Unbiased Analysis of Today's Healthcare Issues

Friday Links

Written By: Jason Shafrin - Jan• 04•18
  • Science facts from 2017.
  • Peak pharma?
  • 2017 year in charts.
  • Nature’s 10.
  • Physicians ignore an important source of data…the patient.  “If you don’t sit and talk with a patient for a half hour, in terms of your job description no one is going to be mad at you. But if you don’t know what the hemoglobin is on the patient, the chief of medicine is going to be very upset with you.”

The Healthcare Economist will be on vacation next week.

The Mediterranean Diet is supposed to be very healthy. Can you write me a prescription for a vacation in Greece?

How does cost sharing rules influence drug prices in Germany?

Written By: Jason Shafrin - Jan• 02•18

Typically, we look at how changes in cost sharing affect patient demand.  However, rules regarding patient cost sharing also influence life sciences firms’ decisions about what price they should use for their products.  A paper by Herr and Suppliet (2017) looks at the effect of changing cost-sharing rules in Germany in their latest paper.

The study first reviews how drug prices are set in Germany.

…drug prices are uniform across all pharmacies and the same co-payment scheme applies to all those who are publicly insured. Pharmacists receive reimbursements directly from the health insurance companies, namely a fixed fee per package plus a fraction of the drug’s price (3 percent)…In general, drug co-payments in Germany are defined as 10 per-cent of the pharmacy’s selling price (or the reference price if the price lies above) with a minimum of €5 and a maximum of €10, plus the difference between that and the reference price, if applicable.

The authors discuss how the use of copayment exemption levels (CEL) affect demand for pharmaceuticals.  These CELs are a set price, below which patients do not have to pay a copayment for these pharmaceuticals.  The CEL depends on the reference price which is set at the 30th percentile of the prior year’s prices for drugs within a specific therapeutic basket.  Most generics (99%) and brands (77%) are set below this reference price.

The authors attempt to measure the causal effect of prices on demand using a difference-in-differences approach that using the sequential introduction of the CEL across different therapeutic groups as the source of variability. The key assumption for the difference-in-difference approach is that the timing of the introduction of CEL is exogenous, in other words, the CEL was not applied to therapeutic classes where drug prices were rising or falling more or less quickly in a systematic way.  The authors also use a 2SLS with instruments on the supply side of packaging costs (i.e., the cost of paper, plastic, and ink) and the introduction of CEL as a demand side instrument.

In their empirical case study, the authors use a nested logit to model demand for anti-epileptics drugs. The authors find that:

…the introduction of tiered co-payments leads to decreasing drug prices and to market segmentation in the German reference price market…The policy has a negative effect of 5 percent on generic prices while brand-name drugs’ prices increase by 4 percent due to the new regulation.  This pattern is similar to the price increases of brand-name drugs after generic entry,the “generic competition paradox”.

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How did the Affordable Care Act affect the U.S. labor supply?

Written By: Jason Shafrin - Jan• 01•18

The Affordable Care Act (ACA) aimed to increase health insurance coverage largely through two pathways: (i) raising the income limits for individuals to qualify for Medicaid, (ii) creating new health insurance exchanges and health insurance subsidies to encourage the purchase of private health insurance among individuals that were not eligible for Medicaid.  Other provisions, such as the health insurance mandate, clearly also had an impact on coverage.  One study found that 19.2 million non-elderly individuals gained health insurance coverage as a result of ACA between 2010 to 2015.

A separate question is whether the increased insurance generosity increased or decreased individual labor supply.  On the one hand, the ACA may reduce the labor supply.  Reducing one’s income increases the likelihood of qualifying for Medicaid.  Also, within the exchanges, the subsidies are decline with income and thus additional income is in essence taxed at a higher rate (through subsidy reduction), thus discouraging work.  Additionally, the Medicaid expansion and subsidies are transfers and in essence increase individual wealth.  Since leisure is desirable, people may decide to work less if it is easier to purchase insurance after the ACA.  On the other hand, people may place more value on private health insurance relative to Medicaid.  If the private health insurance becomes more affordable with the subsidies, people may want to work more to be able to afford to purchase private insurance.

An NBER working paper by Mark Duggan, Gopi Shah Goda, Emilie Jackson (2017) aim to determine how the ACA affected labor supply. They use variation in whether states expanded Medicaid to conduct a difference-in-difference analysis using data from the American Community Survey (ACS). They find that:

…the average labor supply effects of the ACA were close to zero but that this average masks important heterogeneity in its effects. More specifically, we find that in areas with a high share uninsured and eligible for private insurance subsidies, labor force participation fell significantly. In contrast, in areas with a high share uninsured but with incomes too low to qualify for private insurance subsidies, labor force participation increased significantly. These changes suggest that middle-income individuals reduced their labor supply due to the additional tax on earnings while lower income individuals worked more in order to qualify for private insurance. In the aggregate, these countervailing effects approximately balance.

