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The effect of pharmaceutical innovation on longevity: Evidence from the U.S. and 26 high-income countries
Abstract
This study examines the impact that pharmaceutical innovation, which accounts for most private biomedical research expenditure, has had on longevity. We perform two types of two-way fixed-effects analyses, which control for the effects of many potentially confounding variables. First, we analyze long-run (2006-2018) changes in longevity associated with different diseases in a single country: the U.S. Then, we analyze relative longevity levels associated with different diseases in 26 high-income countries during a single time period (2006-2016). The measure of longevity we analyze, mean age at time of death, is strongly positively correlated across countries with life expectancy at birth. The measure of pharmaceutical innovation we use is the mean vintage (year of initial world launch) of the drugs used to treat each disease in each country. Changes in the vintage distribution of drugs are due to both entry of new drugs and exit of old drugs.
Our analysis of U.S. data indicates that the diseases for which there were larger increases in drug vintage tended to have larger increases in the longevity of Americans of all races and both sexes. In other words, the lower the mean age of the drugs, the higher the mean age at death. We test, and are unable to reject, the “parallel trends” hypothesis. We estimate that the 2006-2018 increase in drug vintage increased the mean age at death of Americans by about 6 months (66% of the observed increase). Controlling for sex, race, and education has only a small effect on the estimate of the vintage coefficient.
The estimates indicate that drug vintage did not have a significant effect on the mean age at death of decedents with less than 9 years of education. Drug vintage had a positive and significant effect on the mean age at death of decedents with at least 9 years of education, and a larger effect on the mean age at death of decedents with at least 13 years of education. The finding that pharmaceutical innovation has a larger effect on the longevity of people with more education is consistent with previous evidence that more educated people are more likely to use newer drugs.
Our analysis of data on 26 high-income countries indicates that the higher the vintage of drugs available to treat a disease in a country, the higher mean age at death was, controlling for fixed disease and country effects. The increase in drug vintage is estimated to have increased mean age at death in the 26 countries by 1.23 years between 2006 and 2016—73% of the observed increase.
We obtain estimates of the cost of pharmaceutical innovation—its impact on drug expenditure—as well as estimates of an important benefit of pharmaceutical innovation—the number of life-years gained from it—and of their ratio, i.e., the incremental cost-effectiveness ratio. Estimates of the cost per life-year gained for the U.S. and the 26 countries are 13,904, respectively. Both figures are well below per capita GDP in the respective regions, suggesting that, overall, pharmaceutical innovation was highly cost-effective.
... Biopharmaceutical research and development (R&D) has improved patient lives worldwide and is an engine of economic growth. 1,2 It is generally agreed that the "triple helix" of interactions between private industry, government, and academia is a cornerstone of biopharmaceutical innovation, leveraging each sector's capabilities to bring innovations to the public. 3 Thus, an array of public policies across countries seek to foster these collaborations and stimulate biopharmaceutical R&D via targeted public sector spending and the creation of an environment ripe for private sector investment. ...
Robust biopharmaceutical research and development (R&D) ecosystems require investment from both the public and private sectors. In Europe, there is an interest in growing biopharmaceutical R&D given its contribution to public health and the economy, which requires an understanding of current public and private investment. In addition, recent European draft legislation has focused on the public sector's contributions to biopharmaceutical R&D to inform pharmaceutical prices. However, there is little empirical evidence on the specifics of public and private funding for medicine R&D in Europe. This paper performs aggregative data collection to quantify 2019 investment in biopharmaceutical R&D by the public and private sectors in 6 countries: Belgium, France, Germany, Norway, Poland, and the United Kingdom. We find that, across these countries, the private sector accounts for just under two-thirds of investment. We contrast results to those obtained using high-level R&D indicators from the Organization for Economic Co-operation and Development (OECD) and contextualize differences. We then provide 2013–2019 estimates for Belgium, France, Germany, and the United Kingdom (countries with data to support such analysis), and show that total spending grew over those years, although proportions attributable to each sector remained stable. These findings should provide further evidence for debates on policies to effectively grow the biopharmaceutical R&D sector.
... During this time, the notorious advances in medicine and sanitary conditions improvements significantly reduced the incidence and mortality of infectious diseases, creating an epidemiological transition scene. This scene is characterized by an increasing incidence of cardiovascular, chronic respiratory diseases, mental health and neurological disorders and diabetes as a consequence of the aging of the human population [5][6][7][8][9] . Data from a study commissioned by Roche showed that NCDs kill approximately 41 million people each year, being responsible for 71% of all deaths globally reported 10 . ...
