F.G. Zmudzki

Fred is a senior health economist and policy analyst, with extensive experience across a wide range of projects covering industry, academic research and government. Fred’s experience is particularly focused on economic cost effectiveness and evaluation frameworks, including physical and mental health, disability, and government support programs. His research focus, publications and commissioned evaluation projects include a range of policy and service model initiatives, health economic program evaluation, and cost utility modelling and analysis.

Fred's PhD research project is focusing on chronic musculoskeletal pain (CMP) treatment, investigating the potential machine learning contribution for clinician decision support and patient outcomes. 

Given the complex nature of chronic pain there is no single reliable clinical measure to assess outcomes from multimodal pain programs. So, there is no single endpoint to train machine learning algorithms. In this context, this research is investigating a multidimensional machine learning framework of 13 outcome measures across 5 clinically relevant domains including activity/disability, pain, fatigue, coping and quality of life.

The project will explore potential improved patient assessment, engagement, and personalised goal setting, as well as implications for Interdisciplinary Multimodal Pain Treatment (IMPT) cost effectiveness.

The project research design integrates clinical and health economic components with a novel machine learning approach for investigating the complex IMPT patient cohort. There is potential wider scientific relevance for other clinical diagnoses which do not have single reliable outcome measures. And IMPT has extensive implications for patients who have often already exhausted all clinical pain treatment options. So successful IMPT intervention can achieve life changing improvements and may have long reaching implications for patients and society.