An important question since although expanding health insurance likely increases utility for those who now gain coverage, when measuring the societal benefit we must not only take into account the deadweight loss from the additional taxation needed to fund the system, but also how labor supply response to the changing health insurance market.

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Friday Links

Written By: Jason Shafrin - Dec• 28•17

Top Health Economics Stories of 2017

Written By: Jason Shafrin - Dec• 26•17

What were the top stories at the intersection of health and economics stories in 2017?  Here is the Healthcare Economist’s take.

Obamacare repeal. One of the top stories clearly must be the on-going debate around the repeal of the Affordable Care Act (ACA, a.k.a. Obamacare).  Although the ACA was not fully repealed, the most recent Republican tax legislation will repeal the individual mandate. Donald Trump today predicted that the repeal of the individual mandate will eventually cripple Obamacare leading to the need to replace it.  This prediction is not crazy as by repealing the individual mandate may cause healthy individuals to drop out of the health insurance market, leading to rising premiums, and the potential for an adverse selection death spiral.

Digital medicine is here.  The FDA this year approved the first digital medicine, an antipsychotic with an embedded sensor linked to patient’s smartphone’s and the cloud to better track patient adherence.  My own research has shown that giving physicians real-time, accurate patient drug adherence information can improve treatment decisions for providers treating patients with serious mental illness.  In fact, these types of digital medicines could lead to over $2000 in cost savings if physicians used this improved adherence information.

CAR-T launches with value-based pricing.  Two life sciences firms have gotten FDA approval for new CAR-T (chimeric antigen receptor T-cell) therapy.  The treatments have shown dramatic improvements in patient outcomes, but and are administered one time–rather than in multiple doses across months or years as would be the case for many chemotherapies.  Although the treatments cost $475,000, some payers–such as Medicare–will only pay for the treatments if they demonstrate improved patient outcomes. Not only is this medical breakthrough newsworthy, but so is this innovative pricing scheme.

The opioid epidemic is here.  The CDC reported that opioid deaths are rising among America’s teens.  Donald Trump declared that a state of emergency due to this crisis.  One film I saw, Heroin(e), documents not only the opioid epidemic but the first responders, police officers, judges, and others who are helping to fight this epidemic.   Unfortunately, this health story is likely to make the list again in 2018 unless there are serious efforts to combat the epidemic.

Antibiotic resistant bacteria represent a major public health challenge.  One report identified a numerous outbreaks of antibiotic resistant bacteria, known as CREs.  Seth Seabury and Neeraj Sood argue for a new model to incentivize life sciences firms and researchers to develop new antibiotics to fight this new and deadly threat.  Antibiotic resistance is a top priority at the World Health Organization as well.

Follow the money. An interesting paper by Sood, Shih, Van Nuys and Goldman tracks the flow of funds through the pharmaceutical system.  They find that “…for every $100 spent at retail pharmacies, about $17 compensates for direct production costs, $41 accrues to the manufacturer ($15 of which is net profit), and $41 accrues to intermediaries in the distribution system: wholesalers, pharmacies, pharmacy benefit managers and insurers (with $8 of net profit split among them).”

The Innovation and Value Initiative launches its Open-Source Value Project.  With value frameworks gaining more an more traction, IVI has launched an open-source tool to help a variety of stakeholders evaluate treatment value.  The tool is completely transparent, is based on the latest scientific findings, and allows users to measure treatment value based on their own preferences or preferences over the population which they are managing.  The first Open-Source Value Project covers DMARDs treating patients with moderate to severe rheumatoid arthritis.

 

What happens to CHIP?

Written By: Jason Shafrin - Dec• 26•17

The Children’s Health Insurance Program (CHIP) is a federal program that provides matching funds to states in order for them to provide health insurance to children.  The program was designed to cover uninsured children in families with incomes that are modest but too high to qualify for Medicaid.

Currently, however, the program is in jeopardy.  In fact, federal funding for CHIP expired September 30.  Some states, such as Colorado, have supplied emergency funding to keep CHIP afloat in their states.  On December 21, the federal government did pass $2.85 billion of emergency funding.  As funding was backdated to October 1, the 6 months of funding will only cover expenses through the end of March, 2018.

There are arguments on both sides of the aisle about the merits of CHIP.  Provide health insurance to kids has clear value to these children and their families.  Also, CHIP makes the U.S. society more equitable.  Those opposed to CHIP may prefer other ways to help kids get insurance, such as vouchers to purchase private insurance, or may even prefer to end CHIP and spend the tax money on other federal programs (e.g., education, defense), or tax cuts or may fear that CHIP may decrease the labor supply of parents who otherwise would work to get coverage for their kids.