... Over the past four decades, innovative therapies have substantially increased global life expectancy and health outcomes, with timely access to these therapies playing an essential role in attaining these results [1,2]. ...
BACKGROUND: Hospital Pharmacists (HP) intervene in multiple activities to ensure the patient access to innovative therapies in hospitals, including decision-making process.
AIM: To identify opportunities and strategies that leverage the intervention of HP to improve the access pathway to innovative therapies in hospitals of these therapies.
METHODS: After semi-structured interviews, a survey was implemented targeting Portuguese HP, followed by an expert panel with HP (n=12) to reach a consensus. Data was collected between October 2021 and March 2022.
RESULTS: 58 HP answered the survey. Even though the most important activities identified were related to HP’s support in the decision-making for approval of innovative therapies, it was consensual that there are opportunities for optimizing this process. The expert panel proposed 5 strategic actions focusing on access to legal information about innovative therapies, the approval process, and enhancing collaboration among all stakeholders.
CONCLUSION: HP’s intervention in the decision-making process is essential in the therapeutic innovation access pathway. Therefore, it is important to implement strategies to make the process faster, more informative, and efficient.
... Исследование профессора Колумбийского университета F.R. Lichtenberg, который на протяжении десятилетий изучает демографические и социально-экономические эффекты инновационных ЛП, проведенное на основе данных по 26 развитым странам, показывает, что инновационные ЛП обеспечили 73% роста продолжительности жизни, наблюдаемого между 2006-2016 гг. [4]. В рамках другого анализа [5] было установлено, что в популяции пациентов с редкими заболеваниями в период 1999-2007 гг. ...
SCIENTIFIC RELEVANCE . The rapid expansion of the range of medicines in the global pharmaceutical market determines the importance of periodically reviewing the range of innovative medicines and products at various stages of development.
AIM. This study aimed to determine the main trends in the development of innovative medicines.
DISCUSSION . This review presents information on the therapeutic effects and value of innovative medicinal products, outlines current approaches to their authorisation, and addresses the increase in their costs. The authors used information search, content analysis, and horizon scanning methods to prepare this narrative review. The review describes the global pharmaceutical pipeline for the second half of 2023, both generally and by specific aspects. The authors determined that over 21,000 pharmaceutical products were in development at the time, with approximately 23% of those in the later stages of development (from phase III clinical trials to the registration stage). The predominant indications for use were cancers. The authors separately reviewed innovations in the treatment of Alzheimer’s disease, as well as gene, cell, and RNA therapies.
CONCLUSIONS. A significant number of innovative pipeline medicines have a high likelihood of changing the landscape of current approaches to disease treatment, prevention, and diagnosis. With the rising costs of innovative medicinal products, the potential for change underscores the importance of introducing predictive tools, such as horizon scanning, into the national healthcare system.
... In recent decades, pharmaceutical innovation has been key to improving quality and increasing life expectancy. If the pharmaceuticals marketed between the 80s and 2000 were responsible for more than 40% of the increase in life expectancy worldwide, in the first decade of this century, the percentage has increased to 73% (Lichtenberg 2022). Besides, their use has allowed the eradication of diseases that caused a high rate of mortality and/or disability or have made them considered chronic. ...
