1. Accounting for Psychological Determinants of Treatment Response in Health Economic Simulation Models of Behavioural Interventions A Case Study in Type 1 Diabetes Jen Kruger 1, Alan Brennan 1, Praveen Thokala 1, Debbie Cooke 2, Rod Bond 3 and Simon Heller 4 1 Health Economics and Decision Science, ScHARR, University of Sheffield, UK., 2 Department of Epidemiology & Public Health, University College London, UK., 3 School of Psychology, University of Sussex, UK., 4 Academic Unit of Diabetes, Endocrinology and Metabolism, University of Sheffield, UK. Health economic modelling has paid limited attention to incorporating the effects patients’ psychological characteristics can have on the effectiveness of a treatment. In attempting to represent the real world this is a substantial limitation, particularly when modelling diseases that involve a large element of self-care or when evaluating interventions that aim to change health behaviours. The objective of this study was to test the feasibility of incorporating psychological prediction models of treatment response within an economic model of a diabetes structured education programme: Dose Adjustment For Normal Eating (DAFNE). Introduction Data from the National Institute for Health Research (NIHR) DAFNE Research Programme were used to support all analyses*. Three regression models were used to investigate the relationships between patients’ baseline psychological characteristics (e.g. beliefs about diabetes, confidence in performing self-care behaviours, fear of hypoglycaemia) and their 12-month blood glucose (% HbA 1c ) response to DAFNE. The regression prediction models were integrated with a patient- level simulation model of type 1 diabetes (Sheffield Type 1 Diabetes Model) to evaluate the cost-effectiveness of two new policies: 1.Providing DAFNE only to predicted responders 2.Offering a follow-up intervention to predicted non-responders Response was defined as a reduction in HbA 1c of 0.5% or more. Both new policies were compared with current practice of providing DAFNE to all adults with type 1 diabetes and not offering a follow-up intervention. The model estimated costs and quality-adjusted life-years (QALYs) over a 50-year time horizon from a UK National Health Service (NHS) perspective. Deterministic sensitivity analyses were conducted. Methodology By collecting data on psychological variables for a subgroup of patients before an intervention, we can construct predictive models of treatment response to behavioural interventions and incorporate these into health economic simulation models to investigate more complex treatment policies. Further research using this methodology is indicated. Conclusions Psychological predictors of treatment response were successfully integrated with the health economic simulation model and allowed new treatment policies to be evaluated. The results suggest that providing DAFNE only to predicted responders is dominated by current practice (incremental costs ranged from £297 to £616 and incremental QALYs from –0.112 to –0.209) (see Figure 1). This result was insensitive to the psychological prediction model used and to the majority of sensitivity analysis assumptions tested (sensitivity analysis results not shown). The results suggest that providing a follow-up intervention to predicted non-responders dominates current practice (see Figure 2). This result was sensitive to model assumptions regarding the treatment benefit of the follow-up intervention (see Figure 2). Results The psychological prediction models had low predictive power for HbA 1c change, suggesting alternative predictor variables or model functional forms may be required. The results of this study demonstrate that improvements can be made to the way we model the cost-effectiveness of interventions in disease areas where patients’ psychological and behavioural characteristics are important. The next phase of development of the Sheffield Type 1 Diabetes Model is to fully capture parameter uncertainty in a full probabilistic sensitivity analysis. Discussion * This study was funded by the NIHR. This poster presents independent research commissioned by the NIHR under the Programme for Applied Research. The views expressed in this poster are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health. Figure 1 The cost-effectiveness of providing DAFNE only to predicted responders vs. current practice Figure 2 The cost-effectiveness of providing a follow-up intervention costing the same as the original DAFNE intervention vs. current practice Contact: J. Kruger Postal address: ScHARR, Regents Court, 30 Regent Street, Sheffield S1 4DA, United Kingdom. Email: j.kruger@shef.ac.uk Website: www.shef.ac.uk/heds Contact