Quality-driven Efficiency in Healthcare

During the upcoming decades, healthcare organizations face the challenge to deliver more patient care, of higher quality, and with less financial and human resources. The goal of this thesis is to help and guide healthcare professionals making their organizations future-proof. Building on techniques from Operations Research, a subfield of applied mathematics, and focusing on the management of operations, the research presented contributes to a better understanding and functioning of healthcare delivery. The outcomes support decision makers in realizing the best possible use of available resources. The work presented intends to make healthcare professionals more aware of the added value of taking an integral perspective on logistical decision making. First, the problems addressed emphasize the importance of integrality in terms of objectives: healthcare must be safe, effective, patient-centered, timely, efficient, and equitable. While the traditional belief is that quality and efficiency always confront each other, we demonstrate that they often can, and must, go hand in hand. Second, the research outcomes show the value of integrality in planning and control: performance is enhanced by aligning long-, medium-, and shortterm decision making and by realizing coordination and collaboration between the various care chain actors. The thesis is organized in six parts. Part I provides a general introduction. Part II provides an overview of the field of resource capacity planning and control in healthcare and a review of the state of the art in Operations Research. It sets up the conceptual framework within which several specific decision problems are studied in the following parts. Part III focuses on facilitating combination appointments during single outpatient visits, and Part IV on multidisciplinary treatments requiring a series of outpatient visits. Part V supports the design and operations of inpatient care services. Part VI builds a theoretical framework to model entire care pathways. In Part III–Part VI, a diversity of operations research techniques (often in combination) is applied: computer simulation, heuristics, Markov processes, mathematical programming, queueing theory, and stochastic Petri nets. Based on the obtained results, in the epilogue we claim that Operations Research can play a key role in addressing the tough logistical challenges healthcare organizations face.