Despite concerns about the potential risk associated with the environmental occurrence of pharmaceuticals and personal care products (PPCPs), few studies address the emissions of hospitals to aquatic compartments. We examined within a 3-month sampling period the occurrence and environmental risk of PPCPs in seven Tunisian hospital wastewaters. From personal care products, UV filters, main metabolites, and benzotriazoles were quantified, with benzophenone 3 (oxybenzone, BP3) and benzotriazole (BZT) the most frequently found (71%) at median concentrations in the range 2.43 ± 0.87 ngL ⁻¹ –64.05 ± 6.82 ngL ⁻¹ for BP3 and 51.67 ± 1.67 ngL ⁻¹ –254 ± 9.9 ngL ⁻¹ for BZT. High concentrations were also found for 4-hydroxybenzophenone (4HB) (221 ± 6.22 ngL ⁻¹ ), one of the main metabolites of BP3. The antibiotics ofloxacin and trimethoprim, the anti-inflammatory acetaminophen, the antiepileptic carbamazepine, and the stimulant caffeine were present in all the wastewaters. The highest median concentration corresponded to acetaminophen, with 1240 ± 94 mgL ⁻¹ in Tunis Hospital, followed by ofloxacin with 78850 ± 39 μgL ⁻¹ in Sousse Hospital. For ecotoxicity assessment, acute toxicity was observed for Daphnia magna and Vibrio fischeri . The toxicity data were used in a hazard quotient (HQ) approach to evaluate the risk posed by the target PPCPs to aquatic organisms. The calculated HQs revealed that marbofloxacin (234 for V. fischeri ), enrofloxacin (121 for D. magna ), and BZT (82.2 for D. magna and 83.7 for V. fischeri ) posed the highest risk, concluding that potential risk exists toward aquatic microorganisms. This study constitutes the first monitoring of UV filters in Tunisian hospital effluents and provides occurrence and toxicity data of PPCPs for reference in further surveys in the country.
Graphical Abstract
... Possession of specific disease-causing genes is not the only reason for contracting diseases (Farhud, 2022). The increase in the vintage of the prescription drugs years has increased the average age of death by 1.23 years in 26 countries (Lichtenberg, 2022), assuming the disease is fixed. Thus, the adequate and advanced medical care is an important means of increasing human life expectancy. ...
Purpose
Exploring a dimensionality reduction model that can adeptly eliminate outliers and select the appropriate number of clusters is of profound theoretical and practical importance. Additionally, the interpretability of these models presents a persistent challenge.
Design/methodology/approach
This paper proposes two innovative dimensionality reduction models based on integer programming (DRMBIP). These models assess compactness through the correlation of each indicator with its class center, while separation is evaluated by the correlation between different class centers. In contrast to DRMBIP-p, the DRMBIP-v considers the threshold parameter as a variable aiming to optimally balances both compactness and separation.
Findings
This study, getting data from the Global Health Observatory (GHO), investigates 141 indicators that influence life expectancy. The findings reveal that DRMBIP-p effectively reduces the dimensionality of data, ensuring compactness. It also maintains compatibility with other models. Additionally, DRMBIP-v finds the optimal result, showing exceptional separation. Visualization of the results reveals that all classes have a high compactness.
Research limitations
The DRMBIP-p requires the input of the correlation threshold parameter, which plays a pivotal role in the effectiveness of the final dimensionality reduction results. In the DRMBIP-v, modifying the threshold parameter to variable potentially emphasizes either separation or compactness. This necessitates an artificial adjustment to the overflow component within the objective function.
Practical implications
The DRMBIP presented in this paper is adept at uncovering the primary geometric structures within high-dimensional indicators. Validated by life expectancy data, this paper demonstrates potential to assist data miners with the reduction of data dimensions.
Originality/value
To our knowledge, this is the first time that integer programming has been used to build a dimensionality reduction model with indicator filtering. It not only has applications in life expectancy, but also has obvious advantages in data mining work that requires precise class centers.
... Receiving water CEC concentrations can range from ng·L −1 to μg·L −1 (Cantwell et al., 2018;Dogan et al., 2017;Letsinger et al., 2019), where CECs can have effects on living systems (Brumovský et al., 2017). In comparison to other EU countries, and despite marked rises in personal wealth and life expectancy, as well as indicators of higher medical interventions and reliance on pharmaceuticals (Lichtenberg, 2022), relatively little is known about the environmental occurrence and impact of CECs in the Irish aquatic environment. Thus far, most studies have focussed on small selections of pharmaceutical compounds (Lacey et al., 2008) and little/no environmental measurements of other CECs such as perfluorinated organic chemicals, microplastics and nanomaterials. ...
