Almost three-quarters of alerts were overridden, and 40% of the overrides were not appropriate. Future research should optimize alert types and frequencies to increase their clinical relevance, reducing alert fatigue so that important alerts are not inappropriately overridden.

Clinical decision support (CDS) systems link patient data with an electronic knowledge base in order to improve decision-making and computerised physician order entry (CPOE) is a requirement to set up electronic CDS. The medical informatics literature suggests categorising CDS tools into medication dosing support, order facilitators, point-of-care alerts and reminders, relevant information display, expert systems and workflow support. To date, CDS has particularly been recognised for improving processes. CDS successfully fostered prevention of deep-vein thrombosis, improved adherence to guidelines, increased the use of vaccinations, and decreased the rate of serious medication errors. However, CDS may introduce errors, and therefore the term "e-iatrogenesis" has been proposed to address unintended consequences. At least two studies reported severe treatment delays due to CPOE and CDS. In addition, the phenomenon of "alert fatigue" - arising from a high number of CDS alerts of low clinical significance - may facilitate overriding of potentially critical notifications. The implementation of CDS needs to be carefully planned, CDS interventions should be thoroughly examined in pilot wards only, and then stepwise introduced. A crucial feature of CPOE in combination with CDS is speed, since time consumption has been found to be a major factor determining failure. In the near future, the specificity of alerts will be improved, notifications will be prioritised and offer detailed advice, customisation of CDS will play an increasing role, and finally, CDS is heading for patient-centred decision support. The most important research question remains whether CDS is able to improve patient outcomes beyond processes.

Rationale: Glucagon-like peptide-1 receptor (GLP-1R) agonists are approved to treat type 2 diabetes mellitus and obesity. GLP-1R agonists reduce airway inflammation and hyperresponsiveness in preclinical models. Objectives: To compare rates of asthma exacerbations and symptoms between type 2 diabetic adults with asthma prescribed GLP-1R agonists and those prescribed sodium-glucose cotransporter-2 (SGLT-2) inhibitors, dipeptidyl peptidase-4 (DPP-4) inhibitors, sulfonylureas or basal insulin for diabetes treatment intensification. Methods: Electronic health records-based new-user, active comparator, retrospective cohort study of patients with type 2 diabetes and asthma newly prescribed GLP-1R agonists or comparator drugs, January 2000-March 2018. Primary outcome was asthma exacerbations; secondary outcome was encounters for asthma symptoms. Propensity scores were calculated for GLP-1R agonist and non-GLP-1R agonist use. Zero-inflated Poisson regression models included adjustment for multiple covariates. Measurements and Main Results: Patients initiating GLP-1R agonists (n=448), SGLT-2 inhibitors (n=112), DPP-4 inhibitors (n=435), sulfonylureas (n=2,253) or basal insulin (n=2,692), were identified. At six months, asthma exacerbation counts were lower in persons initiating GLP-1R agonists (reference) compared to SGLT-2 inhibitors (incidence rate ratio [IRR], 2.98 [95% CI, 1.30 to 6.80]), DPP-4 inhibitors (IRR, 2.45 [95% CI, 1.54 to 3.89]), sulfonylureas (IRR, 1.83 [95% CI, 1.20 to 2.77]) and basal insulin (IRR, 2.58 [95% CI, 1.72 to 3.88]). Encounters for asthma symptoms were also lower among GLP-1R agonist users. Conclusions: Adult asthmatics prescribed GLP-1R agonists for type 2 diabetes had lower counts of asthma exacerbations compared to other drugs initiated for treatment intensification. GLP-1R agonists may represent a novel treatment for asthma associated with metabolic dysfunction.