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Current Approaches in European
             Drug related Health Care Policy
                 relative effectiveness and real life
                                             studies
                                     Bengt Jönsson
                     Stockholm School of Economics


Key note lecture ZonMw Congres Goed Gebruik Geneesmiddelen,
31 January 2013

                                                              Page 1
New evidence for decisions about
market access




                              Market
                               Page 3
Regulatory changes

• Drugs have been withdrawn from the
  market due to in-appropriate use
   – Based on risk benefit assessment
   – Data on side effects only one side of the
     assessment
• Post-authorisation efficacy studies (PAESs)
  a new tool for regulatory decisions
   – Conditional market authorization (CMA) or
     “adaptive licensing”
   – Data on “relative efficacy” also relevant for
     HTA


                                                     Page 4
Page 5
Regulatory decisions, uncertainty and
opportunity cost
• More stringent criteria for effectiveness and
  safety, i.e. net health benefit, may lead to delay
  of access to valuable drugs and increasing costs
  for drug development
• Relaxed criteria may lead to the introduction of
  drugs with a negative net health benefit
• Decisions must be made on incomplete data
   – A system for follow-up and re-assessment of ADRs is in
     place based on “real life data”
   – Increasingly recognized that net health benefit
     depends on how the drugs are used in clinical practice


                                                          Page 6
Health technology Assessment
(HTA)
• Shift in focus from established therapies to new
  technologies, particularly drugs
• Limited data for assessment of effectiveness
   – Uncertainty about clinical outcome
• Payers are increasingly using HTA, including
  relative effectiveness assessment (REA) and cost-
  effectiveness analysis (CEA) to inform decisions
• Economic aspects, including price, plays a larger
  role for reimbursement decisions
   – Specific market access agreements


                                                     Page 7
New drug introductions 1940-2009




                                   Page 8
Reduced productivity in R&D




                              Page 9
Mean cost of taking a NME to the
    market

• Di Masi 2003              USD 1 billion
• Paul et al 2010           USD 1.8 billion
• OHE 2011                  USD 1.5 billion
                    (all in 2011 prices)


• Increasing relative costs of new drugs
• New cancer drugs priced at USD 10 000 per
  month of treatment
• Equal to monthly salary for an oncologist in
  Sweden

                                                 Page 10
Increasing role for public payment for drugs

• Chronic therapy for RA and MS cost
  1000 Euro per month
• New cancer drugs priced at 10 000
  USD per month
• Reimbursement is key to market
  access
   – And for efficiency and equity
• HTA is developing as a major policy
  instrument to assess value for money
                                          Page 11
The major problem for HTA – Lack of data
• Regulatory decisions based on clinical trials aimed
  at investigating if a new drug works as intended
   – Balancing benefits and risks
• HTA aims at investigating how a new drug works in
  clinical practice compared to relevant
  alternatives
   – Population (indication)
   – Comparator
   – Outcome
• Clinical trials do not provide the necessary data
  for an assessment of relative effectiveness


                                                  Page 12
Re-engineering drug development to
meet payer demands
• Early HTA advice on development
  strategies
  – May help directing R&D towards development
    of drugs meeting payer objectives
• Joint regulatory and HTA advice
  – May help reducing costs and improving value
    of clinical trials
• But there are limits to produce evidence
  of relative and cost-effectiveness before
  the drug comes to the market
                                              Page 13
Payer decisions, uncertainty and
opportunity cost
• More stringent criteria for relative effectiveness
  and cost-effectiveness, i.e. value for money, may
  lead to delay of access to valuable drugs and
  increasing costs for drug development
• Relaxed criteria may lead to the introduction of
  drugs with a negative net health benefit
  compared to using the resources otherwise
• Decisions must be made on incomplete data
   – A system for follow-up and re-assessment based on “real
     life data” must be introduced
   – Value for money depends on how the drugs are used in
     clinical practice
                                                         Page 14
Methods for the Estimation of the NICE Cost
Effectiveness Threshold
Karl Claxton, Steve Martin, Marta Soares, Nigel Rice,Eldon Spackman, Sebastian
Hinde, Nancy Devlin, Peter C Smith, Mark Sculpher CHE January 2013

