Outcome-Based Contracting

This research was conducted by Jong-Jang Lin, Yi-Kuei Lin, Louis Cheng-Lu Yeng, and Ruey-Huei Yeh. It was published in the Annals of Operations Research. The study proposes a novel risk equilibrium outcome-based contract (OBC) model with a given multi-outcome in maintenance service. The model solves the multi-criteria obligation problem in a complex repairable system maintenance service to achieve three objectives: searching for a dominant risk equilibrium and inner cost, attaining the system's expected outcome, and controlling the multi-outcome and risk equilibrium. The model can apply to disparate maintenance policies comprising various preventive and corrective maintenance methods. The case study shows that the proposed OBC model forms a game-theoretical equilibrium for both parties, ensuring the risk equilibrium with the optimal cost.

This research was conducted by Jose Luis Poveda, Rosa Bretón-Romero, Carlos Del Rio-Bermudez, Miren Taberna, and Ignacio H. Medrano. It was published in the Journal of Pharmaceutical Policy and Practice. The study discusses how artificial intelligence, specifically Natural Language Processing (NLP), can optimize value-based contracts (VBCs) in the pharmaceutical market. The authors argue that the extraction and analysis of massive amounts of real-world evidence (RWE) captured in patients’ electronic health records (EHRs) can circumvent issues associated with VBCs and optimize negotiations. The use of NLP enables the real-time evaluation of treatment response and financial impact in real-world settings, which can be beneficial in the context of innovative contracting.