Evidence map›Paper›PMID 21417501›Full record

ReviewDrug safety2011

The role of computerized decision support in reducing errors in selecting medicines for prescription: narrative review.

Melissa T Baysari, Johanna Westbrook, Jeffrey Braithwaite, Richard O Day

Abstract readReview
PubMed Publisher
In one paragraph

Review in Drug safety, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Melissa T BaysariAustralian Institute of Health Innovation, Faculty of Medicine, University of New South Wales, Sydney, NSW 2010, Australia. m.baysari@unsw.edu.au
Johanna Westbrook
Jeffrey Braithwaite
Richard O Day

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This narrative review includes a summary of research examining prescribing errors, prescription decision making and the role computerized decision support plays in this decision-making process. A reduction in medication prescribing errors, specifically a reduction in the selection of inappropriate medications, is expected to result from the implementation of an effective computerized decision support system. Previous research has investigated the impact of the implementation of electronic systems on medication errors more broadly. This review examines the specific characteristics of decision support systems that may contribute to fewer knowledge-based mistakes in prescribing, and critically appraises the large volume of information available on the decision-making process of selecting medicines for prescription. The results highlight a need for work investigating what decision strategies are used by doctors with different levels of expertise in the prescribing of medications. The nature of the relationship between decision support and decision performance is not well understood and future research is needed to determine the mechanisms by which computerized decision support influences medication selection.

Indexed as

AnimalsDecision Support Systems, ClinicalDrug PrescriptionsHealth Knowledge, Attitudes, PracticeHumansMedication Errors

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.