Despite being a developed country in the European Union (EU), knowledge of the nature and extent of contamination of water bodies with contaminants of emerging concern (CECs) in Ireland is limited. In this study, >140 CECs including pharmaceuticals, pesticides and personal care products were monitored in monthly samples of wastewater treatment plant (WWTP) influent, effluent and receiving surface waters at both an urban and a rural location (72 samples in total) in Ireland over a 12-month period in 2018–2019. In total, 58 CECs were detected, including several EU Water Framework Directive Watch List compounds. Of all classes, the highest concentrations were measured for pharmaceuticals across all media, i.e., propranolol in surface waters (134 ng·L⁻¹), hydrochlorothiazide in effluent (1067 ng·L⁻¹) and venlafaxine in influent wastewater (8273 ng·L⁻¹). Overall, high wastewater treatment removal was observed and a further reduction in CEC occurrence and concentration was measured via dilution in the receiving river environment. Lastly, an environmental risk assessment (ERA) was performed using risk quotients (RQ), which revealed that in surface waters, total RQ for all CECs was an order of magnitude lower than in effluents. The majority of CECs in surface waters posed a lower risk except E2 and EE2 which presented a medium risk (RQs of 3.5 and 1.1, respectively) in the rural area. This work represents the most comprehensive CEC monitoring dataset to date for Ireland which allowed for an ERA prioritisation to be performed for the first time.
... reduced cognitive limitations and bed days), whose value is more difficult to measure. (3) The total value figure shown in Table 5 does not include the value of increased longevity resulting from pharmaceutical innovation, which may be far larger (Lichtenberg 2022). ...
This study seeks to analyze the overall impact that biopharmaceutical innovation had on disability, Social Security recipiency, and the use of medical services of U.S. community residents during the period 1998–2015. We test the hypothesis that the probability of disability, Social Security recipiency, and medical care utilization associated with a medical condition is inversely related to the number of drug classes previously approved for that condition. We use data from the 1998–2015 waves of the Medical Expenditure Panel Survey and other sources to estimate probit models of an individual’s probability of disability, Social Security recipiency, and medical care utilization. The effect of biopharmaceutical innovation is identified by differences across over 200 medical conditions in the growth in the lagged number of drug classes ever approved. 18 years of previous biopharmaceutical innovation is estimated to have reduced: the number of people who were completely unable to work at a job, do housework, or go to school in 2015 by 4.5%; the number of people with cognitive limitations by 3.2%; the number of people receiving SSI in 2015 by 247 thousand (3.1%); and the number of people receiving Social Security by 984 thousand (2.0%). Previous innovation is also estimated to have caused reductions in home health visits (9.2%), inpatient events (5.7%), missed school days (5.1%), and outpatient events (4.1%). The estimated value in 2015 of some of the reductions in disability, Social Security recipiency, and use of medical care attributable to previous biopharmaceutical innovation (127 billion). However, for a number of reasons, the costs are likely to be lower, and the benefits are likely to be larger, than these figures.
Disclaimer
In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time.
Clinical trials are essential for the evaluation of new medical treatments. Their aim is to improve treatment options and insights into disease management. However, increasing bureaucracy is jeopardising the sustainability of research, particularly in academic studies. Complex processes slow down the initiation and progress of studies, and put a strain on research teams and resources. There is an urgent need to simplify these processes in order to optimise patient care. While adherence to ethical and regulatory standards remains paramount, streamlining administrative steps must occur to increase efficiency and promote research. The COVID-19 pandemic has shown that simplification is possible without compromising quality or ethics. A solution-oriented dialogue between all stakeholders is crucial to secure the future of clinical trials.
A number of authors have argued that technological innovation has increased U.S. health care spending. We investigate the impact that pharmaceutical innovation had on the average cost of U.S. health care episodes during the period 2000–2014, using data from the Bureau of Economic Analysis’ Health Care Satellite Account and other sources. We analyze the relationship across approximately 200 diseases between the growth in the number of drugs that have been approved to treat the disease and the subsequent growth in the mean amount spent per episode of care, controlling for the growth in the number of episodes and other factors. Our estimates indicate that mean episode cost is not significantly related to the number of drugs ever approved 0–4 years before, but it is significantly inversely related to the number of drugs ever approved 5–20 years before. This delay is consistent with the fact (which we document) that utilization of a drug is relatively low during the first few years after it was approved, and that some drugs may have to be consumed for several years to have their maximum impact on treatment cost. Our estimates of the effect of pharmaceutical innovation on the average cost of health care episodes are quite insensitive to the weights used and to whether we control for 3 covariates. Our most conservative estimates imply that the drugs approved during 1986–1999 reduced mean episode cost by 4.7%, and that the drugs approved during 1996–2009 reduced mean episode cost by 2.1%. If drug approvals did not affect the number of episodes, the drugs approved during 1986–1999 would have reduced 2014 medical expenditure by about $93 billion. However, drug approvals may have affected the number, as well as the average cost, of episodes. We also estimate models of hospital utilization. The number of hospital days is significantly inversely related to the number of drugs ever approved 10–19 years before, controlling for the number of disease episodes. Our estimates imply that the drugs approved during 1984–1997 reduced the number of hospital days by 10.5%. The hospital cost reduction was larger than expenditure on the drugs.