 • “The central or 'best' threshold is estimated to be
   £18,317 per QALY”
 • “It is crucial that the cost effectiveness threshold
   is seen as representing health forgone as the
   additional costs of new technologies are
   imposed on the fixed budgets of local
   commissioners” (MS)
 • “This study also starts to make the other NHS
   patients, who ultimately bear the opportunity
   cost, less abstract so they can be properly taken
   into account when decisions about new health
   technologies are being made.” (KC)
                                                                           Page 15
Patients and real life data
• Potential patients are interested in access to new
  medicines regard of their costs
• Variations in use of new technologies is seen as
  unfair and inefficient
   – NICE was introduced to solve the problem with “post-
     code” prescribing
• Patients are increasingly involved as a
  stakeholder in decisions about use of drugs
   – Regulatory decisions about safety
   – Development of clinical guidelines
   – Reimbursement decisions


                                                            Page 16
All decision makers and
stakeholders demand real life
data




                                Page 17
Sir richard
            doll

            Smoking causes
            cancer
           Bradford Hill criteria for
           causation
           Strength of association
           Consistency
           Specificity
           Temporal relationship
           Biological gradient
           Plausibility
           Coherence
           Experiment (reversibility)
           Analogy
13-02-08                                18
Collecting real life data

• Data never speaks for themselves
   – Data versus evidence
   – Evidence depends on the circumstances
• Augmenting clinical trial data
   – Inclusion of additional variables (PRO, resource
     utilization)
   – Parallel data collection outside the clinical trial in an
     identical population
• Registries
   – prospective, observational cohort studies of patients
     who have a particular disease and/or are receiving a
     particular treatment or intervention

                                                                 Page 19
Collecting real life data

• Choice of outcome measure
   –   Mortality
   –   Age adjusted mortality
   –   Survival
   –   Quality of life
   –   Other relevant outcome
• Work performance
   – Working versus not working
   – Reduced productivity at work
• Resource utilization
   – Inside and outside health care

                                      Page 20
Analysing real life data
• The problems with “causation” must
  always be considered
• The need for improvement in
  statistical methods for analysing
  registry data
• The need for modelling
• Opportunities for randomization in
  clinical practice should be
  investigated
                                   Page 21
real life data and policy

• Coverage by evidence development
  (CED)
  – Requirement to collect data part of the
    reimbursement decision
  – Data will be used for a revision of the
    reimbursement decision
• Pay for performance (P4P)
  – Reimbursement is linked to collection of data
    on outcome




                                                    Page 22
Issues related to CED and P4P

•   How common is this is different countries?
    – Are there provisions for this in legislation
•   For which types of drugs is it required?
    – Expensive drugs
    – Uncertainty about effects
    – Uncertainty about their use
•   Who is undertaken and paying for the studies?
    – What type of studies
•   How is the link between study result and decision?
    – Open-ended (CED)
    – Decided up-front (P4P)




                                                     Page 23
United Kingdom (NICE)

•   Experience: MS risk sharing scheme in 2002
    –   Price linked to outcome in clinical practice
    –   Initiated to solve a “political” problem
    –   Study complicated and inconclusive
    –   Not used for revision of decision
•   Today
    – No enthusiasm for CED
    – Preference for market access agreements which
      mainly consists of price discounts (Tarceva,Sutent)
    – Pay for responders only (Velcade, Erbitux)
•   Tomorrow
    – Depends on the design of the VBP scheme



                                                            Page 24
France

•   Experience
    – Long tradition of follow up studies
    – Mainly to control that indications are followed
    – No transparent link to decision making
•   Today
    – Studies to assess relative effectiveness and cost
      savings (Risperidol, Januvia)
    – Secret agreement with the company
•   Tomorrow
    – CEA will be mandatory at launch and at revision
      after five years
    – More CED studies but no commitment to specific
      decision


                                                          Page 25
Germany

•   Experience
    – Possible for hospital drugs but not used
•   Today
    – Federal Joint Commission and a pharmaceutical
      company can agree on performing a (real life) study
      to evaluate the effects of a new drug
    – The company has to pay for this
    – Only one example so far
•   Tomorrow
    – CED may be more used in the future to follow up
      results of price negotiations




                                                        Page 26
Sweden

•   Experience
    – CED is used in at least
      20 cases by TLV 2002-
      12                        Evidence on effectiveness
                                and cost-effectivness.

