Data Envelopment Analysis in de Gezondheidszorg: Nieuwe Inzichten voor Efficiëntie en Waardegedreven Zorg

Healthcare systems are designed to maintain and improve human health. Yet, in recent decades, these systems have been struggling to sustain their own health due to rising expenditures that outpace available budgets. This growing financial pressure requires healthcare providers to actively strive for cost-efficient care, meaning additional investments should translate into better quality of care, while cost reductions should not compromise patient outcomes, in line with the principles of Value-Based Healthcare (VBHC). Navigating this complex balance requires analytical methods that explicitly link resource use to health outcomes in order to support well-informed decision-making. Data Envelopment Analysis (DEA) offers such opportunities, as it enables the simultaneous evaluation of multiple inputs and multiple outcomes without requiring predefined trade-offs between them. Although DEA is widely used to assess efficiency in healthcare, traditional applications typically rely on aggregated data and rarely incorporate quality metrics such as patient-centred outcomes, limiting their relevance for VBHC. This dissertation, therefore, explores how DEA can be applied in innovative ways to support the transition toward more efficient and value-based healthcare. In collaboration with three Belgian hospitals, the research adapts DEA to more granular units of analysis, including care processes and individual patients, and integrates it with operations management methods and management accounting techniques. At the process level, DEA combined with Discrete-Event Simulation is applied to evaluate hybrid outpatient appointment scheduling with integrated teleconsultations. The same methodology is used to assess Just-in-Time surgical case cart preparation, demonstrating improvements in efficiency and operational decision-making. At the patient level, a four-step framework is developed to combine individual costs with multiple clinical and patient-reported outcomes into a single value score using DEA and Time-Driven Activity-Based Costing. This framework enables benchmarking patients based on value and is first applied to psoriasis care within an integrated practice unit. It is further used in a comparative analysis of conventional versus robot-assisted Total Knee Arthroplasty, demonstrating the generalizability of the proposed approach. Overall, the dissertation shows that DEA, when adapted to process- and patient-level analyses, can serve as a practical decision-support tool to explicitly link costs to outcomes and to advance the operationalization of value-based healthcare.