Background:
Clinical studies have shown that the use of certain drugs can reduce disability. Access to prescription drugs varies across countries. Even when the total number of drugs launched in two countries is similar, the specific drugs that were launched, and the diseases those drugs are used to treat, may differ.
Objective/hypothesis:
We test the hypothesis that the larger the relative number of drugs for a disease that were launched during 1982-2015 in a country, the lower the relative disability in 2015 of patients with that disease in that country, controlling for the average level of disability in that country and from that disease, and the number of patients with the disease and their mean age.
Methods:
We estimate two-way (by country and disease) fixed-effects models of several measures of disability for 31 diseases in eleven European countries using data from the Survey of Health, Ageing and Retirement in Europe and from other sources.
Results:
The estimates imply that drug launches during 1982-2015 reduced the probability of severe limitation in 2015 by 4.9 percentage points, from 21.8% to 16.9%; they reduced the probability of any limitation by 7.7 percentage points, from 61.1% to 53.4%; and they reduced the mean number of Activities of Daily Living limitations by about 29%. Drug launches also yielded a small increase in an index of quality of life and well-being.
Conclusions:
In general, the larger the number of drugs for a disease that were launched during 1982-2015 in a country, the lower the average disability in 2015 of patients with that disease in that country, controlling for the average level of disability in that country and from that disease, and the number of patients with the disease and their mean age.
Importance
Opioid prescribing and overdose are leading public health problems in North America, yet the precise public health burden has not been quantified.
Objective
To examine the burden of opioid-related mortality across the United States over time.
Design, Setting, and Participants
This study used a serial cross-sectional design in which cross sections were examined at different time points to investigate deaths from opioid-related causes in the United States between January 1, 2001, and December 31, 2016.
Main Outcomes and Measures
Opioid-related deaths, defined as those in which a prescription or illicit opioid contributed substantially to an individual’s cause of death as determined by death certificates. We compared the percentage of deaths attributable to opioids and the associated person-years of life lost by age group.
Results
Between 2001 and 2016, the number of opioid-related deaths in the United States increased by 345%, from 9489 to 42 245 deaths (33.3 to 130.7 deaths per million population). By 2016, men accounted for 67.5% of all opioid-related deaths, and the median (interquartile range) age at death was 40 (30-52) years. The percentage of deaths attributable to opioids increased in a similar fashion. In 2001, 0.4% of deaths (1 in 255) were opioid related, rising to 1.5% of deaths (1 in 65) by 2016, an increase of 292%. This burden was highest among adults aged 24 to 35 years. In this age group, 20.0% of deaths were attributable to opioids in 2016. Among those aged 15 to 24 years, 12.4% of deaths were attributable to opioids in 2016. Overall, opioid-related deaths resulted in 1 681 359 years of life lost (5.2 per 1000 population) in the United States in 2016, most of which (1 125 711 years of life lost) were among men. Adults aged 25 to 34 years had 12.9 years of life lost per 1000 population, and those aged 35 to 44 years had 9.9 years of life lost per 1000 population.
Conclusions and Relevance
Premature death from opioid-related causes imposes an enormous public health burden across the United States. The recent increase in deaths attributable to opioids among those aged 15 to 34 years highlights a need for targeted programs and policies that focus on improved addiction care and harm reduction measures in this high-risk population.
Cost-effectiveness analysis is used to compare the costs and outcomes of alternative policy options. Each resulting cost-effectiveness ratio represents the magnitude of additional health gained per additional unit of resources spent. Cost-effectiveness thresholds allow cost-effectiveness ratios that represent good or very good value for money to be identified. In 2001, the World Health Organization’s Commission on Macroeconomics in Health suggested cost-effectiveness thresholds based on multiples of a country’s per-capita gross domestic product (GDP). In some contexts, in choosing which health interventions to fund and which not to fund, these thresholds have been used as decision rules. However, experience with the use of such GDP-based thresholds in decision-making processes at country level shows them to lack country specificity and this-in addition to uncertainty in the modelled cost-effectiveness ratios-can lead to the wrong decision on how to spend health-care resources. Cost-effectiveness information should be used alongside other considerations-e.g. budget impact and feasibility considerations-in a transparent decision-making process, rather than in isolation based on a single threshold value. Although cost-effectiveness ratios are undoubtedly informative in assessing value for money, countries should be encouraged to develop a context-specific process for decision-making that is supported by legislation, has stakeholder buy-in, for example the involvement of civil society organizations and patient groups, and is transparent, consistent and fair.
