TRANSFERABILITY OF PHARMACOECONOMIC DATA

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TRANSFERABILITY OF PHARMACOECONOMIC DATA

• Maciej Niewada, MD, PhD
• Department of Pharmacology
• Medical University of Warsaw

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Main resources

• Generalisability in economic evaluation studies
  in healthcare a review and case studies by MJ
  Sculpher et al. Health Technology Assessment
  2004 Vol. 8 No. 49
• Generalizability of economic evaluations Using
  results from other geographic areas or from
  multinational trials to help inform health care
  decision making in Canada Ron Goeree. Ontario
  April 26, 2005.
• GUIDELINES FOR THE ECONOMIC EVALUATION OF HEALTH
  TECHNOLOGIES CANADA 2006 available
  www.cadth.ca

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TRANSFERABILITY

• applicability
• exchangeability
• extrapolation
• external validity
• generalizability
• portability
• relevance
• transportability

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Definition (1)

• the problem of whether one can apply or
  extrapolate results obtained in one setting or
  population to another.

Willke RJ. Tailor-made or off-the-rack? The
problem of transferability of health economic
data . Expert Rev Pharmacoecon Outcomes Res
20033(1)1-4.
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Definition (2)

• Usually refers to extent data collected on a
  particular patient population, under unique study
  circumstances, at a particular point in time,
  treated in a particular way, can be applied to
  another group of patients, under different study
  circumstances, at another point in time or under
  different treatment conditions
• Applies to both cost and clinical effectiveness
  data

Generalizability of economic evaluations Using
results from other geographic areas or from
multinational trials to help inform health care
decision making in Canada. Goeree R.
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The key question

• Are there differences in an interventions
  impact on effectiveness and costs across settings
  or locations that produce meaningful differences
  in cost-effectiveness?

Willke RJ. Tailor-made or off-the-rack? The
problem of transferability of health economic
data . Expert Rev Pharmacoecon Outcomes Res
20033(1)1-4.
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Present status

• over 70 factors which are of potential concern
  when conducting transferability studies or
  analyzing multinational economic evaluations
• the most frequently cited factors are
• absolute or relative prices,
• clinical practice,
• treatment efficacy
• and demographics
• Several papers have demonstrated differences in
  the volume and cost of resource use between
  locations, but few studies have looked at
  variability in outcomes.

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Variability Factors

• Methodological Characteristics
• Health Care System Characteristics
• Provider Characteristics
• Disease Characteristics
• Patient Characteristics

Generalizability of economic evaluations Using
results from other geographic areas or from
multinational trials to help inform health care
decision making in Canada. Goeree R.
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There are three aspects ofgeneralizability to be
addressed

• distinction between efficacy and effectiveness
  of the intervention
• handling of data on costs and preferences
  (utilities) that are derived from another setting
• handling of data from trials involving several
  countries, including that of the decision maker.

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Effectiveness

• first criterion that is addressed in determining
  study generalizability.
• most relevant to the decision maker (i.e., the
  external validity of the clinical trial).

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Economic data

• 1. Cost
• vary from country to country, reflecting
  differences in resources use patterns and
  relative unit cost levels
• 2. Preferences for health states
• depend on cultural factors that vary among
  countries

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Adaptation of cost data

• Not simply converting prices from US to
  Australian
• PPP
• the method of using the long-run equilibrium
  exchange rate of two currencies to equalize the
  currencies' purchasing power.
• a U.S. dollar exchanged and spent in the People's
  Republic of China will buy much more than a
  dollar spent in the United States.
• Medical Component of the Consumer Price Index
  (MCPI)

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Modelling techniques

• To adjust observed data about practice patterns
  from other countries or settings to apply to
  local circumstances and then use local unit costs
  in the model
• Adaptation of cost effectiveness based on trial
  data to non-trial settings

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Unit costs

• Most frequent factor generating variability in
  economic results
• selection of study sites should ideally focus on
  those that are representative of the
  jurisdiction(s)
• Together with preferences subject for extensive
  sensitivity analysis

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Cost-effectiveness

• studies based on the analysis of patient-level
  data - regression analysis advocated as a means
  of looking at variability in economic results
  across locations.
• use of tests of heterogeneity similar to those
  used in clinical evaluation in trials

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Multinational studies

• whether to pool data collected from all countries
  or to use data from the centres or countries that
  are most applicable to the decision makers
  setting
• Factors affecting analyses of multinational trial
  data
• clinical practice
• unit prices
• health care system

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Multinational studies

• clinical data can be pooled, although this may
  not be the case for all interventions, and tests
  of homogeneity should be performed
• in contrast, it is generally assumed that
  economic data will differ systematically between
  multinational centres, and therefore pooling will
  be impossible.

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Methods of handling economic data from
multinational trials

• multi-level modelling (MLM)
• empirical Bayesian methods,
• multivariate regression analysis,
• net benefit regression analysis.

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Standard Cost-EffectivenessAnalysis (one level)
Yia ßtiei

• Yi is cost for patient i
• ? is mean cost in control arm
• ? ?? is mean cost for treatment arm
• ti is treatment arm (0, 1)
• ?i random error term

Generalizability of economic evaluations Using
results from other geographic areas or from
multinational trials to help inform health care
decision making in Canada. Goeree R.
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Simple Hierarchical ModelMultilevel Modeling
(MLM)
Ya ßtvujtij eij
fixed effect random effects

• In addition to patients being seen as a random
  effect, country is also considered a random
  effect
• This model can be extended to include additional
  levels (e.g. centers) and other cluster-level
  (country) explanatory variables (covariates)

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MLM

• potential to facilitate estimates of
  cost-effectiveness which both reflect the
  variation in costs and outcomes between locations
  and also enable the consistency of
  cost-effectiveness estimates between locations to
  be assessed directly.

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Probabilistic analysis

• data inputs are incorporated as random variables,
  
• the appropriate means of handling parameter
  uncertainty.

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Sensitivity analysis or scenario analysis

• All key variables (economic and clinical) should
  be tested explicitly in sensitivity analysis
• allow decision makers to make a more informed
  judgment about how applicable data from other
  countries are to their jurisdiction.

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Transparency

• present the cost and outcomes in disaggregated
  detail before aggregation.
• physical quantities (e.g., length of stay in
  hospital) and unit costs should be reported
  separately rather than reporting total costs only.

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Reporting disccusion on

• the relevance of the data and model to the
  jurisdictions and populations of interest, and
  the generalizability of the overall results
• differences for the target audience in terms of
• disease epidemiology,
• population characteristics,
• effectiveness of the intervention,
• clinical practice patterns,
• resource use patterns,
• unit costs,
• and other relevant factors.

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ISPOR Task Force

• focus on best practices in transferability of
  economic data in health technology assessment
  (i.e. key variable economic data, guidelines for
  acceptance data from outside a country taking
  into consideration existing national guidelines).

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