Improving Methods and Processes for Assessing Codependent Technologies

  • 1,873 views
Uploaded on

Technologies that enhance the precision and effect of therapies can make a critical contribution to ensuring value for money and improving patient care. Methods and processes for assessing value, …

Technologies that enhance the precision and effect of therapies can make a critical contribution to ensuring value for money and improving patient care. Methods and processes for assessing value, however, still are imperfect. This presentation reviews the challenges and identifies some approaches for meeting them.

  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Be the first to comment
    Be the first to like this
No Downloads

Views

Total Views
1,873
On Slideshare
0
From Embeds
0
Number of Embeds
6

Actions

Shares
Downloads
0
Comments
0
Likes
0

Embeds 0

No embeds

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
    No notes for slide
  • key pathways of value that the use of Dx to inform treatment or intervention decisions
  • Dx can be available to select patients that are more or less likely to develop adverse effects  a. allow a treatment to receive marketing authorisation by improving the benefit-risk ratio associated with the treatment b. increase adoption of the treatment, in cases where a treatment is licensed, but is not widely used because of its perceived unfavourable average benefit-risk balance when considered across a broad patient population
  • Avoid trial and error approach and identify the most suitable intervention First two points captured in CE analysis; last one notI will illustrate those points using the exampleit avoids or reduces inconvenience to patients who do not need to experience a long diagnostic process or try different therapies to identify the one most suitable
  • Patients are more motivated if they know the intervention is likely to work. In the case of companion diagnostics, however, patients found to be non-responders might experience disutility as they can feel ‘left-behind’, and lose hope and even motivation to pursue any other, less effective, but appropriate therapy.
  • Dx to stratify patientsThree cases where Dx have a positive impact and it is introduced in the market at different stages of the Tx lifecyclepatient stratification in oncology clinical trials could reduce attrition rates in overall clinical development and, in particular, attrition rates from Phase II to Phase III
  • Measured by EQ5D but may not be captured as patients focus on Tx effects rather than on the overall experience of Dx-Tx
  • Those were the five pathways through which co-dependent technologies such as Dx and Tx can generate value as compared to a situation where the intervention is used on its own
  • Only third poikey issue for the assessment of co-dependent technologies is that they are perceived as a joint product so there is no an approach to allocate the value brought by each part.) I then discussed a framework identifying how Dx can bring additional value to Dx-Tx pairs. Here I discuss briefly which the type of process can help ensuring those elements are assessed and considered in the HTA or P&R system. nt
  • Guide for submission sets a high standard of evidence to demonstrate impact of the test on patient outcomesWhich raises important questions as to how value should be demonstrated and who can generate the evidence

