Pharmacist-assisted electronic prescribing at the time of admission to an inpatient orthopaedic unit and its impact on medication errors: a pre- and postintervention study.

Background: Prescribing and administration errors related to pre-admission medications are common amongst orthopaedic inpatients. Postprescribing medication reconciliation by clinical pharmacists after hospital admission prevents some but not all errors from reaching the patient. Involving pharmacists at the prescribing stage may more effectively prevent errors.

Correction to: A Machine-Learning Algorithm to Optimise Automated Adverse Drug Reaction Detection from Clinical Coding.

CK: Principal Investigator. CM and CK were responsible for the study design and conception; all authors were responsible for acquisition and validation of the data; CM was responsible for analysis and interpretation of the data; and all authors contributed to reviewing drafts of the manuscript and approved the final version for publication.

A Machine-Learning Algorithm to Optimise Automated Adverse Drug Reaction Detection from Clinical Coding.

Introduction: Adverse drug reaction (ADR) detection in hospitals is heavily reliant on spontaneous reporting by clinical staff, with studies in the literature pointing to high rates of underreporting [1]. International Classification of Diseases, 10th Revision (ICD-10) codes have been used in epidemiological studies of ADRs and offer the potential for automated ADR detection systems.

Objective: The aim of this study was to develop an automated ADR detection system based on ICD-10 codes, using machine-learning algorithms to improve accuracy and efficiency.

The Prevalence and Nature of Medication Errors and Adverse Events Related to Preadmission Medications When Patients Are Admitted to an Orthopedic Inpatient Unit: An Observational Study.

Background: Medication errors commonly occur when patients move from the community into hospital. Whereas medication reconciliation by pharmacists can detect errors, delays in undertaking this can increase the risk that patients receive incorrect admission medication regimens. Orthopedic patients are an at-risk group because they are often elderly and use multiple medications.