The impact of new drug launches on longevity: evidence from longitudinal, diseaselevel data from 52

1
The impact of new drug launches on
longevityevidence from longitudinal,
disease-level data from 52 countries, 1982-2001

• Frank R. Lichtenberg
• Columbia University and
•  National Bureau of Economic Research

2
United Nations Human Development Index

• (unweighted) average of three indexes
• an index of per capita GDP
• a life expectancy index
• an education index

3
U.S. economic growth, 20th C.
Nordhaus to a first approximation, the
economic value of increases in longevity over the
twentieth century is about as large as the value
of measured growth in non-health goods and
services
4
Life expectancy at birth, world, 1950-2000
5
Life expectancy at birth, by region
Unlike GDP, longevity is converging
6
Sources of longevity increase?

• improved quality of, and access to, medical
  care
• other factors

7
Conventional wisdom

• the empirical evidence indicates that the
  overall contribution of medical care to health is
  rather modest at the margin education,
  lifestyle, the environment, and income are the
  major contributing factors (Santerre and Neun
  (2000, p. 69)).
• increase in life expectancy has been much more
  influenced by economic development than
  improvements in medical care the most important
  medical advances are being brought about by
  improvements in information technology, not pills
  and scalpels (Getzen (1997, p. 330)).

8
Conventional wisdom

• Research on the relationship between health
  status and medical care frequently has found that
  the marginal contribution of medical care to
  health status is rather small any significant
  improvements in health status are more likely to
  originate from factors other than medical
  careFactors that determine the level of health
  include income and education, environmental and
  life-style factors, and genetics (Henderson
  (1999, p.142)).
• The historical declines in population mortality
  rates were not due to medical interventions
  because effective medical interventions became
  available to populations largely after the
  mortality had declined. Instead, public health,
  improved environment, and improved nutrition
  probably played substantial roles (Folland,
  Goodman, and Stano (2001, p. 118)).

9
Paul Romers Model of Endogenous Technical
Progress

• Y (A L) 1-? K ?
• Y output
• A the stock of ideas
• L labor used to produce output
• K capital
• 0 lt ? lt 1
• The cumulative number of drugs launched (N_DRUG)
  is analogous to the stock of ideas.

10
Health production function

• AGE_DEATHijt b ln(N_DRUGij,t-k)
• g Xijt eijt
• AGE_DEATHijt a statistic based on the age
  distribution of deaths from disease i in country
  j in year t
• N_DRUGij,t-k the number of drugs launched to
  treat disease i in country j by year t-k
• Xijt a vector of other factors (e.g. education,
  income, nutrition, the environment, and
  lifestyle) affecting the age distribution of
  deaths from disease i in country j in year t

11
Specification

• diminishing returns to additions to the stock of
  drugs
• specify a k-year lag in the relationship to
  allow for gradual diffusion of new drugs to
  consumers we will estimate the model using
  different assumed values of k (k 0, 1, 2,).

12
Controlling for other factors

• Hypothesize that many of the other factors
  affecting the age distribution of deaths from
  disease i in country j in year t (e.g. per capita
  income, public health expenditure, and
  environmental quality) are
• invariant across diseases within a country and
  year
• invariant across countries within a disease and
  year, or
• invariant across years within a country and
  disease

13
Controlling for other factors

• decompose Xijt as follows
•  
• Xijt ait djt ?ij ?ijt (2)
•  
• where
• ait a fixed effect for disease i in year t
• djt a fixed effect for country j in year t
• ?ij a fixed effect for disease i in country j

14
Reduced form

• AGE_DEATHijt b ln(N_DRUGij,t-k)
• ait djt ?ij uijt
• Zero-lag equation (k 0), is estimated using
  4678 observations, included 496 countryyear
  effects, 189 diseaseyear effects, and 502
  countrydisease effects. The equations are
  estimated via weighted least squares, using the
  number of deaths in that disease-country-year
  cell as the weight.

15
IMS Health Drug Launches database

• Has tracked new product introductions worldwide
  since 1982
• In August 2001 the database contained over
  165,000 records of individual product
  introductions between 1982 and 2001
• Allows measurement, for each country and
  therapeutic area, of the total number of
  ingredients launched, and the number of new
  chemical entities launched

16
Example tenecteplase

• Launch date Country
• 6/00 USA
• 3/01 Finland
• 5/01 UK
• 9/01 Norway
• 10/01 Canada
• 10/01 South Africa
• 11/01 Ireland

17
Drug launch probability profiles U.S. vs. Canada
18
Censoring of drug launches

• IMS Health Drug Launches database has tracked new
  product introductions worldwide since 1982
• NCE launches are guaranteed to be initial
  launches, but non-NCE launches may be either
  initial launches or re-launches we suspect they
  are predominantly the latter.

19
Censoring of drug launches

• AGE_DEATHijt bNCE ln(CUM_NCEij,t-k)
• bNON ln(CUM_non-NCEij,t-k)
• ait djt ?ij uijt
• CUM_NCE the cumulative number of NCEs launched
• CUM_non-NCE the cumulative number of non-NCEs
  launched
• Hypothesize that bNCE gt bNON
• bNON could be negative?

