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:
[email protected] Website: www.shef.ac.uk/heds Contact