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Quantifying uncertainty in long-term care costs following introduction of new drug therapy: the importance of model choice. Paul McNamee, Alessandra Vanoli, Debbie Hutchings, Ian McKeith, John Bond. In the next 25 minutes. Aims, methods and results of the paper

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Paul McNamee, Alessandra Vanoli, Debbie Hutchings, Ian McKeith, John Bond

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Paul mcnamee alessandra vanoli debbie hutchings ian mckeith john bond

Quantifying uncertainty in long-term care costs following introduction of new drug therapy: the importance of model choice

Paul McNamee, Alessandra Vanoli, Debbie Hutchings, Ian McKeith, John Bond


In the next 25 minutes

In the next 25 minutes...

  • Aims, methods and results of the paper

  • Conclusions and points for discussion


Aims of the paper

Aims of the paper

  • To compare two approaches in modelling the net NHS costs of drug treatment for Alzheimer’s Disease

  • Application of deterministic and probabilistic modelling methods to estimate costs and explore uncertainty about likely “budget impact” to the NHS over 10 years

  • Apply these methods to 3 different policies (ALL, NG1, NG2)


Some background

Some background

  • AD affects a large and growing number of older people

  • Drugs are effective at slowing disease progression

  • Uncertainty over whether they are ‘cost-effective’

  • NICE recommends assessment of “budget impact” for NHS, but only partially done for AD drugs in 2001

  • Recent guidance (March 05) - treatment should no longer be prescribed for new patients


Methods 1

Methods -1

  • Simulate cost impact for AD population (England and Wales)

    • ONS population data

    • MRC ageing study for AD prevalence rates

    • Systematic review of effects of treatment on cognition

    • Long term prognosis from observational studies

  • OLS and GLM regression models estimate cost effect of changes in disease progression


Methods 2 regression models

Ordinary least squares (OLS)

Identity link

Normal (Gaussian) distribution

Generalized Linear Model (GLM)

Log link

Gamma or Negative Binomial Distribution

Methods – 2 Regression models

N=371

dependent variable: weekly cost

Constant term allowed.

independent variables: sex, age, ADL, MMSE


Estimated incremental cost impact over 10 yrs 2002 03 prices m

Estimated incremental cost impact over 10 yrs 2002/03 prices £m


Estimated incremental 10 yr cost per patient 2002 03 prices diff from ols estimate

Estimated incremental 10 yr cost per patient 2002/03 prices £ (% diff from OLS estimate)


Conclusions

Conclusions

  • Drug treatment for AD likely to lead to additional costs to the NHS

  • Choice of modelling method makes a difference to magnitude of estimates


Discussion points

Discussion points

  • A GLM framework for probabilistic analysis more likely to produce outliers

  • Lack of evidence on long term effects

  • Estimates based on 10 year old observations of costs of care

  • Estimates assume full adoption for different NICE policy decisions – but how realistic?

  • How important is the “budget impact” question to local and national decision-makers?


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