20
WHO Mortality database

• Provides data on the age distribution of deaths,
  by disease, country, and year
• Use aggregate life tables to translate our
  estimates of the impact of new drug launches on
  survival probabilities into estimates of the
  impact of new drug launches on life expectancy

21
Relationship between life expectancy and
probability of survival to age 65, U.S., 1900-2000
22
Linkage of drug launches to diseases

• Drug launches documented in the IMS Health Drug
  Launches database are classified by therapeutic
  category
• Deaths documented in the WHO Mortality Database
  are classified by cause (disease), using the
  International Classification of Diseases
• The high-level IMS drug classification
  corresponds quite closely to the high-level ICD
  disease classification, e.g. cardiovascular
  system drugs obviously correspond to (are used to
  treat) diseases of the circulatory system

23
11 broad disease categories
24
Countries with most and fewest drug launches
25
Findings

• Launches of New Chemical Entities (NCEs) have a
  strong positive impact on the probability of
  survival
• It takes at least three years for new NCE
  launches to have their maximum impact on survival
  rates
• This is probably due to the gradual diffusion of
  drugs to consumers following launch data on
  pharmaceutical expenditure are consistent with
  this interpretation
• Launches of (older) drugs that are not NCEsmany
  of which may already have been on the marketdo
  not increase longevity

26
Estimates of bNCE for different lags between
stock of NCEs launched and longevity
27
Estimates of bNCE and bexpend at different lag
values
28
Contribution of NCE launches to longevity
increase

• NCE launches appear to account for a significant
  fraction of the long-run increase in longevity in
  the sample as a whole
• Between 1986 and 2000, average life expectancy of
  the entire population of sample countries
  increased by almost two (1.96) years.
• The estimates imply that NCE launches accounted
  for 0.79 years (40) of the 1986-2000 increase in
  longevity.
• The average annual increase in life expectancy of
  the entire population resulting from NCE launches
  is .056 years, or 2.93 weeks.

29
Contribution of NCE launches to increase in
average life expectancy of the population since
1986
30
Cost per life-year gained from the launch of NCEs

• In 1997, average per capita pharmaceutical
  expenditure in OECD countries was about 250
• The average annual increase in life expectancy
  of the entire population resulting from NCE
  launches is .056 years
• Hence pharmaceutical expenditure per person per
  year divided by the increase in life-years per
  person per year attributable to NCE launches is
  about 4500
• This is far lower than most estimates of the
  value of a life-year
• Moreover, since the numerator includes
  expenditure on old drugs as well as on
  recently-launched NCEs, it probably grossly
  overstates the cost per life-year gained from the
  launch of NCEs

31
Micro evidence from a Medicaid program
32

• Vintage of drugs
• used Jan-June 2000
• approved after 1970
• approved after 1980
• approved after 1990

Probability of death by end of 2002

• Other characteristics
• age
• sex
• region
• utilization Jan-June 2000
• no. of MD visits
• no. of Rxs
• no. of hospital admissions
• nature of persons illnesses

540,000 people 12.2 million claims
33
Data

• All medical and pharmacy claims of Medicaid
  beneficiaries during the period January 1-June
  30, 2000
• Almost 800,000 people 540,000 had pharmacy
  claims
• About 12.2 million claims
• List of all residents who died during the period
  2000-2002.

34
Mortality rate declines as drug vintage increases
35
Actual vs. hypothetical mortality rates
36
Analysis by disease group
37
The Economics of Invention Incentives Patents,
Prizes, and Research Contracts

• Brian D. Wright
• American Economic Review 73,
• 1983, pp. 691-707.

38
How should the government support biomedical
research?

• Alternative mechanisms
• Government labs
• Research grants and contracts
• Regulation (e.g. Orphan Drug Act)
• Antitrust law (Joint ventures)
• Patent law
• Prizes purchase commitments

39
Simple model of research

• Large number of firms, each of which can
  undertake one research project
• Each research firm can conduct one research study
  at a cost of c 1
• The more firms actively searching for a
  particular invention, the higher the probability
  that at least one of them will discover it. The
  probability of success is an increasing function
  of n

40
Optimal number of firms
41
Optimal number of firms
42
Research contracts

• If government can determine the optimal
  number of contracts (n), and firms engage in
  energetic research even though payments are
  independent of success, govt. should offer
  research contracts to the n lowest bidders
  competition drives price down to cost

43
Government prizes

• Even if there is no patent protection, a large
  enough prize can induce research
• If the government sets the prize properly, the
  optimal number of firms race to win it
• A higher prize stimulates excessive research
• A prize equal to the social value of the
  innovation may be too highit induces excessive
  innovation

44
Government uncertainty

• When the government has full information, patents
  and joint ventures are less desirable than prizes
  or research contracts because they distort
  pricing
• However, if inventors have more information
  before they start inventing than do government
  officials, patents and joint ventures may be
  superior

45
Patents

• Because patents lead to distortions due to
  monopoly pricing, they are less efficient than
  optimal prizes or research contracts if the
  government has sufficient information to induce
  the optimal amount of research
• Permanent patent may lead to excessive research
• By having patents last shorter periods of time,
  the government can reduce the incentive for
  excessive research

46
Patents

• Tradeoff the longer the patent, the greater the
  inducement of research (and the probability of
  success), but the larger the cost due to more
  research projects and the monopoly loss
• Government should choose patent length to
  maximize expected net social benefit
• Because of the distortions associated with
  patents, society may want fewer projects than it
  would with prizes or research contracts

47
Public policy towards innovation

• In reality, the government cannot directly
  control the number of projects
• But the government can influence the number of
  projects by establishing a system of intellectual
  property rights (e.g. patents), which affect
  firms incentives to invest in RD
• Designing an optimal patent system is a
  challenging task, however. A patent system could
  lead to either too little or too much RD
  investment.

48
Patents benefits and risks

• In the absence of patents, there may be
  inadequate investment in RD, since firms attempt
  to free ride on other firms investments
• Patents can solve the problem of
  under-investment.
• However, since patents create a winner-take-all
  competition, patents can cause over-investment.
• Other aspects of patents
• Prices
• Disclosure of invention
• Sequential innovation