Contracts to Promote Optimal Use of Optional Diagnostic Tests in Cancer Treatment

In this study, we examine performance-based payment contracts to promote the optimal use of an optional diagnostic test for newly diagnosed cancer patients. Our work is inspired by three trends: tremendous increases in the cost of new, advanced cancer drugs; development of new diagnostic tests to allow physicians to tailor treatment to patients; and changes in healthcare funding models that reward quality care. We model the interaction between two parties—a healthcare payer and an oncologist, in which the oncologist has private information about patients’ characteristics (adverse selection) and the payer does not know whether the oncologist takes the optimal course of action (moral hazard). We show that, in the presence of information asymmetry, a healthcare payer should never incentivize an oncologist to use a diagnostic test for all patients, even if the diagnostic test is available for free. Moreover, although the oncologist has additional information about a patient\u27s risk, he cannot always benefit from this private information. We also find that social welfare may not increase as a result of a decrease in the oncologist\u27s concerns regarding the health outcome of patients. Finally, we show that it is not always socially optimal to make a diagnostic test compulsory even if such a policy can be implemented for free

Three Essays on Incentive Problems of Parties with Potential Conflict of Interest

I study the impact of different incentives on strategic decisions of parties that have the option of cooperating with each other. Incentive problems are well studied in various contexts, such as supply chain management and healthcare operations management. However, in the fast-changing business environment, there is a need to study and understand the new and emerging strategic behaviors of firms to adopt better incentive mechanisms and reach desired outcomes. This dissertation consists of three essays that examine the strategic behavior of parties under different incentive schemes. In the first essay, I study the supply chain partnership of two potential competitors and evaluate the impact of limited capacity on their strategic behavior. An increasing number of original brand manufacturers (OBMs) do not have in-house production capability, and thus rely on competitive contract manufacturers (CCMs) on the supply side. This increasing demand puts CCMs in a capacity allocation dilemma between their own product and the OBM’s product. I derive the conditions that incentivize the two potential competitors to cooperate and compete (coopetition), compete, or only cooperate (supply chain partnership). I show that the OBM might multi-source its component demand only when competition in the final-product market is intense. Moreover, the CCM can be worse off from having more capacity, even when that CCM’s capacity is available for free. The second and third essays are inspired by changes in healthcare funding models that reward quality care. In the second essay, I examine performance-based payment contracts to promote the optimal use of an optional diagnostic test for cancer patients. This essay is inspired by three ongoing trends: tremendous increases in the cost of new advanced cancer drugs, development of new diagnostic tests to allow physicians to tailor treatments to patients, and changes in healthcare funding models that reward quality care. I model the interaction between two parties—a healthcare payer and an oncologist—where the oncologist has private information about the patient’s characteristics (adverse selection) and the payer does not know whether the optimal course of action is used by the oncologist (moral hazard). I demonstrate that, in the presence of information asymmetry, an oncologist should never test all patients, even when the diagnostic test is available for free. I also show that it is not iii always socially optimal to make a diagnostic test compulsory, even if such a policy can be implemented for free. In the third essay, I study gain-sharing agreements between a hospital and a healthcare provider that can only treat a patient and achieve the desired quality of care with collective effort. The Centers for Medicare and Medicaid Services (CMS) introduced a bundled payment model for lower extremity joint replacement (LEJR) that offers hospitals a fixed bundled payment for a patient’s treatment expenses during acute and post-acute care. This bundled payment model aims to incentivize hospitals to enter into agreements with providers to ensure that the total treatment cost and care quality meets the bundled payment requirements. However, I show that the bundled payment does not always incentivize a hospital to offer gain-sharing agreements to the provider. Furthermore, I show that the provider prefers a low bundled payment, such that the hospital needs the provider to reduce the total cost of treatment

Decision analysis in the UK energy supply chain risk management: tools development and application.

The aims of this thesis are developing decision-making tools for risk identification, risk causal relationships analysis, risk prioritisation, and long-term risk mitigation strategy recommendations in the UK energy supply chain. The thesis is comprised of four study phases in eight chapters. In phase I, a framework is introduced including 12 risk dimensions, and 5 classification perspectives. Then, in phase II, the Neutrosophic Revised Decision-Making Trial and Evaluation Laboratory (NR-DEMATEL) method has been utilised in order to analyse the 12 identified risk dimensions based on the causal interrelationships between them. Additionally, a novel Hesitant Expert Selection Model (HESM) to systematically assist researchers with the expert selection process is proposed. In phase III, two extensions of the original Best-Worst Method (BWM) are proposed in order to contribute to the theoretical development and application of the BWM in energy supply chain risk prioritisation. The Neutrosophic Enhanced BWM (NE-BWM) and hybrid Spanning Trees Enumeration and BWM (STE-BWM) are introduced to enhance the efficiency of the original BWM in dealing with uncertainty in experts’ subjective judgements. In phase IV, a novel stratified decision-making model is introduced. It is based on Concept of Stratification (CST), game theory and Shared Socio-economic Pathway (SSP) to deal with long-term risk mitigation planning for the most critical identified risks. The model has been applied in the region of Highland and Argyll in Scotland based on the primary data obtained from experts to prioritise flooding risk mitigation strategies which were recommended by the Scottish Environment Protection Agency (SEPA). The stratified decision-making model is aimed at taking into account both UK socio-economic situations and flooding risk impacts for the long-term decision making