Introduction. Dengue is a viral disease affecting 390 million people each year, globally. Tropical countries are mainly affected, like Malaysia, where in 2015, 120,839 cases were reported. To aid dengue diagnosis, point of care rapid tests have been developed. Among the manufacturers, BluSense Diagnostics has developed an innovative test providing higher performance. To evaluate the new diagnostic tool in comparison to current solutions, a cost-utility analysis was performed. Methods. Using an inductive, pragmatic approach, literature describing frameworks of economic evaluation for point-of-care diagnostic devices has been analysed to establish the design principles for the creation of a novel framework. Information was collected on the diagnosis processes, official guidelines, and the management and treatment of patients in Malaysia. This led to the design of a root decision tree model mapping all possible clinical pathways of dengue patients, influenced by test results. The model uses the pathways to describe patients’ clinical conditions, and the related costs and health outcomes (DALYs). Features accounting for medical incompliance and the influence of rapid tests on different stakeholders were added to the model. A user interface was developed, where to introduce input data and change the construction parameters of the model without compromising its functioning. The validity of the model has been tested by performing a oneway sensitivity analysis on all its parameters. Results. The total cost and health outcomes estimates were compared to obtain an incremental cost effectiveness ratio, with the final decision favouring BluSense with 1,568.62 USD saved for every DALY adverted. Conclusions. Although the analysis favours BluSense diagnostic, further research must be conducted to remove the uncertainty around key parameters. With more precise data, the model can be used among different countries and scenarios, and provide quick insights on the cost-effectiveness of different dengue diagnostic solutions.
|Educations||MSc in Business Administration and Innovation in Health Care, (Graduate Programme) Final Thesis|
|Number of pages||135|
|Supervisors||Zorana Jovanovic Andersen|