle; G Ryan; C Bond; T Thorsen; F M Haaijer-Ruskamp
Journal:  Pharm World Sci       Date:  1999-08

Review 2.  Assessing medication appropriateness in the elderly: a review of available measures.

Authors:  P S Shelton; M A Fritsch; M A Scott
Journal:  Drugs Aging       Date:  2000-06       Impact factor: 3.923

Review 3.  Evidence on interventions to reduce medical errors: an overview and recommendations for future research.

Authors:  J P Ioannidis; J Lau
Journal:  J Gen Intern Med       Date:  2001-05       Impact factor: 5.128

4.  Impact of feedback and peer review on prescribing.

Authors:  F M Haaijer-Ruskamp; P Denig
Journal:  Occas Pap R Coll Gen Pract       Date:  1995-02

5.  A prescription for better prescribing.

Authors:  J K Aronson
Journal:  Br J Clin Pharmacol       Date:  2006-05       Impact factor: 4.335

Review 6.  Polypharmacy: the cure becomes the disease.

Authors:  C A Colley; L M Lucas
Journal:  J Gen Intern Med       Date:  1993-05       Impact factor: 5.128

7.  A prescription is not a simple matter anymore.

Authors:  A I Wertheimer
Journal:  Am J Public Health       Date:  1983-08       Impact factor: 9.308

  7 in total

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