We examine the effects of two important types of medical innovation—diagnostic imaging innovation and pharmaceutical innovation—and cancer incidence rates on U.S. cancer mortality rates during the period 1996-2006. The outcome measure we use is not subject to lead-time bias, and our measures of medical innovation are based on extensive data on treatments given to large numbers of patients with different types of cancer. We estimate difference-in-difference models of the age-adjusted cancer mortality rate using longitudinal, annual, cancer-site-level data on over 60 cancer sites. There is a significant inverse relationship between the cancer mortality rate and both lagged imaging innovation and contemporaneous drug innovation, and a significant positive relationship between the cancer mortality rate and the lagged incidence rate. Imaging innovation, drug innovation, and declining incidence jointly explain about three-fourths of the decline in cancer mortality. Only 7% of the mortality decline is attributable to the decline in (lagged) incidence. About one-fourth of the mortality decline is attributable to drug innovation, and 40% of the decline is attributable to (lagged) imaging innovation. Life expectancy at birth may have been increased by almost three months between 1996 and 2006 by the combined effects of cancer imaging and cancer drug innovation.
We develop a model of repeated product improvements in a continuum of sectors. Each product follows a stochastic progression
up a quality ladder. Progress is not uniform across sectors, so an equilibrium distribution of qualities evolves over time.
But the rate of aggregate growth is constant. The growth rate responds to profit incentives in the R&D sector. We explore
the welfare properties of our model. Then we relate our approach to an alternative one that views product innovation as a
process of generating an ever-expanding range of horizontally differentiated products. Finally, we apply the model to issues
of resource accumulation and international trade.
Objectives
The objective of this study was to investigate whether estimates of ‘potential gains in life expectancy’ (PGLE) are potentially unreliable.
Study design
We compare the sum of the PGLEs from actual 1999-2017 reductions in U.S. mortality from all causes to the actual change in life expectancy of the entire population.
Methods
Multiple-decrement life table techniques are used to calculate the PGLEs from the actual reductions in age-specific rates of mortality from 113 causes. Then, the sum of the estimated PGLEs is compared to the actual change in life expectancy (LE) of the entire population.
Results
The sum of the estimated gains in LE at birth is 40% larger than the actual increase in LE at birth: 2.7 years vs 1.9 years. The sum of the estimated gains in LE at age 65 years is 40% smaller than the actual increase in LE at age 65 years: 1.0 years vs 1.7 years.
Conclusions
The fact that the sum of the estimated gains in LE from all diseases differs substantially (in both directions) from the actual increase in LE suggests that estimates of PGLE are potentially unreliable.
Linear regressions with period and group fixed effects are widely used to estimate treatment effects. We show that they estimate weighted sums of the average treatment effects (ATE ) in each group and period, with weights that may be negative. Due to the negative weights, the linear regression coefficient may for instance be negative while all the ATEs are positive. We propose another estimator that solves this issue. In the two applications we revisit, it is significantly different from the linear regression estimator. (JEL C21, C23, D72, J31, J51, L82)
There are two types of prescription drug cost offsets. The first type of cost offset – from prescription drug use – is primarily about the effect of changes in drug quantity (e.g. due to changes in out-of-pocket drug costs) on other medical costs. Previous studies indicate that the cost offsets from prescription drug use may slightly exceed the cost of the drugs themselves. The second type of cost offset – the cost offset from prescription drug innovation – is primarily about the effect of prescription drug quality on other medical costs. Two previous studies (of a single disease or a single country) found that pharmaceutical innovation reduced hospitalization, and that the reduction in hospital cost from the use of newer drugs was considerably greater than the innovation-induced increase in pharmaceutical expenditure. In this study, we reexamine the impact that pharmaceutical innovation has had on hospitalization, employing a different type of 2-way fixed effects research design. In lieu of analyzing different countries over time for a single disease, or different diseases over time for a single country, we estimate the impact that new drug launches that occurred during the period 1982–2015 had on hospitalization in 2015 for 67 diseases in 15 OECD countries. Our models include both country fixed effects and disease fixed effects, which control for the average propensity of people to be hospitalized in each country and from each disease. The number of hospital discharges and days of care in 2015 is significantly inversely related to the number of drugs launched during 1982–2005, but not significantly related to the number of drugs launched after 2005. (Utilization of drugs during the first few years after they are launched is relatively low, and drugs for chronic conditions may have to be consumed for several years to achieve full effectiveness.) The estimates imply that, if no new drugs had been launched after 1981, total days of care in 2015 would have been 163% higher than it actually was. The estimated reduction in 2015 hospital expenditure that may be attributable to post-1981 drug launches was 5.3 times as large as 2015 expenditure on those drugs.
