Evidence map›Paper›PMID 32229485›Full record

ArticleBMJ open quality2020

'Real time' monitoring of antipsychotic prescribing in patients with dementia: a study using the Clinical Record Interactive Search (CRIS) platform to enhance safer prescribing.

Craig Colling, Christoph Mueller, Gayan Perera, Nicola Funnell, Justin Sauer, Daniel Harwood, Robert Stewart, Delia Bishara

Open access · goldAbstract read
In one paragraph

Article in BMJ open quality, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.2field-weighted citation impact, top 48% 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

4 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
  3. Observational
  4. 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

8 authors at 2 institutions in 1 country.

Craig CollingBiomedical Research Centre (BRC), Institute of Psychiatry, Psychology and Neuroscience, London, UK.
Christoph MuellerBiomedical Research Centre (BRC), Institute of Psychiatry, Psychology and Neuroscience, London, UK.
Gayan PereraBiomedical Research Centre (BRC), Institute of Psychiatry, Psychology and Neuroscience, London, UK.
Nicola FunnellMental Health of Older Adults and Dementia Clinical Academic Group (SLaM), South London and Maudsley NHS Foundation Trust, London, UK.
Justin SauerBiomedical Research Centre (BRC), Institute of Psychiatry, Psychology and Neuroscience, London, UK.
Daniel HarwoodMental Health of Older Adults and Dementia Clinical Academic Group (SLaM), South London and Maudsley NHS Foundation Trust, London, UK.
Robert StewartBiomedical Research Centre (BRC), Institute of Psychiatry, Psychology and Neuroscience, London, UK.
Delia BisharaBiomedical Research Centre (BRC), Institute of Psychiatry, Psychology and Neuroscience, London, UK delia.bishara@slam.nhs.uk.ORCID 0000-0002-6254-2054
South London and Maudsley NHS Foundation Trust · GBNIHR Imperial Biomedical Research Centre · GB

Funding

Medical Research Council MC_PC_17214Medical Research Council MR/T045302/1
6 · The paper itself

Abstract

backgroundThe use of antipsychotic drugs in dementia has been reported to be associated with increased risk of cerebrovascular events and mortality. There is an international drive to reduce the use of these agents in patients with dementia and to improve the safety of prescribing and monitoring in this area.

objectivesThe aim of this project was to use enhanced automated regular feedback of information from electronic health records to improve the quality of antipsychotic prescribing and monitoring in people with dementia.

methodsThe South London and Maudsley NHS Foundation Trust (SLaM) incorporated antipsychotic monitoring forms into its electronic health records. The SLaM Clinical Record Interactive Search (CRIS) platform provides researcher access to de-identified health records, and natural language processing is used in CRIS to derive structured data from unstructured free text, including recorded diagnoses and medication. Algorithms were thus developed to ascertain patients with dementia receiving antipsychotic treatment and to determine whether monitoring forms had been completed. We used two improvement plan-do-study-act cycles to improve the accuracy of the algorithm for automated evaluation and provided monthly feedback on team performance.

resultsA steady increase in antipsychotic monitoring form completion was observed across the study period. The percentage of our sample with a completed antipsychotic monitoring form more than doubled from October 2017 (22%) to January 2019 (58%).

conclusion'Real time' monitoring and regular feedback to teams offer a time-effective approach, complementary to standard audit methods, to enhance the safer prescribing of high risk drugs.

Indexed as

Antipsychotic AgentsDementiaElectronic Health RecordsHumansLondonMonitoring, PhysiologicState MedicineAntipsychotic Agentschecklistsclinical auditcontinuous quality improvementdementiaelectronic health records

Identifiers

PMID32229485
PMCPMC7170541
OpenAlexW3014009376

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.