A5023508631- Telemedicine and Telehealth Implementation
- Obesity, Physical Activity, Diet
- Child and Adolescent Health
- Mobile Health and mHealth Applications
- Global Public Health Policies and Epidemiology
- Obesity and Health Practices
- Health Policy Implementation Science
- Artificial Intelligence in Healthcare and Education
- Patient Satisfaction in Healthcare
- Electronic Health Records Systems
- Nutritional Studies and Diet
- Birth, Development, and Health
- Health Promotion and Cardiovascular Prevention
- Healthcare cost, quality, practices
- Artificial Intelligence in Healthcare
- Primary Care and Health Outcomes
- Chronic Disease Management Strategies
- Public Health Policies and Education
- Sepsis Diagnosis and Treatment
- Acute Kidney Injury Research
- Community Health and Development
- Patient-Provider Communication in Healthcare
- Stroke Rehabilitation and Recovery
- Social Media in Health Education
- Health Systems, Economic Evaluations, Quality of Life
King's College London
2024-2025
The University of Queensland
2018-2024
The University of Sydney
2024
Australian Government
2021-2024
Queensland Government
2020-2023
Digital Health Cooperative Research Centre
2022-2023
Children’s Health Queensland Hospital and Health Service
2018-2022
Queensland Children’s Hospital
2018
Non-communicable diseases (NCDs) remain the largest global public health threat. The emerging field of precision (PPH) offers a transformative opportunity to capitalize on digital data create an agile, responsive and data-driven system actively prevent NCDs. Using learnings from health, our aim is propose vision toward PPH for NCDs across three horizons transformation: Horizon 1—digital workflows; 2—population analytics; 3—precision health. This perspective provides high-level strategic...
Focusing solely on financial measures is unlikely to deliver a comprehensive view of the value digital health Digital health, which refers use technology provide and support care services, promises strengthen systems worldwide has been accelerated by coronavirus disease 2019 (COVID-19) pandemic.1 Amid rapid transformation care,2, 3 sizeable investments remains unclear.3, 4 The required for are often substantial may come at cost existing delivery models. Decision makers can be paralysed...
There are many Machine Learning (ML) models which predict acute kidney injury (AKI) for hospitalised patients. While a primary goal of these is to support clinical decision-making, the adoption inconsistent methods estimating baseline serum creatinine (sCr) may result in poor understanding models' effectiveness practice. Until now, performance such with different baselines has not been compared on single dataset. Additionally, AKI prediction known have high rate false positive (FP) events...
ABSTRACT Introduction This study aimed to (a) determine the unmet clinical resource needs of multidisciplinary primary healthcare practitioners (PHPs) overcome evidence‐based barriers preventing and managing childhood obesity in practice; (b) co‐design precision solutions identified PHPs. Methods qualitative was conducted across three phases: (1) assessment with 18 PHPs over five virtual focus groups, (2) participatory, user‐centred via an online design workshop four caregivers, (3)...
ObjectiveWith the digital transformation of hospitals having unfolded globally, it is important to understand impacts eHealth on hospital practice. This study aims update two previous narrative reviews systematic and assess: (1) what current state in hospitals? (2) how have these changed over time?MethodsA review investigating impact (i.e. Electronic Medical Records (EMR), Clinical Decision Support System (CDSS), ePrescribing, Computerised Provider Order Entry (CPOE)) published between 2...
Digital disruption and transformation of health care is occurring rapidly. Concurrently, a global syndemic preventable chronic disease crippling healthcare systems accelerating the effect COVID-19 pandemic. Healthcare investment paradoxical; it prioritises treatment over prevention. This an inefficient break-fix model versus person-centred predict-prevent model. It easy to reward invest in acute because activity easily measured therefore funded. Social, environmental behavioural determinants...
Abstract Background Understanding electronic medical record (EMR) implementation in digital hospitals has focused on retrospective “work as imagined” experiences of multidisciplinary clinicians, rather than done” behaviors. Our research question was “what is the behavior clinicians during transition to a new hospital?” Objectives The aim study to: (1) Observe clinical hospital using ethnography. (2) Develop thematic framework hospital. Methods setting go-live greenfield 182-bed specialist...
Smartwatches can count every step towards a predict–prevent health care system, but clinical regulation is the first leap Australia struggling with ever-increasing burden of chronic disease. Over $38 billion per year spent on for people diseases, such as cardiovascular disease, type 2 diabetes, and cancer.1 The majority this funding dedicated to acute care, just 9.6% investment supports disease prevention.1 Perversely, Australia's system rewarded increasing activity (activity-based funding)...
Consumer trust and confidence in telehealth is pivotal to successful service implementation effective consultations. This cross-sectional study measured telephone video consultations associated with experience modalities among people chronic kidney disease at a metropolitan hospital Australia. Self-report data were collected using validated scales 5-point Likert responses. Non-parametric tests used compare (Wilcoxon Matched Pairs) associations (Mann-Whitney). Of the 156 survey participants,...
Abstract Issue addressed Children of Māori & Pacific Islander descent living in Australia have a greater prevalence overweight/obesity and an increased risk adverse health outcomes. This study aimed to co‐design Healthier Together, community‐based, childhood prevention program tailored cultures. Methods Co‐design involved three‐phase, iterative, participatory experience‐based process, guided by the Te Ara Tika: Guidelines for Research Ethics promote respect equity. Following traditional...
Abstract Background Global action to reduce obesity prevalence requires digital transformation of the public health sector enable precision (PPH). Useable data for PPH is yet be identified, collated and appraised there currently no accepted approach creating this single source truth. This scoping review aims address globally generic problem by using State Queensland (Australia) (population > 5 million) as a use case determine (1) availability primary sources usable (2) quality identified...
Wearables hold potential to improve chronic disease self-management in conditions like cystic fibrosis (CF) through remote monitoring, early detection of illness and motivation. Little is known about the acceptability sustainability integrating wearables into routine care from perspectives people with CF (pwCF) their treating clinicians.
Aim To develop and validate a model (i‐PATHWAY) to predict childhood (age 8–9 years) overweight/obesity from infancy 12 months) using an Australian prospective birth cohort. Methods The Transparent Reporting of multivariable Prediction for individual Prognosis or Diagnosis (TRIPOD) checklist was followed. Participants were n = 1947 children (aged the Raine Study Gen2 – cohort who had complete anthropometric measurement data available at follow up. primary outcome overweight obesity years),...
Abstract Background Health services and systems research (HSSR) strategies dedicated to paediatric health care service delivery are limited. Strategies available but outdated yet be optimised for use in a system. We aim describe the development integration of Children’s Service System Research Strategy (CHSSR-S) Queensland (CHQ), large specialist quaternary hospital caring children young people northern New South Wales, Australia. Methods The CHSSR-S was developed using an inductive,...
Aim: Patients' trust and confidence in telehealth are core components of its adoption, effectiveness sustained use. This study aimed to develop validate scales measure using modalities people with chronic kidney disease (CKD).Methods: After developing potential items, 2-phases were conducted investigate construct validity. Phase 1 examined face content validity via: think-aloud patients focus group (n=5), specialists email feedback (n=3) investigators discussion (n=4). 2 used factor...
Objective To co-design artificial intelligence (AI)-based clinical informatics workflows to routinely analyse patient-reported experience measures (PREMs) in hospitals. Methods The context was public hospitals (n=114) and health services (n=16) a large state Australia serving population of ~5 million. We conducted participatory action research study with multidisciplinary healthcare professionals, managers, data analysts, consumer representatives industry professionals across three phases:...