    – Over-representation       Evaluating if the use in
                                clinical praxis follows the
      of “life style drugs”     specified indication.
                                Combination

    – Follow up data on
      restricted indications
    – Follow-up data on
      cost-effectiveness
•   Tomorrow
    – To be used more at
      the county level


                                                  Page 27
CED, P4P and CER in the US – Growing importance for
Europe




                                                      Page 28
Why CED and P4P are going to be the new
standard in health care – Outcome matters




                                       Page 29
Conclusions
• Regulators and HTA/reimbursement
  agencies/payers have a common objective
   – Improvements in public health
• They have different roles and are guided by
  different legislation
   – But closer collaboration can overcome many of
     the present problems
• Real life data is a common interest
   – For assessment of risk-benefit
   – For assessment of cost-benefit
   – For assuring patients that resources are used in an
     efficient and equitable manner

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Current Approaches in European Drug related Health Care Policy: Relative Effectiveness and Real Life Studies

  • 1. Current Approaches in European Drug related Health Care Policy relative effectiveness and real life studies Bengt Jönsson Stockholm School of Economics Key note lecture ZonMw Congres Goed Gebruik Geneesmiddelen, 31 January 2013 Page 1
  • 2. New evidence for decisions about market access Market Page 3
  • 3. Regulatory changes • Drugs have been withdrawn from the market due to in-appropriate use – Based on risk benefit assessment – Data on side effects only one side of the assessment • Post-authorisation efficacy studies (PAESs) a new tool for regulatory decisions – Conditional market authorization (CMA) or “adaptive licensing” – Data on “relative efficacy” also relevant for HTA Page 4
  • 5. Regulatory decisions, uncertainty and opportunity cost • More stringent criteria for effectiveness and safety, i.e. net health benefit, may lead to delay of access to valuable drugs and increasing costs for drug development • Relaxed criteria may lead to the introduction of drugs with a negative net health benefit • Decisions must be made on incomplete data – A system for follow-up and re-assessment of ADRs is in place based on “real life data” – Increasingly recognized that net health benefit depends on how the drugs are used in clinical practice Page 6
  • 6. Health technology Assessment (HTA) • Shift in focus from established therapies to new technologies, particularly drugs • Limited data for assessment of effectiveness – Uncertainty about clinical outcome • Payers are increasingly using HTA, including relative effectiveness assessment (REA) and cost- effectiveness analysis (CEA) to inform decisions • Economic aspects, including price, plays a larger role for reimbursement decisions – Specific market access agreements Page 7
  • 7. New drug introductions 1940-2009 Page 8
  • 9. Mean cost of taking a NME to the market • Di Masi 2003 USD 1 billion • Paul et al 2010 USD 1.8 billion • OHE 2011 USD 1.5 billion (all in 2011 prices) • Increasing relative costs of new drugs • New cancer drugs priced at USD 10 000 per month of treatment • Equal to monthly salary for an oncologist in Sweden Page 10
  • 10. Increasing role for public payment for drugs • Chronic therapy for RA and MS cost 1000 Euro per month • New cancer drugs priced at 10 000 USD per month • Reimbursement is key to market access – And for efficiency and equity • HTA is developing as a major policy instrument to assess value for money Page 11
  • 11. The major problem for HTA – Lack of data • Regulatory decisions based on clinical trials aimed at investigating if a new drug works as intended – Balancing benefits and risks • HTA aims at investigating how a new drug works in clinical practice compared to relevant alternatives – Population (indication) – Comparator – Outcome • Clinical trials do not provide the necessary data for an assessment of relative effectiveness Page 12
  • 12. Re-engineering drug development to meet payer demands • Early HTA advice on development strategies – May help directing R&D towards development of drugs meeting payer objectives • Joint regulatory and HTA advice – May help reducing costs and improving value of clinical trials • But there are limits to produce evidence of relative and cost-effectiveness before the drug comes to the market Page 13
  • 13. Payer decisions, uncertainty and opportunity cost • More stringent criteria for relative effectiveness and cost-effectiveness, i.e. value for money, may lead to delay of access to valuable drugs and increasing costs for drug development • Relaxed criteria may lead to the introduction of drugs with a negative net health benefit compared to using the resources otherwise • Decisions must be made on incomplete data – A system for follow-up and re-assessment based on “real life data” must be introduced – Value for money depends on how the drugs are used in clinical practice Page 14
