DEMENTIA ECONOMIC MODELLING: DISEASE PREVENTION, DIAGNOSIS AND DISEASE PROGRESSION

Purpose: To address the issues and challenges in developing a comprehensive Dementia model  that is flexible to evaluate a broad range of current and future dementia policies.

Method: A dementia model that can address incidence, diagnosis, and disease progression issues is highlighted in this presentation. A systematic review of existing dementia models was performed to review the methods of economic evaluation and modelling in previous studies in dementia. Expert opinion was sought in developing the conceptual model, finalising the structure and choosing the data sources for the model.

An individual patient-level simulation model incorporated modifiable metabolic risk factors within existing risk scores for dementia to describe the incidence of dementia in the general population. Disease progression is monitored by mini–mental state examination (MMSE) scores, institutionalisation and mortality. Patient pathway included diagnosis, disease progression and transitions in service delivery . The model takes a lifetime perspective, estimating societal costs, clinical outcomes, survival and quality-adjusted life years. The model outcomes also include short-term return on investment data. The model was developed to evaluate the cost-effectiveness of public health interventions modifying BMI, systolic blood pressure and cholesterol and the value of earlier diagnosis.

Result: The systematic review identified 69 relevant articles evaluating pharmacological interventions and diagnostic interventions. The review identified a broad range of literature to inform model parameters and highlighted the importance of using a societal perspective. The new dementia model estimates five year and lifetime costs and QALY gains of modifications to behavioural factors influencing BMI, systolic blood pressure, cholesterol and HbA1c and earlier diagnosis. The cost effectiveness of preventive intervention and early diagnosis of diagnosis is sensitive to a range of assumptions including duration of effect of prevention intervention, intervention cost, and diagnostic accuracy.  Given the level of evidence it is not yet possible to say what combination on preventative interventions and diagnostic procedure would yield the most attractive CE strategy. 

Conclusion: The model is highly flexible and has broad potential application to evaluate different preventative and diagnostic strategies in dementia.