Mobilising Clinical Practice Data to Improve Multidisciplinary Oncology Care

Abstract

As cancer incidence grows, healthcare services are increasingly pressured to provide timely, efficient, evidence-based care. The use of quality indicators are essential to identify and address variations in care delivery and patient outcomes. This thesis aims to inform best-practice quality measurement, feedback, and improvement utilising routinely collected data in cancer care. A systematic review of electronic medical record enabled measurement feedback systems found 12 of 14 studies reported mostly positive outcomes, but were of low-quality and lacking implementation context to replicate findings. A qualitative study identified significant consensus among key informant interviews on factors influencing success of data use and measurement feedback systems. A common theme between the review and interviews was the importance of clinical relevance and engagement. The findings were applied to a case study in colorectal cancer (CRC), including a systematic review and modified Delphi to identify clinically relevant quality indicators and a quantitative study to test the feasibility of the identified indicators against a population-based linked dataset of clinical practice data. The review identified 93 indicators in the literature and 56 CRC professionals prioritised 26 of those indicators. The feasibility study found that only six of the clinically prioritised indicators were feasible using available data in NSW. Feasible indicators were predominantly surgical, whereas indicators related to imaging, (neo)adjuvant therapy, and supportive care were lacking required data. As the use of data and value-based care continues to grow, this thesis provides direction for future data driven quality measurement for clinically meaningful quality improvement. System-wide coordination and standardised data capture, management, and operable exchange is required to transform data and quality indicators into actionable information to improve care.