Abstract
Background: Treating refractory cardiogenic shock (RCS) adult patients with extracorporeal membrane oxygenation (ECMO) consumes considerable resources with questionable effec-tiveness. By assessing microcirculatory system of individual patients, a new health care tech-nology oxygen delivery index (ODIN) may aid to increase the efficacy and efficiency of the costly ECMO treatment. The aim of this thesis was to build a conceptual framework for ECMO treatment that can be used to approach the early health technology assessment (HTA) of ODIN for RCS adult patients during ECMO treatment. Method: A decision tree and a Markov model have been utilized to construct the conceptual model. It has been revised at every stage of the model development by systematic literature review and experts’ opinion. After finalizing the conceptual model, suggestions for defining and obtaining parameter data and assumptions about how ODIN might affect parameter estimates were concluded using basic economic evaluation knowledge and experts’ opinion. Result: The conceptual model consists of a decision tree and a Markov model. It starts with a decision tree with the RCS patients receiving the ECMO treatment for the first time. There are four clinical responses: total or partial recovery, receiving more durable mechanical heart pump assistance, receiving heart transplant and death. The distribution of the re-sponses was assumed to be affected by age, the clinical causes for receiving ECMO. All the patients who survived the therapy entered the Markov model. It included four described health states: the first remission, the relapse, the second remission, and death. Patients with different clinical responses have different transition probabilities in every health state. The key estimation parameters were: state cost, state utility, transition probability and discount-ing rate. Conclusion: The conceptual frame developed in this thesis can be used to do early HTA of ODIN when more data become available. The conceptual model can also be used to guide the personalized care of ODIN and ECMO and to develop more specific and customized models for solving more problems.