Obesity is associated with serious health risks. Monitoring obesity
prevalence is relevant for public health programs that focus on reducing
or preventing obesity. Between 2003–2004 and 2013–2014, there were no
significant changes in childhood obesity prevalence, but adults showed an
increasing trend. This report provides the most recent national estimates
from 2015–2016 on obesity prevalence by sex, age, and race and Hispanic
origin, and overall estimates from 1999–2000 through 2015–2016.
There is a large body of work that documents a strong, positive correlation between education and measures of health, but little is known about the mechanisms by which education might affect health. One possibility is that more educated individuals are more likely to adopt new medical technologies. We investigate this theory by asking whether more educated people are more likely to use newer drugs, while controlling for other individual characteristics, such as income and insurance status. Using the 1997 MEPS, we find that more highly educated people are more likely to use drugs more recently approved by the FDA. We find that education only matters for individuals who repeatedly purchase drugs for a given condition, suggesting that the more educated are better able to learn from experience.
It is not widely recognized that conventional measures of national income and output exclude the value of improvements in the health status of the population. The present study discusses the theory of the measurement of national income, proposes a new concept called "health income" that can be used to incorporate improvements in health status, and applies the theory to data for the United States over the 20th century. It concludes that accounting for improvements in the health status would, over the twentieth century in the United States, make a substantial difference to our measures of economic welfare. *William D. Nordhaus is Sterling Professor of Economics at Yale University. He is a member of the National Academy of Sciences, a Fellow of the American Academy of Arts and Sciences, and is on the research staffs of the Cowles Foundation and of the National Bureau of Economic Research. He serves on the Congressional Budget Office Panel of Economic Experts and is Chair of the Advisory Committee for the Bureau of Economic Analysis. From 1977 to 1979, he was a member of the President's Council of Economic Advisers, and from 1986 to 1988 he served as the Provost of Yale Uni- versity. The present research was supported by the National Science Foundation. The author is grateful for research support of Joseph Boyer and for helpful comments from William Brainard, David Cutler, Angus Deaton, Robert Gordon, and T. N. Srinivasan.
COPD represents an important public health challenge, in the US and globally, that is both preventable and treatable. We describe the average age at death from COPD, a leading cause of death in the US, using data from the National Vital Statistics System for the periods 1980–85, 1990–95, and 2000–05. Average age at death from COPD increased 3–4 years between 1980–85 and 2000–05 for men and women as well as for Whites and Blacks.
There is a large body of work that documents a strong, positive correlation between education and measures of health, but little is known about the mechanisms by which education might affect health. One possibility is that more educated individuals are more likely to adopt new medical technologies. We investigate this theory by asking whether more educated people are more likely to use newer drugs, while controlling for other individual characteristics, such as income and insurance status. Using the 1997 Medical Expenditure Panel Survey (MEPS), we find that more highly educated people are more likely to use drugs more recently approved by the FDA. We find that education only matters for individuals who repeatedly purchase drugs for a given condition, suggesting that the cost of searching for higher-quality treatments is lower for more educated people.
We study an economy in which firms use labor and various vintages of capital in a CES production function for the final good. We explicitly solve for the investment in capital of a given vintage as a function of its age, and for the resulting stocks of capital. We show that for reasonable parameter values, inverted-U-shaped dynamics of investment and S-shaped dynamics for capital arise in equilibrium. We view the model as an explanation of intra-firm adoption lags, i.e., the observation that firms adopt innovations over time and not instantaneously.
