This thesis consists of three empirical chapters that studies hospital performance. The thesis attempts to contribute to the existing health and organisational economics, and applied IO literature that study the role of internal factors such as management quality in explaining differences in performance across the hospitals. It examines the role of organisation, management, staff incentives and wellâbeing along with their interactions in driving hospital performance. The first chapter examines the role of organisation and its interactions in explaining variations in quality of care for stroke services. The findings indicate presence of rich complementarities amongst the drivers and strengthen the previous research on managerial and organisational determinants of quality. The chapter uses machine learning techniques to identify the complex interactions and are complemented with traditional econometric approaches. The second chapter studies variations in qualityâadjusted productivity across the NHS trusts and the role of human resource management practices in explaining those variations. Clustering techniques are used to explore the complementarity and clusters of optimal management practices that drive productivity differences and are tested using panel regression techniques. The third chapter studies the problem of hospital delayed transfers of care, and using theories from economics, examines the effectiveness of staff wellâbeing in alleviating delays.