Toward value-based care using cost mining: cost aggregation and visualization across the entire colorectal cancer patient pathway.

Background: The aim of this study is to develop a method we call "cost mining" to unravel cost variation and identify cost drivers by modelling integrated patient pathways from primary care to the palliative care setting. This approach fills an urgent need to quantify financial strains on healthcare systems, particularly for colorectal cancer, which is the most expensive cancer in Australia, and the second most expensive cancer globally.

Methods: We developed and published a customized algorithm that dynamically estimates and visualizes the mean, minimum, and total costs of care at the patient level, by aggregating activity-based healthcare system costs (e.

Profiling current cancer survivorship practices and enhancing survivorship care in public hospitals in Victoria, Australia.

Purpose: Comprehensive survivorship care involves cancer surveillance, management of post-treatment effects, health promotion and coordination between care sectors. This study aimed to understand current survivorship practices, build awareness and support improved survivorship care in Victoria, Australia.

Methods: This project had three components: (1) a survey of 20 Victorian clinical sites, assessing elements described in the Victorian Quality Cancer Survivorship Framework; (2) educational webinars for oncology health professionals, to increase survivorship knowledge and awareness; (3) implementation of targeted survivorship care quality initiatives in a sample of health services.

Co-design of an electronic patient-reported outcome symptom monitoring system for immunotherapy toxicities.

Background: Utilising electronic patient-reported outcomes (ePRO) to monitor symptoms can improve patient outcomes. However, ePRO systems are typically not co-designed with end-users which may limit their utility and long-term sustainability. We aimed to co-design a real-time ePRO symptom monitoring system for immune checkpoint inhibitor (ICI) toxicities.

Application of Artificial Intelligence in Symptom Monitoring in Adult Cancer Survivorship: A Systematic Review.

Purpose: The adoption of artificial intelligence (AI) in health care may afford new avenues for personalized and patient-centered care. This systematic review explored the role of AI in symptom monitoring for adult cancer survivors.

Methods: A comprehensive search was performed from inception to November 2023 in seven bibliographic databases and three clinical trial registries.