In this chapter we argue that the endogenous growth model with quality-improving innovations provides a framework for analyzing the determinants of long-run growth and convergence that is versatile, simple and empirically useful. Versatile, as the same framework can be used to analyze how growth interacts with development and cross-country convergence and divergence, how it interacts with industrial organization and in particular market structure, and how it interacts with organizations and institutional change. Simple, since all these aspects can be analyzed using the same elementary model. Empirically useful, as the framework generates a whole range of new microeconomic and macroeconomic predictions while it addresses empirical criticisms raised by other endogenous growth models in the literature.
Growth in this model is driven by technological change that arises from intentional investment decisions made by profit-maximizing agents. The distinguishing feature of the technology as an input is that it is not a conventional good or a public good; it is a nonrival, partially excludable good. Because of the noconvexity introduced by a nonrival good, price-taking competition cannot be supported. Instead, the equilibrium is one with monopolistic competition. The main conclusions are that the stock of human capital determines the rate of growth, that too little human capital is devoted to research in equilibrium, that integration into world markets will increase growth rates, and that a large population is not sufficient to generate growth. Copyright 1990 by University of Chicago Press.
We develop a framework for valuing improvements in health and apply it to past and prospective reductions in mortality in the United States. We calculate social values of (i) increased longevity over the twentieth century, (ii) progress against various diseases after 1970, and (iii) potential future progress against major diseases. Cumulative gains in life expectancy after 1900 were worth over 3.2 trillion per year to national wealth, equal to about half of GDP. Potential gains from future health improvements are also large; for example, a 1 percent reduction in cancer mortality would be worth $500 billion.
Public and private financial support of biomedical research have increased over the past decade. Few comprehensive analyses of the sources and uses of funds are available. This results in inadequate information on which to base investment decisions because not all sources allow equal latitude to explore hypotheses having scientific or clinical importance and creates a barrier to judging the value of research to society.
To quantify funding trends from 1994 to 2004 of basic, translational, and clinical biomedical research by principal sponsors based in the United States.
Publicly available data were compiled for the federal, state, and local governments; foundations; charities; universities; and industry. Proprietary (by subscription but openly available) databases were used to supplement public sources.
Total actual research spending, growth rates, and type of research with inflation adjustment.
Biomedical research funding increased from 37.1 billion dollars in 1994 to 94.3 billion dollars in 2003 and doubled when adjusted for inflation. Principal research sponsors in 2003 were industry (57%) and the National Institutes of Health (28%). Relative proportions from all public and private sources did not change. Industry sponsorship of clinical trials increased from 4.0 dollars to 14.2 billion dollars (in real terms) while federal proportions devoted to basic and applied research were unchanged. The United States spent an estimated 5.6% of its total health expenditures on biomedical research, more than any other country, but less than 0.1% for health services research. From an economic perspective, biotechnology and medical device companies were most productive, as measured by new diagnostic and therapeutic devices per dollar of research and development cost. Productivity declined for new pharmaceuticals.
Enhancing research productivity and evaluation of benefit are pressing challenges, requiring (1) more effective translation of basic scientific knowledge to clinical application; (2) critical appraisal of rapidly moving scientific areas to guide investment where clinical need is greatest, not only where commercial opportunity is currently perceived; and (3) more specific information about sources and uses of research funds than is generally available to allow informed investment decisions. Responsibility falls on industry, government, and foundations to bring these changes about with a longer-term view of research value.
This paper provides a survey on studies that analyze the macroeconomic effects of intellectual property rights (IPR). The first part of this paper introduces different patent policy instruments and reviews their effects on R&D and economic growth. This part also discusses the distortionary effects and distributional consequences of IPR protection as well as empirical evidence on the effects of patent rights. Then, the second part considers the international aspects of IPR protection. In summary, this paper draws the following conclusions from the literature. Firstly, different patent policy instruments have different effects on R&D and growth. Secondly, there is empirical evidence supporting a positive relationship between IPR protection and innovation, but the evidence is stronger for developed countries than for developing countries. Thirdly, the optimal level of IPR protection should tradeoff the social benefits of enhanced innovation against the social costs of multiple distortions and income inequality. Finally, in an open economy, achieving the globally optimal level of protection requires an international coordination (rather than the harmonization) of IPR protection.
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