Implementing a digital clinical decision support tool for side effects of antipsychotics: a focus group study.

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.

Absence of practice effects in preclinical Alzheimer's disease.

OBJECTIVE: To describe how practice effects influence cognitive trajectories and determine if a reduction in practice effects is a potential marker of Stage-III preclinical Alzheimer's disease (AD). METHOD: Participants included 263 older adults who were cognitively normal at baseline (i.e., had a Clinical Dementia Rating [CDR] of 0; Morris, 1993) and returned for an average of 9.5 annual visits. Participants completed standard tests of episodic memory, visuospatial ability, semantic memory, and executive function. Progressors (n = 66) converted to CDR > 0 with a diagnosis of symptomatic AD after a minimum of 3 visits and stable participants (n = 197) never progressed to CDR > 0. Practice effects, defined as the slope of performance across Visits 1-3, were compared between groups and used within subjects to predict risk of conversion. Change-point models that accounted for retest were contrasted with linear models that ignored retest. RESULTS: The stable group showed practice effects on episodic-memory measures (ß = 0.14, SE = .02, p < .0001) but the progressor group did not (ß = 0.03, SE = .03, p = .343). Across all participants, practice effects on episodic-memory tests were associated with a decreased risk of progression to AD as indicated by the subdistribution hazards model (SHR; Fine & Gray, 1999); SHR = .110, 95% CI [.032, .384], p = .001). Finally, use of change-point models dramatically altered rate-of-change estimates compared with models that ignored practice. CONCLUSION: Our results indicate that preclinical AD is marked by a reduction in practice effects in episodic memory and that the magnitude of gain from retesting is inversely related to progression risk. Assessment of practice effects may be a face-valid indicator of Stage-III preclinical AD.