  • 14. Methods for the Estimation of the NICE Cost Effectiveness Threshold Karl Claxton, Steve Martin, Marta Soares, Nigel Rice,Eldon Spackman, Sebastian Hinde, Nancy Devlin, Peter C Smith, Mark Sculpher CHE January 2013 • “The central or 'best' threshold is estimated to be £18,317 per QALY” • “It is crucial that the cost effectiveness threshold is seen as representing health forgone as the additional costs of new technologies are imposed on the fixed budgets of local commissioners” (MS) • “This study also starts to make the other NHS patients, who ultimately bear the opportunity cost, less abstract so they can be properly taken into account when decisions about new health technologies are being made.” (KC) Page 15
  • 15. Patients and real life data • Potential patients are interested in access to new medicines regard of their costs • Variations in use of new technologies is seen as unfair and inefficient – NICE was introduced to solve the problem with “post- code” prescribing • Patients are increasingly involved as a stakeholder in decisions about use of drugs – Regulatory decisions about safety – Development of clinical guidelines – Reimbursement decisions Page 16
  • 16. All decision makers and stakeholders demand real life data Page 17
  • 17. Sir richard doll Smoking causes cancer Bradford Hill criteria for causation Strength of association Consistency Specificity Temporal relationship Biological gradient Plausibility Coherence Experiment (reversibility) Analogy 13-02-08 18
  • 18. Collecting real life data • Data never speaks for themselves – Data versus evidence – Evidence depends on the circumstances • Augmenting clinical trial data – Inclusion of additional variables (PRO, resource utilization) – Parallel data collection outside the clinical trial in an identical population • Registries – prospective, observational cohort studies of patients who have a particular disease and/or are receiving a particular treatment or intervention Page 19
  • 19. Collecting real life data • Choice of outcome measure – Mortality – Age adjusted mortality – Survival – Quality of life – Other relevant outcome • Work performance – Working versus not working – Reduced productivity at work • Resource utilization – Inside and outside health care Page 20
  • 20. Analysing real life data • The problems with “causation” must always be considered • The need for improvement in statistical methods for analysing registry data • The need for modelling • Opportunities for randomization in clinical practice should be investigated Page 21
  • 21. real life data and policy • Coverage by evidence development (CED) – Requirement to collect data part of the reimbursement decision – Data will be used for a revision of the reimbursement decision • Pay for performance (P4P) – Reimbursement is linked to collection of data on outcome Page 22
  • 22. Issues related to CED and P4P • How common is this is different countries? – Are there provisions for this in legislation • For which types of drugs is it required? – Expensive drugs – Uncertainty about effects – Uncertainty about their use • Who is undertaken and paying for the studies? – What type of studies • How is the link between study result and decision? – Open-ended (CED) – Decided up-front (P4P) Page 23
  • 23. United Kingdom (NICE) • Experience: MS risk sharing scheme in 2002 – Price linked to outcome in clinical practice – Initiated to solve a “political” problem – Study complicated and inconclusive – Not used for revision of decision • Today – No enthusiasm for CED – Preference for market access agreements which mainly consists of price discounts (Tarceva,Sutent) – Pay for responders only (Velcade, Erbitux) • Tomorrow – Depends on the design of the VBP scheme Page 24
  • 24. France • Experience – Long tradition of follow up studies – Mainly to control that indications are followed – No transparent link to decision making • Today – Studies to assess relative effectiveness and cost savings (Risperidol, Januvia) – Secret agreement with the company • Tomorrow – CEA will be mandatory at launch and at revision after five years – More CED studies but no commitment to specific decision Page 25
  • 25. Germany • Experience – Possible for hospital drugs but not used • Today – Federal Joint Commission and a pharmaceutical company can agree on performing a (real life) study to evaluate the effects of a new drug – The company has to pay for this – Only one example so far • Tomorrow – CED may be more used in the future to follow up results of price negotiations Page 26
  • 26. Sweden • Experience – CED is used in at least 20 cases by TLV 2002- 12 Evidence on effectiveness and cost-effectivness. – Over-representation Evaluating if the use in clinical praxis follows the of “life style drugs” specified indication. Combination – Follow up data on restricted indications – Follow-up data on cost-effectiveness • Tomorrow – To be used more at the county level Page 27
  • 27. CED, P4P and CER in the US – Growing importance for Europe Page 28
  • 28. Why CED and P4P are going to be the new standard in health care – Outcome matters Page 29
  • 29. Conclusions • Regulators and HTA/reimbursement agencies/payers have a common objective – Improvements in public health • They have different roles and are guided by different legislation – But closer collaboration can overcome many of the present problems • Real life data is a common interest – For assessment of risk-benefit – For assessment of cost-benefit – For assuring patients that resources are used in an efficient and equitable manner

