14/11/2014 The Insurance Value of Medical Innovation Darius LakdawallaAnup MalaniJulian Reif USC and NBERUniversity of ChicagoUniversity of Illinois.

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Presentation transcript:

14/11/2014 The Insurance Value of Medical Innovation Darius LakdawallaAnup MalaniJulian Reif USC and NBERUniversity of ChicagoUniversity of Illinois

Consider a standard coin toss gamble 2 Risk matters when evaluating payoffs

Valuing medical technology: Gleevec for treatment of chronic myeloid leukemia 3 Technology may produce “self-insurance” value

Valuing medical technology: Highly Active Antiretroviral Therapy (HAART) for HIV 4 Technology may produce “market insurance” value

Risk-reduction value of technology raises several research questions 1.How can we define and measure the risk-reduction value of medical technology? 2.Under what conditions is it appropriate to abstract away from risk-reduction value? 3.How empirically significant is risk-reduction value over a range of real-world medical technologies? 4.What are the implications for how we value and pay for different types of medical technologies? 5

Value of medical technology can be intuitively illustrated in a simple two-good model 6

Intuition can be illustrated in a one-good model 7

Conventional “risk-free” value is the movement along the original expected utility chord 8 Traditional value

Additional “self-insurance” value accounts for the movement up the risk-averse utility curve 9 Self-insurance value

Additional “market insurance” value accounts for the incremental value of financially insuring the technology 10 Market-insurance value

Traditional valuations ignore the “insurance value” 11 Traditional value Insurance value Insurance value is the sum of self insurance and market insurance

Results from theoretical analysis Three separate components of value: – Traditional Value of Technology Corresponds to the “risk-free” value – Self-Insurance Value of Technology (SIVT) – Market-Insurance Value of Technology (MIVT) Accounting for only the traditional valuation causes researcher to underestimate the total value of technology This underestimate is particularly bad for severe diseases with low quality of life, i.e., high “unmet need” 12

Empirical framework is based on Cobb-Douglas utility 13

Parameterizing the utility function 14

“Cost-effectiveness” of technology drives variation in the risk-free and insurance values 15

Value of health technology is right-skewed 16 Traditional valueSelf-insurance valueMarket-insurance value Sigma (RRA)MedianMeanMedianMeanMedianMean 0.5 (0.85) $108$564 1 (1) $108$564 3 (1.6) $108$564 5 (2.2) $108$564 8 (3.1) $108$564 Notes: Sample is 1,188 interventions from CEAR. Estimates are weighted by the prevalence of disease.

Value of health technology is right-skewed 17 Traditional valueSelf-insurance valueMarket-insurance value Sigma (RRA)MedianMeanMedianMeanMedianMean 0.5 (0.85) $108$564($9)($114)($1.60)($5.01) 1 (1) $108$564$0.17$3$0.03$5 3 (1.6) $108$564$51 $839 $10 $70 5 (2.2) $108$564$120$1,928$27$184 8 (3.1) $108$564$243$3,193$55$403 Notes: Sample is 1,188 interventions from CEAR. Estimates are weighted by the prevalence of disease.

Insurance value dominated by self-insurance and comparable in magnitude to risk-free value 18 Traditional valueSelf-insurance valueMarket-insurance value Sigma (RRA)MedianMeanMedianMeanMedianMean 0.5 (0.85) $108$564($9)($114)($1.60)($5.01) 1 (1) $108$564$0.17$3$0.03$5 3 (1.6) $108 $564 $51 $839 $10 $70 5 (2.2) $108$564$120$1,928$27$184 8 (3.1) $108$564$243$3,193$55$403 Notes: Sample is 1,188 interventions from CEAR. Estimates are weighted by the prevalence of disease.

Providing special reimbursement for treating diseases with high unmet need remains controversial 19 “[The fund] not only undermines NICE, it undermines the entire concept of a rational and evidence-based approach to the allocation of finite health-care resources.” “New cancer treatments clearly challenge the cost thresholds set by NICE”

Self insurance value (SIV) is large for diseases with high unmet need 20

Treating diseases with unmet needs – e.g., cancer – is much more valuable than previously recognized 21 HIV/AIDS Gleevec Alzheimer’s

Policy implications of risk-reduction value Economic value of health increases may be larger than previously thought – Greater expenditures on health-related research may be worthwhile Health technology assessment – Risk-reduction value should be incorporated into value assessments – Treatments for diseases with high unmet need are especially undervalued, perhaps by an order of magnitude 22

Reexamining the role of medical innovation Policies to promote new health technology also function like insurance reform – Financial markets may have played a secondary role in reducing society’s exposure to health risk The distributional implications of health technologies have been poorly understood – The poor benefit disproportionately from health risk- reduction (McClellan and Skinner, 2006) – Access to medical technology is a policy substitute for financial redistribution or means-tested health insurance 23