Transcript

  • 1. Assessing the Value of Co-dependent Technologies:How Can Current Methods and Processes Be Improved?ScHARR Seminar, University of Sheffield16 April 2013 ● Sheffield, UKMartina Garau, Office of Health Economics
  • 2. Adrian Towse (OHE) and the other authors of:Garau, M., Towse, A., Garrison, L., Housman, L. and Ossa, D.(2012) Can and should value based pricing be applied tomolecular diagnostics? Personalized Medicine. 10(1), 61-72.Acknowledgements
  • 3. • What is the value of co-dependent technologies?• Framework for assessing value• How prove value?• How aggregate value dimensions?• Proposed institutional processes• International experience• Australia• NICE• ConclusionsAgenda
  • 4. • “Technologies that are dependent on another technologyeither to achieve their intended effect or to enhance theirintended effect” (www.health.gov.au)• In particular, a diagnostic test (Dx) can be used to identifypatients most likely to:• Respond or fail to respond to a drug treatment (Tx)• Exhibit adverse eventsBut also to:• Monitor responses to drugs• Determine the risk of developing a diseaseDefinition of co-dependent technologies
  • 5. 1. Key elements of value are:• Health effects for patients (clinical effectiveness measured by theQALY)• Cost offsets (savings to the health care system)What is the value of co-dependent technologies? (1)Traditionally, ICERs do not capture benefits beyond health attributesNHS,PSS Cost of Treatment A - NHS,PSS Cost of Treatment BICER =Health effects of Treatment A - Health effects of Treatment BThe focus is on downstream effects of treatments not recognising the additionalvalue brought by use of Dx
  • 6. • Other value dimensions• Societal preferences giving priority to certain patients ordiseases• Quality of life aspects not reflected in generic measuresused in CE analyses• Other effects beyond those to patients and NHS(productivity gains)• Health care process related aspects (dignity, time andlocation of treatment)• Information for the patient independent of healtheffectsWhat is the value of co-dependent technologies? (2)
  • 7. • The value created is a “joint product” and there are no rulesfor the attribution of the value to one or the other• Garrison and Austin (2007) pointed out that how value isallocated across patients, payers, Dx manufactures and Txmanufacturers depends on the institutional context• E.g. whether the Tx was priced before the Dx was available; therelative strength of intellectual property protection for Dx and Tx• This will have consequences in terms of incentives forevidence generation and subsequent innovationThe issue of attribution of value ofco-dependent technologies
  • 8. Value1. Reducingdrug adverseeffects2. Reducingtime delays inselectingoptimal Tx3.Increasingadherence orwillingness tostart Tx4. Enabling Txeffective in asmall fractionto be madeavailable5.Reducinguncertaintyabout valueFramework for assessing value ofco-dependent technologiesValue dimensionsderived from:• Characteristics ofDx recentlyintroduced• Literature reviewon the economicsof personalisedmedicine andvalue ofinformation of Dx
  • 9. Availability of Dx can improve average benefit-risk ratioso, depending on the severity of side effects:• Tx obtains marketing authorisation, or• Use of a licensed Tx in clinical practice increasesExample: HLA-B*5701• Allele associated with hypersensitivity to abacavir for HIV-1• Identification of the marker has increased prescribing of abacavir, whichnow is recommended for HLA-B*5701-negative patients in European andUS guidelines1. Reducing or avoiding drug adverse effects
  • 10. Identifying non-responders and switching them to an alternativetreatment regime/care can:• Improve survival and/or quality of life (particularly in diseases at advancedstages)• Avoid or reduce the cost of treating non-responders• Avoid or reduce inconvenience to patientsExample: BCR-ABL• Test identifies chronic myelogenous leukemia (CML) patients who arereceiving treatment, but not responding to it• Can prevent the disease from progressing to blast crisis and death, andenables stopping first-line treatment when no longer effective2. Reducing time delays in selecting optimal Tx
  • 11. • Patients are more motivated if they know (ex-ante) theintervention is likely to work• Issue of non-responders who might experience disutility (theycan feel “left-behind”)Example: PreDx Diabetes Risk test• Test estimates the patient’s risk for developing Type 2 diabetesover the next five years• This can further encourage patients to follow a healthy lifestyleand take other preventive measures.3. Increasing adherence or willingness to under-take Tx or other interventions
