Business process analytics for healthcare organisations

Healthcare organisations are increasingly pushed to improve the quality of care services in an unfavourable and rapidly changing scenario. Advances in treatments, an ageing population, increased patient expectations, limited resources are some of the factors that have increased the pressures on hospitals. Therefore, improving process efficiency is of utmost importance and represents a critical success factor for healthcare organisations. In order to face these challenges, it is essential to seize the opportunity offered by digitalisation. In fact, digital innovation seems to be the key-driver factor to improve the continuity and the access to care for patients, and to guarantee greater effectiveness, efficiency, and sustainability of healthcare organisations. The widespread adoption of Hospital Information Systems, together with the recent technologies advancements, are allowing hospitals to measure and record an ever-growing volume and variety of patient and process-related data. The availability and the richness of such data pave the way for Business Process Analytics. Business Process Analytics are emerging as suitable data-driven techniques for extracting and analysing data and for providing useful insights to assist decision-making. By properly leveraging Business Process Analytics, e.g., Process Mining, healthcare organisations can analyse and transform their business processes, to achieve internal operational efficiencies and establish competitive advantages. The main goal of the Thesis is to support Business Process Management in healthcare organisations, by exploiting such innovative data-driven techniques, with the final aim of increasing the efficacy and efficiency of healthcare systems. More specifically, this Thesis intents to develop and test new methodologies and models, based on Process Mining and Machine Learning, to help hospital managers in the design, analysis and monitoring of healthcare processes. The case studies included in this Thesis confirm the validity of the proposed approaches and suggest some relevant managerial contributions for supporting healthcare managers.