Regardless of where you stand on the political spectrum, this uncertainty is clearly bad for all involved.  States have a hard time planning their budgets if they are unsure whether federal funds will materialized.  The federal government’s need to dip into emergency funding leads to a lack of fiscal discipline.  These expenses should be planned for.  Most importantly, parents and their children need to be able to plan for the future.  If CHIP is available, clearly many parents will want this coverage for their children.  If the program is not available, however, then perhaps some would return to work at suboptimal jobs rather than continue a job hunt in order to get health insurance for their family.  Large purchases (e.g., house, car, durable goods) clearly depend on the amount disposable income families have and this amount would decreases significantly if they had to buy insurance rather than be covered through CHIP.

Clear planning, transparency, and predictability are the hallmarks of good government.  This debate over CHIP funding–similar to the debates over the “doc fix” over physician reimbursement–shows that these emergency funding approaches are not only bad for the budget, but they hurt the people they are supposed to help by increasing the amount of uncertainty in their lives.

Friday Links

Written By: Jason Shafrin - Dec• 21•17

Why fighting disease is hard

Written By: Jason Shafrin - Dec• 19•17

Without a doubt, medicine has made tremendous gains over the last decades and even more progress when viewed across centuries.  Often to treat diseases, physicians and researchers identify a single or primary pathway that is causing the disease.  Maybe there is a gene mutation which causes an abnormality.  Maybe there is a bacteria or virus that is invading the body.  Typically, we look for a single disease cause and identify treatments to that can address this root cause.

Things get much more complicated, however, when disease a disease is caused by numerous factors.  Consider the following example from the book I Contain Multitudes: The Microbes within us and a gander View of Life, examining the case study of researcher Herbert Virgin and his analyses of mice with genetic mutations for Crohn’s disease.

These rodents developed inflated guts, but only if they were infected by a virus that knocked out part of their immune system, and were exposed to an inflammatory toxin and had a normal set of gut bacteria.  If any of these triggers was missing, the mice stayed healthy.  It was the combination of genetic susceptibility, viral infection, immune probles, environmental toxin, and their microbiome that gave them IBD [Irritable Bowel Disease].

Identifying multiple root causes is complex.  In this case, by addressing one of these causes, IBD could be cured.  In practice, however, sometime there many be cases that without addressing all causes, the individual may not recover normal health.

This complexity certainly makes for interesting research for scientist, but also highlights that perhaps medicine has only begun to address the low hanging fruits.  While there is much potential to further cure human diseases, doing so will likely become increasing complex.

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How is Washington State using evidence-based medicine?

Written By: Jason Shafrin - Dec• 18•17

A paper by Rothman et al. (2017) explains what goes on at the Washington Health Technology Assessment Program’s (WHTAP), the first state-administered health technology assessment (HTA) program in the U.S.:

Over the past 9 years, Washington State has been pursuing an innovative and generally effective program to use evidence-based medicine to determine state health care coverage decisions. Its Health Technology Assessment Program committee evaluates diagnostic and therapeutic technologies—except pharmaceuticals, the responsibility of a different group—by the criteria of safety, efficacy, and cost-effectiveness.

How are new diagnostic and therapeutics to be evaluated?  The answer is purely based on cost. As one state official said:

We will be looking for emerging or fast-growing technologies that could have the biggest impact on the state’s budget.

Once treatments are selected, WHTAP determines whether to cover a technology, cover it with conditions, or simply deny coverage.  These decisions affect coverage decisions for state employees, Medicaid, state worker’s compensation programs and correctional health.  Between 2007 and 2013, 67% of technologies of the 39 technologies that were reviewed were covered with conditions, 26% denied, but only 8% covered with no conditions. The key factors affecting this decision were lack of efficacy and lack of safety; a lack of cost-effectiveness only because relevant for technologies with significant capital outlays (e.g., robotic surgery purchases). The factor with the smallest influence was cost-effectiveness.

While using treatments supported by evidence is clearly a good thing, the effect of WHTAP’s decisions on state finances or clinical outcomes is not well known as data are limited.  Further, practicing top-down medicine to identify treatments that are high-value for the average patient may be problematic if there exists significant clinical heterogeneity that physicians, nurses or other health professionals can observe on the ground, but that WHTAP committee members may not be able to see.  Identifying evidence-based treatments is useful; however, we need to keep medical decision-making in the hand of the physician-patient relationship informed by–rather than mandated by–evidence based medicine.

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The Big Five

Written By: Jason Shafrin - Dec• 17•17

UnitedHealthcare, Anthem, Aetna, Cigna and Humana are the five largest health insurers in America. To learn more about them, check out a recent paper by Schoen and Collins (2017) in Health Affairs.

The five largest US commercial health insurance companies together enroll 125 million members, or 43 percent of the country’s insured population…In 2016 Medicare and Medicaid accounted for nearly 60 percent of the companies’ health care revenues and 20 percent of their comprehensive plan membership. Although headlines have focused on losses in the state Marketplaces created by the Affordable Care Act (ACA), the Marketplaces represent only a small fraction of insurers’ members.

With CVS and Aetna merging, it will be interesting to see if Aetna’s market share grows or shrinks based on this merger.