The HOTspots Digital Surveillance: Conceptualisation to Clinical Deployment.

The HOTspots digital surveillance platform (HOTspots) is a critical technology of the HOTspots Surveillance and Response Program. It provides timely point-of-care access to pathology and demographic data from previously underserved regions. Co-designed with clinicians, epidemiologists, and health policy makers, the platform provides the evidence-base to empower efficient clinical management of patients with antimicrobial resistant (AMR) infections and supports national disease surveillance efforts in Australia.

CBL on FHIR: A FHIR-Based Platform for Health Professional Education.

A FHIR based platform for case-based instruction of health professions students has been developed and field tested. The system provides a non-technical case authoring tool; supports individual and team learning using digital virtual patients; and allows integration of SMART Apps into cases via its simulated EMR. Successful trials at the University of Queensland have led to adoption at the University of Melbourne.

Leveraging Unlabeled Clinical Data to Boost Performance of Risk Stratification Models for Suspected Acute Coronary Syndrome.

The performance of deep learning models in the health domain is desperately limited by the scarcity of labeled data, especially for specific clinical-domain tasks. Conversely, there are vastly available clinical unlabeled data waiting to be exploited to improve deep learning models where their training labeled data are limited. This paper investigates the use of task-specific unlabeled data to boost the performance of classification models for the risk stratification of suspected acute coronary syndrome.

A Decision Support System for Pathology Test Result Reviews in an Emergency Department to Support Patient Safety and Increase Efficiency.

The review of pathology test results for missed diagnoses in Emergency Departments is time-consuming, laborious, and can be inaccurate. An automated solution, with text mining and clinical terminology semantic capabilities, was developed to provide clinical decision support. The system focused on the review of microbiology test results that contained information on culture strains and their antibiotic sensitivities, both of which can have a significant impact on ongoing patient safety and clinical care.

A SMART on FHIR Prototype for Genomic Test Ordering.

Queensland Genomics recently undertook a number of Clinical Demonstration Projects (CDPs) to demonstrate the benefits of genomics in clinical practice. Integration of this testing requires the health system to provide the infrastructure for the appropriate ordering of these tests. Ordering of genomics tests will likely require greater exchange of information between the ordering clinician and the lab that is producing a clinical test report.

Computer-Assisted Diagnostic Coding: Effectiveness of an NLP-based approach using SNOMED CT to ICD-10 mappings.

Computer-assisted (diagnostic) coding (CAC) aims to improve the operational productivity and accuracy of clinical coders. The level of accuracy, especially for a wide range of complex and less prevalent clinical cases, remains an open research problem. This study investigates this problem on a broad spectrum of diagnostic codes and, in particular, investigates the effectiveness of utilising SNOMED CT for ICD-10 diagnosis coding.

Assessing colonoscopic inspection skill using a virtual withdrawal simulation: a preliminary validation of performance metrics.

Background: The effectiveness of colonoscopy for diagnosing and preventing colon cancer is largely dependent on the ability of endoscopists to fully inspect the colonic mucosa, which they achieve primarily through skilled manipulation of the colonoscope during withdrawal. Performance assessment during live procedures is problematic. However, a virtual withdrawal simulation can help identify and parameterise actions linked to successful inspection, and offer standardised assessments for trainees.

Radiation exposure during scoliosis surgery: a prospective study.

Background Context: The present literature on the cancer risks related to radiation exposure in patients and surgeons during scoliosis surgery is sparse.

Purpose: To assess the radiation exposure in patients and surgeons during scoliosis surgery and estimate the increased cancer risk of both groups.

Study Design: Over a 6-month period, we conducted a prospective study to monitor the intraoperative radiation dose received by both patients and surgeons during scoliosis cases.