Notas do Editor

  1. Thanks for your kind invitation to this important conference. I cannot read the details of the program, but enough to understand that you are looking for ways to make sure that medicines are used safely, effective and efficient; what we call rational pharmacotherapy. Development of new pharmaceuticals is one of the great success stories of innovation for improvement of health and welfare. The historical benefits are enormous. But today there is a crises, of a similar type which we experience in the 1960 when the regulatory criteria was tightened post thalidomide. In the same way as in the 1960 the solution is looked for in terms of improved methods for evaluation of new drugs and new data. The clinical trial which served well for half a decade is not sufficient to provide answers to the new questions about relative effectiveness and value for money. Today we are focus attention on real life data to provide the guidance for rational pharmacotherapy. How did we get there? What are the key issues? What are the policy responses? What is the likely future and how can we shape it? Name, Department
  2. The data for regulatory approval are well established in a continuous development since the 1960s. They are based on randomized clinical trials, designed in co-operation between regulators and the pharmaceutical industry. After market authorization, the data are used for information/marketing to practicing physicians. Limited involvement of other stakeholders such as payers and patients. Real life data has complemented trial data but only for detection of rare side effects. HTA was first developed to assess established non-drug technologies, such as diagnostics and surgery, which have been introduced without proper assessment and evidence of effectiveness. In addition, HTA took a broader view on medical technologies, including economic aspects. But HTA was also applied to drug technologies, such as treatment of hypertension and osteoporosis, mainly to assess the proper indications (over-and underuse).. Since the beginning of 1990s, economic evaluation, or cost-effectiveness analysis was introduced to inform decisions about reimbursement of pharmaceuticals, first in Canada and Australia. In Europe, Holland was one of the first countries to use this instrument. Lately the concept “relative effectiveness” has been introduced as a response to the need for a more coordinated approach to reimbursement in Europe. We can thus see that regulatory approval over time has been complemented with other policy instruments to manage the introduction and use of new drugs. Name, Department
  3. We can see that regulatory authorities have responded in various ways to the challenges involved in making decisions about market authorization. One response is the gradually increasing demands for data for assessment of risk-benefit for drugs in the market. We can also observe that this has resulted in re-calls of market authorization. But the learning is that risk-benefit does not only depend on side effects, it depends also on the benefit, and both are determined by the use of the drug. If used in patients with low risk and/or high benefit the ratio may be acceptable. However, this calculus also requires more transparency in how risks and benefits are assessed and compared. Recently we have seen a call for post-authorisation efficacy studies, which is very much the same as relative effectiveness. Unless evidence is restricted to experimental studies in clinical practice. This is hardly possible, since opportunities for experimental design and randomization is limited in clinical practice. Reletad to this is also a discussion about “adaptive licensing”, which mirrors the use of “coverage by evidence development” for reimbursment decisions. We can note the also regulatory decision making isincreasingly requesting real life data. Name, Department
  4. Name, Department
  5. Partly the demand for more data post-authorisation comes from an understanding that it is not possible to asks for more evidence pre MA. That will delay introduction of new drugs and make development more expensive. It is more efficient to find an optimal trade off between what is required as evidence before and after MA. Some technological advances, such as development of target therapies, with a deeper understanding of the disease, its mechanisms and which patients that benefit from treatment facilitate shorter and smaller trials, in combination with follow-up data to optimize the use of the therapy in clinical practice. Name, Department
  6. After being used to weed out ineffective established therapies, HTA has increasingly been applied where it is most needed, for assessment of new and expensive therapies. Unfortunately this is also where the the method is weakest, since there are no studies available which can be subject of “systematic reviews”, a major tool in HTA. But due to the need for payers to make early decisions, and lack of better alternatives, it has been extensively used to inform reimbursement decisions and therapeutic guidelines, also in situations with limited data. Due to the uncertainties involved, specific agreements about re-assessment and other conditions for reimbursement are common. Name, Department
