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Falls among adults over 60 are a global health concern, including Australia.This study aimed to investigate temporospatial fall alert patterns-across time and location-detected by ambient fall detection sensors in three Australian aged care settings, to inform fall prevention strategies.A mixed-methods approach was used to analyze fall alert patterns and fall risks. Ambient fall detection sensors collected data from three care settings (residential aged care facilities [RACFs], retirement villages [RVs], and [...]

The effective operation of magnetic resonance imaging (MRI) systems relies on physical interactions with complex imaging environments, equipment, and user interfaces (UIs). However, there is limited empirical data evaluating how physical interactions with MRI equipment and accessories, workspace configuration, MRI UI design, and technical proficiency influence clinical workflow.In this study, a cross-sectional survey was conducted among MRI end-users, across public and private health facilities (n = 13), using a structured questionnaire to [...]

As the use of artificial intelligence (AI) in healthcare is rapidly expanding, there is also growing recognition of the need for ongoing monitoring of AI after implementation, called algorithmovigilance. Yet, there remain few systems that support systematic monitoring and governance of AI used across a health system. In this study, we identify end-user needs for a novel AI monitoring system-the Vanderbilt Algorithmovigilance Monitoring and Operations System (VAMOS)-using human-centered design (HCD).

Phone surveys are crucial for collecting health data but are expensive, time-consuming, and difficult to scale. To overcome these limitations, we propose a survey collection approach powered by conversational Large Language Models (LLMs).

Describing the development of a visual dashboard leveraging available tools for efficient recruitment for patient centered clinical trials in resource constrained settings.

Clinical trial data is still predominantly manually entered by site staff into Electronic Data Capture (EDC) systems. This process of abstracting and manually transcribing patient data is time-consuming, inefficient and error prone. Use of Electronic Health Record to Electronic Data Capture (EHR-To-EDC) technologies that digitize this process would improve these inefficiencies.

To engage end-users to develop and evaluate an algorithm to convert electronic adherence monitoring device (EAMD) output into the adherence data required for analyses.

Deprescribing is the clinically supervised process of stopping or reducing medications that are no longer beneficial. MedSafer is an electronic decision support tool that guides healthcare providers (HCPs) through the deprescribing process. We recently developed a novel patient-facing version of the software, allowing patients and caregivers to generate a personalized deprescribing report to bring to their prescriber.

Medical examiners and coroners (ME/C) oversee medicolegal death investigations which determine causes of death and other contextual factors that may have influenced a death. We utilize open data releases from ME/C offices covering 6 different geographic areas to demonstrate the strengths and limitations of ME/C data for forensic epidemiology research.

Health informatics continues to be a continuously evolving discipline. As a result, faculty in health informatics training programs cover a broad range of topics and work in highly diverse academic contexts. This is a strength of the field, and also introduces challenges in understanding faculty salary ranges and assessing potential salary disparities across contexts. Although limited studies have been done on salary ranges in specific academic contexts, prior to this [...]