  • 12. A biomarker or other genetic characteristic allowing forpatient stratification can:1. “Rescue” Tx that otherwise may either not have been licensed orhave been withdrawn2. Increase the chance of a Tx meeting reimbursement criteria (iftargeting responders improves cost -effectiveness)3. Accelerate R&D process for Tx (if stratification ascertained at anearly development stage)4. Enabling Tx effective in a small fraction to bemade available
  • 13. • Gefitinib for non-small-cell lung cancer (NSCLC) initially licensed, butwithdrawn when Phase III failed to show a survival benefit. With theidentification of EGFR mutations and its association with response rate toTKIs, gefitinib was approved in the EU and other markets in combination withthe EGFR mutation test.• NICE recommended trastuzumab for advanced and early-stage breast cancerin HER2/neu positive patients identified with HER2/neu test. The Dx-Tx costper QALY was found to be below the standard threshold.• Crizotinib targets a small subset of NSCLC patients with an ALK-positivemolecular abnormality. The development of the ALK FISH test hasaccelerated the development process and increased the likelihood ofcrizotinib delivering health benefits and commercial value.4. Enabling Tx effective in a small fraction to bemade available – Examples
  • 14. • Uncertainty around expected health effects and costs; influences the risk of poorvalue for money for payers• Value of information to patients about their medical condition independent of thehealth outcome (Ash, et al, 1990)• “Empowerment” (Payne, et al, 2012)• Effect of reassurance (measured with EQ-5D?) (Kenen, 1996)• Lifestyle choices and planning (Lee, et al, 2010)• Example of Oncotype DX ® and MammaPrint ®• Multi-gene assays estimating the risk of recurrence in breast cancer patientsfollowing surgery• Can guide intervention decisions and reduce the risk of dispensing unnecessarychemotherapy (reduce resource costs to the healthcare system and adverse effectfor the patient)5. Reducing uncertainty about value
  • 15. • Low accuracy of Dx will decrease potential net gains topatients and healthcare system• False positive and false negative patients will not get most appropriatetherapy• Tx can be more cost effective when used on its own• When Dx does not provide binary response, depending on the size ofthe subset for which the Dx does not provide clear-cut result and theDx cost relative to Tx• When Dx has low accuracyOther factors affecting value ofco-dependent technologies
  • 16. • Barriers to evidence generation• Cost and feasibility of certain study designs• Protection of intellectual property rights of Dx• Regulatory processes for diagnostics• Assessment of competitive tests with similar clinical useHow prove value of co-dependent technologies?
  • 17. How is value aggregated? Key issues Key meritsNet benefit As the sum of the benefits,each assessed in monetarytermsChallenges estimating the value inmonetary terms of each type of valueAllocating a monetary value to health hasbeen always one of the mayor criticismsArguably, a better grounding in economic theoryFacilitates the comparison of value and value for money across healthand other sectorsUse of monetary value may resonate better with some (private)payersMCDA As the sum of the pointsassigned to each aspect ofvalueThe cost -effectiveness threshold wouldneed to be re-assessed in terms of thecost per incremental “point”A pragmatic approach, widely used in the UK public sector.A more transparent (compared to a weighted QALY, or deliberativeprocess alone) means of addressing multiple criteriaMCDA is used in local NHS commissioning – potential to develop aconsistent priority-setting framework for both new and existinghealth care technologiesWeightedadjustedQALYs1. By QALYs gained, up-ratedor down-rated by one ormultiple weights to representthe magnitudes of otheraspects of value; or2. Direct estimation of howpeople trade off QALY gainswith other value elementsAssumes that all other sources of valueare proportional to the number of QALYsgained.Implications for the threshold. If the valueof new technologies is assessed in termsof a range of criteria, then opportunitycost also must be considered in the sameterms, not just QALYs foregone. Even if asimple social weighting or QALYs isapplied, opportunity cost will changeIs it relevant to state here the classic arguments in favour of the QALYsuch as:- Allows for comparisons across therapeutic areas in the NHS- “A QALY is a QALY” argument- Well established in the UK within HTA bodies (and academiccentres)- Understood by health economics communityDeliberativeprocessWeights are assigned by acommittee to each relevantaspect of valueThe weights are often implicitAre implications for the thresholdProvides an element of flexibilityIs a well-recognised approach taken by HTA bodies around the world.How aggregate value dimensions?Source: adapted from Sussex, et al, 2013