  7. With some variations, the number of new drug introductions per year have not change very much over more than a half century. Name, Department
  8. But the annual expenditures for R&D in the pharmaceutical industry has continued to increase, resulting in a reduced number of introductions per biliion USD invested. What is depicted in the above graph from BCG as a decline in R&D productivity. Name, Department
  9. Other methods for calculating the cost for bringing a NME to the market confirms the increasing costs over time. This is an explanation for the increasing relative costs of new drugs, and the high prices for drugs used in diseases with low incidence and prevalence. On the other hand, when the drug loses patent, the prices are substantially reduced. But this does not help the relative disadvantage of costs during the patent period when investments should be re-covered.. Name, Department
  10. High prices also means that it is difficult to leave to the patients to make the priorities for use. Without public payment (reimbursement) there is no real access for patients to the new drugs. It also put a lot of pressure on reimbursement agencies to make decisions that are efficient and fair for patients. Name, Department
  11. Clinical trials during the development of a drug focus on evidence that it works as intended. It thus often studied in patients, with comparators and outcome measures that do not necessarily answer questions which HTA agencies and payers are asking: What are the benefits in different subpopulations? What are the extra benefits compared to available used or best alternatives? What is the value for the patient assessed with relevant outcomes? Name, Department
  12. A lot can be done in the development process to make the studies and data collected relevant for HTA and payers. Assessing this need in advance may increase the value of the trials without adding to costs. It is also important to identify development strategies that have a small chance to lead to the desired goals, and redirect efforts to development of potentially more valuable medicines. But there are limits to what is possible and meaningful to do pre market authorization. Particularly taking into account that products may fail. Thus joint advice from regulators and HTA experts is particularly valuable to get at best possible information for a global assessment of the opportunities for a specific potential asset. Name, Department
  13. It may seem trivial that main consequence of wrong reimbursement decisions is a loss of money if potential side effects can be ignored. But with limited health care resoruces there are opportunity costs. Spending money on less valuable products and services means that those money cannot be spent on valuable products and services. Name, Department
  14. As is seen from this recent study from researcher linked to NICE in England, there is a growing demand for finding measures, not only of the outcome of new therapies, but also of those which they replace. The method and estimates presented in the report are debatable, a comparison should always be made to the least important services and products. Calculations of averages is perhaps the most relevant, but the more rational and efficient the health service becomes, the more important will it be to find estimates also of opportunity costs in terms of losses of health. Name, Department
  15. Patients have played a minor role in regulatory decisions. It is assumed that the doctors take patients interests into account in their use of new medicines. HTA and formal reimbursement decisions have made decisions more transparent and given patients as a group a seat at the table when assessment are undertaken and decisions made. Since all citizens are potential patients, everybody using and paying for health services is a stakeholder when it comes to real life data. Name, Department
  16. Everybody wants it, but how should we do it? Name, Department
  17. Sir Richard Doll, one of the most famous epidemiologists can illustrate both the power of real life data and the potential controversies. As his colleague Bradford Hill early noted, it is no straightforward conclusion about what causes disease or what contribute to its cure. The experimental clinical trial has an advantage in terms of internal validity. But we are also interested in external validity. Trials and real life data are thus complements. Name, Department
  18. Data never talk for themselves. They have to be “massaged” to provide information, and to rise to the level of evidence. Data are also, like the human body, better if they are exercised (used). One important point for establishing validity is to make a connection between trial data and observational data. Including similar variables in both trials and observational studies in similar population is one way. Registries in an important source for real life data. Actually, Doll used a “natural registry of NHS doctors for his follow up studies on the impact of smoking on lung cancer. Name, Department
