3.3. Cost-effectiveness of personalised diabetes treatment

Associations of biomarkers, risk factors and situational issues with hard outcomes such as hospitalizations (that can be economically valued) will be investigated using secondary analysis on clinical trials and analysis of real-world data to identify patient subgroups most benefiting or being minimally harmed with targeted therapies.

The project is in the context of a PhD with building blocks being

1. Reviews on current health economic models in diabetes precision medicine;
2. Analyses of burden of diabetes comorbidities and non-adherence;
3. Associations of diabetes comorbidities with clinical & economic outcomes;
4. Consideration of risk factors in secondary analyses of clinical trials; and
5. Integration in a health-economic model, potentially building on existing models (such as the CORE-model).

To pave the way for cost-effectiveness analyses of personalized diabetes treatment.

This project includes the essential steps for developing a new health economic diabetes model that is able to assess personalized medicine (1) describe the currently available models and their fitness to assess personalized medicine, (2) assess associations of real-life patient characteristics (non-adherence, comorbidities, biomarkers) with morbidity and mortality, (3) incorporate these personalized patient profiles and develop and validate a new health economic model

For chapters 1-2: literature reviews
For chapter 3-4: GIANTT real-world database analyses
For chapter 5-6: modelling using R and/or Excel

1. State-of-the-art review of current health economic diabetes models: are they with for personalized medicine?;
2. The clinical and economic burden of comorbidities in diabetes;
3. Associations of diabetes comorbidities with hospitalizations and mortality;
4. Associations of non-adherence with hospitalizations and mortality;
5. The design and validation of a health economic diabetes model to assess personalized medicine;
6. Cost-effectiveness analyses of several personalized diabetes treatments.

This project will give insight in the current status of the health economic assessments of personalized diabetes treatment, and provide an optimized model taking into account patient heterogeneity.

Important links can be made within the Drug Regulation Domain and the Drug Application Domain. This may lead to expanding the patient-level factors that will be assessed in reimbursement decision making; as well as support healthcare professionals in making personalized decisions.