Frank R. Lichtenberg

1. During the two decades prior to the Covid-19 pandemic, there were substantial reductions in the mortality and hospital utilization rates of the Danish population. From 2000 to 2019, the number o...

Objectives: We investigate the long-run impact of changes in prescription drug sales on mortality and hospital utilization in Belgium during the first two decades of the 21st century. Methods: We analyze the correlation across diseases between changes in the drugs used to treat the disease and changes in mortality or hospital utilization from that disease. The measure of the change in prescription drug sales we use is the long-run (1998–2018 or 2000–2019) change in the fraction of post-1999 drugs sold. A post-1999 drug is a drug that was not sold during 1989–1999. Results: The 1998–2018 increase in the fraction of post-1999 drugs sold is estimated to have reduced the number of years of life lost before ages 85, 75, and 65 in 2018 by about 438 thousand (31%), 225 thousand (31%), and 114 thousand (32%), respectively. The 1995–2014 increase in in the fraction of post-1999 drugs sold is estimated to have reduced the number of hospital days in 2019 by 2.66 million (20%). Conclusions: Even if we ignore the reduction in hospital utilization attributable to changes in pharmaceutical consumption, a conservative estimate of the 2018 cost per life-year before age 85 gained is EUR 6824. We estimate that previous changes in pharmaceutical consumption reduced 2019 expenditure on inpatient curative and rehabilitative care by EUR 3.55 billion, which is higher than the 2018 expenditure on drugs that were authorized during the period 1998–2018: EUR 2.99 billion.

We investigate whether the diseases for which there was more biomedical innovation had larger 1999–2019 reductions in premature mortality. Biomedical innovation related to a disease is measured by the change in the mean vintage of descriptors of PubMed articles about the disease. We analyze data on 286 million descriptors of 27 million articles about over 800 diseases. Premature mortality from a disease is significantly inversely related to the lagged vintage of descriptors of articles about the disease. In the absence of biomedical innovation, age-adjusted mortality rates would not have declined. Some factors other than biomedical innovation (e.g., a decline in smoking and an increase in educational attainment) contributed to the decline in mortality. But other factors (e.g., a rise in obesity and the prevalence of chronic conditions) contributed to an increase in mortality. Biomedical innovation reduced the mortality of white people sooner than it reduced the mortality of black people.

Background: Off-label and contraindicated prescription drug use can result in adverse health outcomes. Despite concerns, the extent and characteristics of such usage patterns remain underexplored in the American population. We conducted a cross-sectional study analysing outpatient prescription data between 2016 and 2021 to determine the prevalence of off-label and contraindicated drug use.

More recently approved drugs have significantly fewer indications than drugs approved many years ago. One possible reason for this may be that, controlling for the number of years since approval or launch, more recently approved drugs have fewer indications (e.g. at the time of launch). The role of precision and personalised medicine has increased, and the goal of precision medicine is to provide a more precise approach for the prevention, diagnosis and treatment of disease. Drugs that have fewer indications may be ‘more precise’ than drugs that have many indications. We use different kinds of data from two countries – France and the U.S. – to analyze the relationship across many drugs between the number of indications of a drug, the drug’s vintage – i.e. the year in which the drug was first marketed or approved – and its age – the number of years it has been marketed. All the evidence from both countries indicates that, controlling for drug age, more recently approved drugs tend to have fewer indications than drugs approved many years ago. In the U.S., a 10-year increase in vintage is associated with a 10.7% decline in the effective number of indications of all drugs, and a 19.4% decline in the effective number of indications of drugs approved after 1989. In France, the positive effect on the number of indications of the increase in drug age was more than offset by the negative effect of the increase in drug vintage. More recently approved drugs are less likely to be ‘general-purpose technologies’ (or even multi-purpose technologies) than older drugs. The relative importance of ‘precision medicine’ has increased in recent decades. Drugs that have fewer indications may be ‘more precise’ than drugs that have many indications.

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.