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Co-prescribing of opioids and sedatives is a known risk factor for opioid-induced ventilatory impairment (OIVI). Prevalence data for sedative and opioid co-prescription in inpatients in Australia are unknown. Our objective was to determine the prevalence of inpatient sedative and opioid co-prescribing and to identify factors associated with co-prescription. We conducted a retrospective cross-sectional study from July 2017 to October 2017 across four South Australian hospitals utilizing a centralized electronic health record. Multivariate analysis was used to identify characteristics predictive of co-prescribing of a strong opioid (fentanyl, hydromorphone, morphine, and oxycodone) and sedative medications (benzodiazepines, antiepileptics, antipsychotics, and tricyclic antidepressants). Of the 6170 inpatients, 2795 (45.3%) were prescribed a strong opioid and of those, 1889 (30.6% of all inpatients) were co-prescribed a sedative. Of those prescribed a strong opioid, five (0.18%) developed OIVI. Patients prescribed a strong opioid had a 27–77% increased likelihood of being prescribed a sedative. Factors predictive of sedative co-prescribing included the presence of disease of the central nervous system adjusted OR (aOR) 8.66 [95% CI 5.83–12.9] and respiratory disease aOR 1.42 [95% CI 1.17–1.72]. Nearly, one third of all hospital inpatients were co-prescribed a strong opioid and a sedative medication. Patients with comorbidities resulting in increased risk of respiratory depression/OIVI were more likely to have sedative co-prescription. Clinicians should be aware of the effects of high-risk medications and ensure that systems and monitoring are in place that help mitigate adverse outcomes Refereed/Peer-reviewed

The purpose of this study was to evaluate the quality of adverse drug reaction (ADR) documentation in a state-wide electronic health record (EHR), and to assess the impact of the interface design on documentation accuracy and ability to provide decision support. Data were extracted from 43 011 unique records in a state-wide electronic health record in South Australia, Australia. Information obtained included ADR coding as allergy or intolerance, allergen name, reaction, and occupation of those entering data. Categorization into drug allergy or intolerance was assessed for accuracy. Reactions were entered predominantly by nurses (60.1%), also by doctors (31.0%) and pharmacists (6.1%). Of 27 314 reactions, 86.5% were coded as allergy and 13.5% as intolerance. The majority (78.2%) described reactions to drugs (as opposed to food, environmental or contact allergens), predominantly chosen from the drug database (96.4%). Many entries used free text for the reaction description (27.4%). Terms found in the predefined list under the allergy heading were more likely to be categorized as allergy, even when the mechanism was pharmacological intolerance. Only 45.1% (n = 1671/3705) of reactions consistent with intolerance (eg, "nausea," "diarrhea") were correctly categorized as such, although categorization by pharmacists was more accurate (P < .0001). These data suggest that ADR categorization as allergy or intolerance is influenced by the EHR design. The obligatory classification of ADRs into allergy or intolerance was not well understood and does not appear to have practical benefit. Refereed/Peer-reviewed