Publications by authors named "M H Barras"
Objective: To describe development and application of a checklist of criteria for selecting an automated machine learning (Auto ML) platform for use in creating clinical ML models.
Materials And Methods: Evaluation criteria for selecting an Auto ML platform suited to ML needs of a local health district were developed in 3 steps: (1) identification of key requirements, (2) a market scan, and (3) an assessment process with desired outcomes.
Results: The final checklist comprising 21 functional and 6 non-functional criteria was applied to vendor submissions in selecting a platform for creating a ML heparin dosing model as a use case.
Introduction: Clozapine is the gold standard treatment for treatment-resistant schizophrenia, however adverse events remain a clinical challenge.
Areas Covered: This review presents a narrative synthesis of systematic reviews and meta-analyses that have reported the onset, incidence, prevalence, and management of clozapine's adverse events. We conducted a systematic literature search using PubMed, Embase, PsycINFO, OvidMEDLINE, CINAHL, and the Cochrane Database of Systematic Reviews from inception to April 2024.
Background: Clinical pharmacists perform activities to optimise medicines use and prevent patient harm. Historically, clinical pharmacy quality indicators have measured individual activities not linked to patient outcomes.
Aim: To determine the proportion of patients who receive a pharmaceutical care bundle (PCB) (consisting of a medication history, medication review, discharge medication list and medicines information on the discharge summary) as well as investigate the relationship between delivery of this PCB and patient outcomes.
Introduction: Aspirin is used for venous thromboembolism (VTE) prophylaxis after total hip and knee arthroplasty (THA/TKA). However, its efficacy is unclear in patients with multiple VTE risk factors and at risk of aspirin resistance (AR).
Background And Aims: To determine the prevalence of risk factors for VTE and AR in patients after THA/TKA and to determine the relationship between risk factors and drugs prescribed for thromboprophylaxis.
Background: Medication harm affects between 5 and 15% of hospitalised patients, with approximately half of the harm events considered preventable through timely intervention. The Adverse Inpatient Medication Event (AIME) risk prediction model was previously developed to guide a systematic approach to patient prioritisation for targeted clinician review, but frailty was not tested as a candidate predictor variable.
Aim: To evaluate the predictive performance of an updated AIME model, incorporating a measure of frailty, when applied to a new multisite cohort of hospitalised adult inpatients.