Evidence map›Paper›PMID 41371747›Full record

ArticleBMJ open2025

Study protocol for optimising antipsychotic prescribing among hospitalised patients in the acute care setting in Scotland: a national retrospective cohort study.

Cosmika Goswami, Tanja Mueller, Alexa Wall, Chris F Johnson, David Grosset, Marion Bennie, Amanj Kurdi

Abstract read
In one paragraph

Article in BMJ open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

7 authors.

Cosmika GoswamiStrathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, UK cosmika.goswami@strath.ac.uk.ORCID http://orcid.org/0000-0002-5289-5550
Tanja MuellerStrathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, UK.ORCID http://orcid.org/0000-0002-0418-4789
Alexa WallPharmacy Services, National Health Services Lothian, Edinburgh, UK.
Chris F JohnsonPharmacy Services, National Health Services Greater Glasgow & Clyde, Glasgow, UK.ORCID http://orcid.org/0000-0002-6006-6605
David GrossetPsychiatry, National Health Services Lothian, Edinburgh, UK.
Marion BennieStrathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, UK.ORCID http://orcid.org/0000-0002-4046-629X
Amanj KurdiStrathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, UK.ORCID http://orcid.org/0000-0001-5036-1988

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionPrescribing high-dose antipsychotics is typically reserved for individuals with treatment-resistant severe mental illnesses, such as schizophrenia, bipolar disorder and psychotic depression. It carries an increased risk of adverse drug effects, necessitating regular monitoring. Non-mental health specialist clinicians may not always be aware when the maximum recommended dose of antipsychotics is exceeded, leading to unintentional high-dose prescribing without recognising the need for additional monitoring or understanding the associated risks. Therefore, providing clinical decision support (CDS) tools to support clinicians and improve the appropriate prescribing of antipsychotics is important. The aim of this study is to understand current prescribing practices and assess the impact of high-dose antipsychotic prescribing on clinical outcomes among hospitalised patients. The findings from this study will shape a future project focused on developing an integrated computerised CDS tool. METHODS AND ANALYSIS: This retrospective cohort study will examine antipsychotic prescribing among hospitalised patients using Hospital Electronic Prescribing and Medicines Administration data in Scotland from 2019 to 2023, in linkage with hospital records, Scottish Morbidity Records and primary care prescribing (Prescribing Information System). Patients will be grouped into those prescribed high-dose (exposed), defined as exceeding the 100% maximum recommended British National Formulary dose and normal-dose (unexposed) antipsychotics, followed from their first ever antipsychotic prescription date (index date) until the end of the study, study outcomes or death, whichever happens first. We will quantify high-dose antipsychotic prescribing, profile patient characteristics and use machine learning techniques to assess associations of high-dose antipsychotic prescribing with clinical outcomes, including harms and benefits, but will not attempt to establish causality. ETHICS AND DISSEMINATION: The Health and Social Care Public Benefit and Privacy Policy Panel (HSC-PBPP) has granted ethical approval (ref. 2024-0239) following a Data Protection Impact Assessment, with data securely held and accessed in the National Safe Haven. The results will be published in international peer-reviewed journals and will be shared with clinicians.

Indexed as

Antipsychotic AgentsPractice Patterns, Physicians'Decision Support Systems, ClinicalHospitalizationHumansResearch DesignRetrospective StudiesScotlandAntipsychotic AgentsINTENSIVE & CRITICAL CAREMENTAL HEALTHPolypharmacy

Identifiers

PMID41371747
PMCPMC12699559

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Registered trials

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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.