Standardizing imaging findings representation: harnessing Common Data Elements semantics and Fast Healthcare Interoperability Resources structures.

Objectives: Designing a framework representing radiology results in a standards-based data structure using joint Radiological Society of North America/American College of Radiology Common Data Elements (CDEs) as the semantic labels on standard structures. This allows radiologist-created report data to integrate with artificial intelligence-generated results for use throughout downstream systems.

Materials And Methods: We developed a framework modeling radiology findings as Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) observations using CDE set/element identifiers as standardized semantic labels.

Integrating and Adopting AI in the Radiology Workflow: A Primer for Standards and Integrating the Healthcare Enterprise (IHE) Profiles.

The deployment of artificial intelligence (AI) solutions in radiology practice creates new demands on existing imaging workflow. Accommodating custom integrations creates a substantial operational and maintenance burden. These custom integrations also increase the likelihood of unanticipated problems.

Understanding and Mitigating Bias in Imaging Artificial Intelligence.

Artificial intelligence (AI) algorithms are prone to bias at multiple stages of model development, with potential for exacerbating health disparities. However, bias in imaging AI is a complex topic that encompasses multiple coexisting definitions. may refer to unequal preference to a person or group owing to preexisting attitudes or beliefs, either intentional or unintentional.

How Patient-Centred Are Inhaler Device Choices? A Survey of Canadian Prescribers.

Background: The choice of inhaler device type can play a crucial role in managing asthma and chronic obstructive pulmonary disease (COPD). With various devices available, differences in choice and application may lead to confusion for both prescribers and patients. Furthermore, improper use of a device may lead to suboptimal or inadequate treatment.

Prescribing Portraits to Optimize Prescribing of Proton Pump Inhibitors in Long-Term Care: PPI-T STOP Study.

Background: Proton pump inhibitors (PPIs) are among the most commonly prescribed medications in Canada, particularly for older adults (at least 65 years of age). Overprescribing of long-term PPIs leads to health care system waste and is associated with adverse effects, including infections and fractures. The high prevalence of PPI prescribing in long-term care (LTC) facilities prompted an evaluation of systematic approaches to PPI deprescribing.

Switching Topical Diclofenac from Higher to Lower Strength: Financial and Clinical Evaluation.

Background: In February 2020, the Fraser Health Authority in British Columbia introduced an automatic therapeutic interchange policy, whereby orders for any strength of topical diclofenac would be automatically interchanged to the commercially available diclofenac 2.32% gel for twice-daily administration. The new policy was intended mainly as a cost-saving measure but had the potential for clinical impacts that needed to be considered.

Evaluation of Climate-Aware Metrics Tools for Radiology Informatics and Artificial Intelligence: Toward a Potential Radiology Ecolabel.

Radiology is a major contributor to health care's impact on climate change, in part due to its reliance on energy-intensive equipment as well as its growing technological reliance. Delivering modern patient care requires a robust informatics team to move images from the imaging equipment to the workstations and the health care system. Radiology informatics is the field that manages medical imaging IT.

Diffusion-weighted imaging of the orbit.

Orbital lesions compose a heterogeneous group of pathologies that often present with non-specific imaging findings on conventional magnetic resonance imaging (MRI) sequences (T1-and T2-weighted). Accordingly, the application of diffusion MRI offers an opportunity to further distinguish between lesions along this spectrum. Diffusion-weighted imaging (DWI) represents the simplest and most frequent clinically utilised diffusion imaging technique.

Deep Learning for Detection of Pneumothorax and Pleural Effusion on Chest Radiographs: Validation Against Computed Tomography, Impact on Resident Reading Time, and Interreader Concordance.

Purpose: To study the performance of artificial intelligence (AI) for detecting pleural pathology on chest radiographs (CXRs) using computed tomography as ground truth.

Patients And Methods: Retrospective study of subjects undergoing CXR in various clinical settings. Computed tomography obtained within 24 hours of the CXR was used to volumetrically quantify pleural effusions (PEfs) and pneumothoraxes (Ptxs).

Hiding in Plain Sight: Quantifying Salbutamol and Ipratropium Inhaler Wastage in Hospitals.

Background: Previous studies have found significant inhaler wastage in the inpatient setting, which contributes to unnecessary health care expenditures. Wastage may involve inhalers available in automated dispensing cabinets (ADCs).

Objectives: To evaluate whether salbutamol and ipratropium inhalers were unnecessarily withdrawn from ADCs for hospital inpatients.

Recycling unused medications in hospitals is financially viable and good for the environment.

Objectives: Considerable pharmaceutical waste is generated in hospital settings which can be reduced by recycling of unused medications. We sought to determine the recycling practices as well as quantify the volume and the value of oral solid medications returned from nursing units to the pharmacy departments at three urban hospitals.

Methods: Unused oral solid medications were recycled at three sites and the net financial impact of this practice was calculated (cost recovered - labour costs).

Artificial Intelligence and Radiology Education.

Implementation of artificial intelligence (AI) applications into clinical practice requires AI-savvy radiologists to ensure the safe, ethical, and effective use of these systems for patient care. Increasing demand for AI education reflects recognition of the translation of AI applications from research to clinical practice, with positive trainee attitudes regarding the influence of AI on radiology. However, barriers to AI education, such as limited access to resources, predispose to insufficient preparation for the effective use of AI in practice.

American Society of Emergency Radiology (ASER) social media committee workgroup: best practices for the use of social media in emergency radiology.

Social media has become integrated within the profession of medicine, and emergency radiology has inevitably felt the impact of its presence. Emergency radiologists are encouraged to consider the advantages of embracing the digital era and the benefits it may bring to our careers. We aim to present the best practice guidelines for emergency radiologists and radiology departments.

Performance of Multiple Pretrained BERT Models to Automate and Accelerate Data Annotation for Large Datasets.

Purpose: To develop and evaluate domain-specific and pretrained bidirectional encoder representations from transformers (BERT) models in a transfer learning task on varying training dataset sizes to annotate a larger overall dataset.

Materials And Methods: The authors retrospectively reviewed 69 095 anonymized adult chest radiograph reports (reports dated April 2020-March 2021). From the overall cohort, 1004 reports were randomly selected and labeled for the presence or absence of each of the following devices: endotracheal tube (ETT), enterogastric tube (NGT, or Dobhoff tube), central venous catheter (CVC), and Swan-Ganz catheter (SGC).

Evidence showing lipotoxicity worsens outcomes in covid-19 patients and insights about the underlying mechanisms.

We compared three hospitalized patient cohorts and conducted mechanistic studies to determine if lipotoxicity worsens COVID-19. Cohort-1 (n = 30) compared COVID-19 patients dismissed home to those requiring intensive-care unit (ICU) transfer. Cohort-2 (n = 116) compared critically ill ICU patients with and without COVID-19.