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Implementing a digital clinical decision support tool for side effects of antipsychotics: a focus group study
  1. Catherine Henshall1,
  2. Andrea Cipriani2,
  3. David Ruvolo3,
  4. Orla Macdonald4,
  5. Leona Wolters5,
  6. Ivan Koychev5
  1. 1 Faculty of Health and Life Sciences, Oxford Brookes University, Oxford, UK
  2. 2 Department of Psychiatry, University of Oxford, Oxford, UK
  3. 3 Research Reporting, Analysis, Data and Systems Research Portfolio, University of Sydney, Sydney, New South Wales, Australia
  4. 4 Pharmacy, Oxford Health NHS Foundation Trust, Oxford, UK
  5. 5 Psychiatry, University of Oxford, Oxford, UK
  1. Correspondence to Dr Catherine Henshall, Faculty of Health and Life Sciences, Oxford Brookes University, Oxford OX3 0BP, UK; chenshall{at}


Background In medicine, algorithms can inform treatment decisions by combining the most up-to-date evidence about side effect profiles of medications, which are comparable in efficacy. Their use provides opportunities for improved shared clinician–patient decision-making when initiating therapy. We designed a decision support tool (DST) that incorporated the latest evidence regarding antipsychotic side effects. The tool allowed patients to select one side effect commonly associated with antipsychotics that they wished to avoid; the tool then provided a list of suggested medications and ones to avoid.

Objective To explore qualitatively the acceptability and usefulness of the DST from the perspectives of patients and psychiatrists.

Methods This qualitative study took place at a mental health and community hospital in Oxford, UK, in 2018. Four patients/carers and four psychiatrists were recruited to two focus groups to explore their perceptions of the tool. Data were thematically analysed.

Findings Findings demonstrated a high degree of acceptability and potential usability of the DST for patients and psychiatrists. The main themes to emerge relating to the DST were ‘prescribing preferences and practices’, ‘consideration and awareness of side effects’, ‘app content, layout and accessibility’, ‘influence on clinical practice’ and ‘role in decision-making’.

Conclusions A proof-of-concept clinical study will incorporate the recommendations produced from the findings into the tool’s design.

Clinical implications Digital DSTs provide opportunities for the most up-to-date information on medication side effects to be used as the basis for shared clinician–patient decision-making. This tool has the potential to improve adherence to psychiatric medication, with benefits to clinical outcomes and healthcare resourcing.

  • adult psychiatry

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  • Contributors CH prepared the first draft of the manuscript and collated authors’ input. IK and DR designed and implemented the ICE application with substantial input from AC. CH, LW and IK designed and conducted the focus groups and CH undertook the data analysis. All authors provided substantial contributions on the data interpretation and revising it critically for important intellectual content. All authors have given final approval of the version to be published and have provided agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

  • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

  • Competing interests None declared.

  • Ethics approval Ethical approvals were not required for this study as it was deemed to be a Quality Improvement project by the participating NHS Trust.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data sharing statement Data are available on reasonable request from the corresponding author (CH) ( and is comprised of deidentified focus group data from participants.

  • Patient consent for publication Not required.