Clinical Data Science in Lung Cancer Multidisciplinary Team Care

Abstract

Lung cancer remains a major cause of cancer morbidity and mortality around the world. It is the most common cause of cancer in men worldwide, there were nearly 2.1 million new cases globally in 2018 according to GLOBOCAN data and in Australia, lung cancer is the commonest cause of cancer death in both men and women. The practice of lung cancer care within multidisciplinary teams (MDTs) has become progressively more common around the world and in many countries is regarded as best practice and standard of care. As MDTs have evolved, the methods of data collection and reporting have also changed, evolving from informal settings with minimal data collection to highly organised prospective recording of clinical information, regular audit and data integration as for example in the National Lung Cancer Audit in the United Kingdom. The work presented in this thesis aims to explore the use of clinical data by lung cancer multidisciplinary teams, to identify gaps in routine data organisation and use by clinicians and to develop datasets and feedback strategies that can lead to better clinical outcomes. Chapter 1 explores the background to multidisciplinary team care, outlines the methodology and provides the context for this body of work. Chapter 2 reviews the current literature on data use by multidisciplinary lung cancer teams across a range of settings (established teams, comprehensive cancer centres, emerging MDT services) and in different countries (Australia, UK, USA in particular). Chapter 3 explores the use of local MDT and cancer registry data to compare a range of clinical outcomes between lung cancer patients managed with and without MDT input. Chapter 4 develops optimal datasets (AMDAT datasets, Australian MDT Data) for lung cancer MDT collection, resulting from a modified Delphi consensus process involving MDT clinicians across Australia. Chapter 5 presents the results of a pilot data feedback study, based on the AMDAT datasets, to 3 separate lung cancer MDTs. Chapter 6 is a discussion chapter linking the results from Chapters 2 to 5, which summarizes the findings of the thesis, relates them to current understanding of lung cancer MDT use of data and develops concepts for future research into the best use of clinical data to optimize lung cancer MDT outcomes.