Evidence map›Paper›PMID 30181862›Full record

ReviewTherapeutic advances in drug safety2018

Using EMR-enabled computerized decision support systems to reduce prescribing of potentially inappropriate medications: a narrative review.

Ian A Scott, Peter I Pillans, Michael Barras, Christopher Morris

Abstract readReview
In one paragraph

Review in Therapeutic advances in drug safety, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers.

0numbers the graph read from it
0cells of the map it votes in
50citing papers in PubMed
–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

50 citing papers in PubMed.

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  18. Digitalisation of the drug prescribing process in Swiss hospitals - results of a survey.European journal of hospital pharmacy : science and practice · 2023
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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.

Ian A ScottDepartment of Internal Medicine and Clinical Epidemiology, Princess Alexandra Hospital, 199 Ipswich Road, Brisbane, QLD 4102, Australia.ORCID https://orcid.org/0000-0002-7596-0837
Peter I PillansDepartment of Clinical Pharmacology, Princess Alexandra Hospital, Brisbane, Australia School of Clinical Medicine, University of Queensland, Brisbane, Australia.
Michael BarrasDepartment of Pharmacy, Princess Alexandra Hospital, Brisbane, Australia School of Pharmacy, University of Queensland, Brisbane, Australia.
Christopher MorrisDepartment of General Medicine, Redlands Hospital, Cleveland, Australia Queensland Digital Healthcare Improvement Network, Queensland Health Department, Brisbane, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Prescribing of potentially inappropriate medications (PIMs) that pose more risk than benefit in older patients is a common occurrence across all healthcare settings. Reducing such prescribing has been challenging despite multiple interventions, including educational campaigns, audits and feedback, geriatrician assessment and formulary restrictions. With the increasing uptake of electronic medical records (EMRs) across hospitals, clinics and residential aged care facilities (RACFs), integrated with computerized physician order entry (CPOE) and e-prescribing, opportunities exist for incorporating clinical decision support systems (CDSS) into EMR at the point of care. This narrative review assessed the process and outcomes of using EMR-enabled CDSS to reduce the prescribing of PIMs. We searched PubMed for relevant articles published up to January 2018 and focused on those that described EMR-enabled CDSS that assisted prescribers to make changes at the time of ordering PIMs in adults. Computerized systems offering only medication reconciliation, dose checks, monitoring for medication errors, or basic formulary information were not included. In addition to outcome measures of medication-related processes and adverse drug events, qualitative data relating to factors that influence effectiveness of EMR-enabled CDSS were also gathered from selected studies. We analysed 20 studies comprising 10 randomized trials and 10 observational studies performed in hospitals (

Indexed as

clinical decision support systemscomputerized physician orderdeprescribingelectronic medical recordpotentially inappropriate medications

Identifiers

PMID30181862
PMCPMC6116772

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.