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.
Henshall, CatherineCipriani, AndreaRuvolo, DavidMacDonald, OrlaWolters, LeonaKoychev, Ivan
Faculty of Health and Life Sciences\Department of Psychology, Health and Professional Development
Year of publication: 2019Date of RADAR deposit: 2019-06-12
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