  19. There is no “cock-book” solutions to questions which real world data should be collected. It depends on the circumstances. The choice of outcome measure can illustrate this. Different outcome measures give different answers. From an economic perspective, outcome measures that can be combined to a relevant composite measure, for example quality-adjusted life years (QALY) are to be preferred. Work performance is is also an important economic outcome, which may be ignored if not supported by data. Resource utilization can to a large extent be retrieved from existing administrative and clinical record, but needs to be complemented with resource utilization outside health care for both formal and informal care. Name, Department
  20. The value of real world studies depend on what other supporting information is available to help assessing their validity. See the Bradford Hill criteria as an example. Still most reports from registers and other “real world data collections” are simple descriptions. There are statistical techniques developed which makes it possible to get much more information out of these data bases. One example being instrumental variables techniques frequently used in economics. See for example Heckman, J. (1997) Instrumental variables: A study of implicit behavioral assumptions used in making program evaluations, Journal of Human Resources, 32(3), 441–462. James Heckman is professor of Economics at the University of Chicago and 2000 Nobel Laureate in Economics. Name, Department
  21. A reimbursement decision has to be made based on the information available when the drug first come to market. There are two ways of managing the uncertainty of outcome and costs where real life data are used. The first is CED where real life data are used for a reassessment of the reimbursement decision at a later point in time. The second is P4P where the actual reimbursement is linked to real life data about outcome. Both methods have been proposed and used for a rather long time, both in the US and Europe, and not only for pharmaceuticals. Contracting between purchasers and providers of health care usually includes some conditions where payment is related to outcome. For hospitals, the DRG payment can be complemented with outcome indicators related to quality. Also payment for physicians may include payments related to outcome. However, the use of these methods are still under development, and for example in US, CED has mainly been an extra payment if the provider collected data on the use of the technology. Name, Department
  22. There are many issues related to CED and P4P and there is no time to go deeper into approaches and experiences. I will briefly look at the situation in a selected number of countries which may be of interest as a background for developments in the Netherlands, which I for obvious will not review. My impression is that you have lessons to tell rather than learn from other countries. Name, Department
  23. The MS risk sharing scheme was set up due to the uncertainty about the cost-effectiveness of the new MS drugs, and to make sure that patients got access to the new treatments in an equal fashion. The data collection was organized through a project with multiple stakeholders, and paid for by DH and companies selling the products. It will take to long to review this project in detail, but the conclusion must be that it is seen as a failure, at least in the sense that it did not provide any information that could be used for an informed decision about these drugs in a reasonable time. One of the most important reasons for this was the lack of a relevant control group for comparision to those patients treated with the new drugs. Today the main approach in UK seems to be to achieve market access agreements which include price reductions. In some cases these price reductions have the form of P4P, since payment is linked to measures of response by patients to the treatment (pay for responders only). Velcade (bortozemid) in MM: Refund if no response after four cycles (60 days). Erbitux refund if there is progression in mCRC (scan after 5 weeks). Name, Department
  24. France have a long tradition of follow up studies, but it is difficult to evaluate their impact since they are based on secret agreements between HAS and the manufacturer. Name, Department
  25. Name, Department
  26. CED has been used both to floow-up the restricted indications are followed, and to evaluate outcome and cst-effectiveness. Two examples: Risperdal Consta and Lantus. Consta illustrate the problem to measure the value of improved compliance. Lantusthe individual trade off between risk of hypoglycemic event and reduction in HbA1c. Name, Department
  27. The investments in comparative effectiveness research in the US are important for Europe. Not least for the experiences in development of principles and methodologies for such studies. Name, Department
  28. Over a longer time, we will see a trend towards payment related to outcome. The will make real world data key to management of health care systems. Name, Department
  29. Name, Department