  • 18. • A joint Dx-Tx review of “at launch” technologies; to be done by a drugcommittee to exploit synergies across Dx and Tx• However, there is a need to address the lack of expertise of most drugcommittees in the Dx area• A separate Dx committee to develop Dx-specific expertise and to assessmultiple tests with similar clinical use• However, there may be a trade-off if there are not enough decisions to justifya distinct committee• A comprehensive and consistent approach to assessing value of both Dxand TxProposed institutional processes forco-dependent technologies
  • 19. Proposed institutional processesNew DxDx linked to a Tx(companion Dx)Dx-Tx pairlaunchedsimultaneouslyDx-Tx jointassessment viaDrug processSingle DxlaunchedseparatelyDx assessed viaDiagnostic-dedicated processMultiple Dx withsame clinical useDx assessed viaDiagnostic-dedicated processDx not linked to aTxDx assessed viaDiagnostic-dedicated process
  • 20. • Until recently, Dx and associated Tx assessed via differentcommittees (MSAC and PBAC)• No clear structure for consideration of the interactions and benefitsfrom joint use• New coordinated process and decision framework for “co-dependent technologies”• “Integrated” applications combining information from Dx and Txmanufacturers• Reimbursement decisions are made jointly by PBAC and MSAC toensure optimal clinical use (Merlin, et al, 2012)• The preferred type of evidence to show clinical benefit is a randomisedclinical trialInternational experience: Australia
  • 21. • NICE has dedicated-process for stand-alone Dx that followsvery closely that used for drugs• Strong preference for measuring health gains with the QALY• Value dimensions beyond health effects, such as value of informationto patients and process-related benefits, are not explicitly factored in• “At launch” combinations are appraised via the drug reviewprogramme (TAs)• No explicit consideration of test-related parameters (accuracy, costs)• Value dimensions beyond health effects are not explicitly factored inInternational experience: NICE in Englandand Wales
  • 22. • The use of Dx-Tx combinations can deliver health gains and cost savings within thehealth care system, but also generate broader benefits to patients and society• To ensure efficient use of limited resources, health decision makers should takeaccount of the full value generated by health technologies• Clear incentives are needed to encourage evidence collection• HTA and other decision making systems need coordinated and consistent approachto assessing value of Dx and Tx• NICE is heading in this direction, but does not yet have a comprehensive approachto assessing the value of Dx or Tx• In Australia, the common methodology needs to be supported by a realistic view ofevidence developmentConclusions
  • 23. Ash, D.A., Patton, J.P. and Hershey, J.C. (1990) Knowing for the sake of knowing: The value of prognostic information. MedicalDecision Making. 10(1), 47-57.Garau, M., Towse, A., Garrison, L., Housman, L. and Ossa, D. (2012) Can and should value based pricing be applied to moleculardiagnostics? Personalized Medicine. 10(1), 61-72.Garrison, L.P. and Austin, M.J.F. (2007) The economics of personalized medicine: A model of incentives for value creation andcapture. Drug Information Journal. 41(1), 501-509.Lee, D.W., Neumann, P.J. and Rizzo, J.A. (2010) Understanding the medical and nonmedical value of diagnostics testing. Value inHealth. 13(2), 310-314.Merlin, T., Farah, C., Schubert, C., Mitchell, A., Hiller, J.E. and Ryan, P. (2012) Assessing personalized medicines in Australia: Anational framework for reviewing codependent technologies. Medical Decision Making. 33(3), 333-342.Kenen, R.H. (1996) The at-risk health status and technology: A diagnostic invitation and the gift of knowing. Social Science &Medicine. 42(11), 1545-1553.Payne, K., McAllister, M. and Davies L. (2012) Valuing the economic benefits of complex interventions: When maximising health isnot sufficient. Health Economics. 22(3), 258-271.Sussex, J., Towse, A. and Devlin, N. (2013) Operationalising value based pricing of medicines: A taxonomy of approaches.Pharmacoeconomics. 13(1), 1-10.References
  • 24. To enquire about additional information and analyses, please contactMartina Garau: mgarau@ohe.orgTo keep up with the latest news and research, subscribe to our blog, OHE News.Follow us on Twitter @OHENews, LinkedIn and SlideShare.Office of Health Economics (OHE)Southside, 7th Floor105 Victoria StreetLondon SW1E 6QTUnited Kingdom+44 20 7747 8850www.ohe.orgOHE’s publications may be downloaded free of charge for registered users of its website.©2013 OHE