Evidence map›Paper›PMID 21676939›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA

The influence of computerized decision support on prescribing during ward-rounds: are the decision-makers targeted?

Melissa T Baysari, Johanna I Westbrook, Katrina L Richardson, Richard O Day

Open access · greenAbstract read
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 3 pooled it
13.2field-weighted citation impact, top 1% of its field
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

30 citing papers in PubMed, 3 syntheses or guidelines pooled it, 70 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Trial
  5. Article
  6. Review
  7. Article
  8. Habit and Automaticity in Medical Alert Override: Cohort Study.Journal of medical Internet research · 2022
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  16. Evidence-based usability design principles for medication alerting systems.BMC medical informatics and decision making · 2018
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  17. Article
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  19. Alert override as a habitual behavior - a new perspective on a persistent problem.Journal of the American Medical Informatics Association : JAMIA · 2017
    Article
  20. Article
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 at 3 institutions in 1 country.

Melissa T BaysariAustralian Institute of Health Innovation, Faculty of Medicine, University of New South Wales, Sydney, Australia. m.baysari@unsw.edu.au
Johanna I Westbrook
Katrina L Richardson
Richard O Day
UNSW Sydney · AUAustralian Institute of Business · AUSt Vincent's Hospital Sydney · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo assess whether a low level of decision support within a hospital computerized provider order entry system has an observable influence on the medication ordering process on ward-rounds and to assess prescribers' views of the decision support features.

methods14 specialty teams (46 doctors) were shadowed by the investigator while on their ward-rounds and 16 prescribers from these teams were interviewed.

resultsSenior doctors were highly influential in prescribing decisions during ward-rounds but rarely used the computerized provider order entry system. Junior doctors entered the majority of medication orders into the system, nearly always ignored computerized alerts and never raised their occurrence with other doctors on ward-rounds. Interviews with doctors revealed that some decision support features were valued but most were not perceived to be useful. DISCUSSION AND

conclusionThe computerized alerts failed to target the doctors who were making the prescribing decisions on ward-rounds. Senior doctors were the decision makers, yet the junior doctors who used the system received the alerts. As a result, the alert information was generally ignored and not incorporated into the decision-making processes on ward-rounds. The greatest value of decision support in this setting may be in non-ward-round situations where senior doctors are less influential. Identifying how prescribing systems are used during different clinical activities can guide the design of decision support that effectively supports users in different situations. If confirmed, the findings reported here present a specific focus and user group for designers of medication decision support.

Indexed as

Attitude of Health PersonnelDrug Therapy, Computer-AssistedMedical Order Entry SystemsMedical Staff, HospitalDecision Support Systems, ClinicalHospitals, TeachingHumansInterviews as TopicMedication ErrorsNew South WalesReminder Systems

Identifiers

PMID21676939
PMCPMC3197993
OpenAlexW2100728000

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.