Unbiased Analysis of Today's Healthcare Issues

Trump tax bill keeps the individual mandate

Written By: Jason Shafrin - Nov• 02•17

The Trump tax bill–potentially known as the “the Tax Cuts and Jobs Act“– includes provisions such as increasing the standard deduction and reducing the number of tax brackets from 7 to 4.  Additionally, a number of deductions are removed–such as capping local and state property tax deductions at $10,000 and only allowing mortgage interest deductions for loans under $500,000–to finance the larger standard deduction and increase the child tax credit to $1,600.

One item that was not removed was the tax penalty for individuals who do not buy insurance.  The Hill reports on the decision not to eliminate the individual mandate:

The tax reform bill to be released Thursday will not include a repeal of ObamaCare’s individual mandate, sources say, despite President Trump proposing the idea on Wednesday.

Repealing the mandate would introduce a whole new area of controversy into the bill, and many Republicans think tax reform is hard enough without adding in health care…

Repealing the mandate would save around $400 billion, which could be used to help pay for tax cuts, but the Congressional Budget Office also says 15 million more people would be uninsured and premiums would rise 20 percent.
Your tax rate may change, but you’ll still need to buy insurance.

 

Interesting paper measuring the option value

Written By: Jason Shafrin - Nov• 01•17

One key benefit new cancer treatments is not only that they improve survival, but also–in areas with a lot of treatment innovation–they that they allow some patients to live to receive the next treatment advance.  Although this concept may make sense intuitively, it is not clear how one could quantify this value.

This is the problem that a paper by Thornton Snider et al. (2017) attempts to address.  Using data from SEER and clinical trials, they examine a novel immuno-oncology treatments for renal cell carcinoma (RCC) and both squamous and nonsquamous non-small cell lung cancer (NSCLC).

To estimate the conventional value of nivolumab, survival with the pre-nivolumab standard of care was compared with survival with nivolumab assuming no future innovation. To estimate the option value of nivolumab, long-term survival trends in RCC and squamous and nonsquamous NSCLC were measured in SEER to forecast mortality improvements that nivolumab patients may live to see.

Using this approach, they find:

Compared with the previous standard of care, nivolumab extended life expectancy by 6.3 months in RCC, 7.5 months in squamous NSCLC, and 4.5 months in nonsquamous NSCLC, according to conventional methods. Accounting for expected future mortality trends, nivolumab patients are likely to gain an additional 1.2 months in RCC, 0.4 months in squamous NSCLC, and 0.5 months in nonsquamous NSCLC. These option values correspond to 18%, 5%, and 10% of the conventional value of nivolumab, respectively.

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What do cancer patients value when making treatment decisions?

Written By: Jason Shafrin - Oct• 31•17

Clearly choosing treatments that extend expected survival is important, but survival expectations are not the only factor that matters to cancer patients. A 2017 NCCN policy report–based on the findings from a working group–identifies a number of factors:

Patients, for example, may view high-value care as any combination of trust, transparency, and effective communication with providers; care coordination; survivorship care; quality of life (QOL); toxicity management; limited travel for care; and limited financial risk. To this end, patient care is highly individualized.

While patients may have their own preferences, one relevant question is whether patients really want to make these tough decisions or if they want physicians to largely pick for them. Most, but not all, research indicates that patients want information and tools to make informed treatment decisions with their providers.

Recent survey data from Cancer Support Community supports these identified gaps, finding that a quarter of the 1,046 patients surveyed did not feel confident they received the care that they needed, with more than a third of respondents indicating they would have liked to have been more involved in decisions about their care and treatment options.

The authors, thus, call for more tools to help patients make informed decisions about treatment benefits, risks and costs.

Moving forward, it is important to develop measurement capacity in a value tool framework that is sensitive to cost, distress, and the individual existential experience of the cancer care journey, thus informing and shaping high-quality cancer care.

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Do HDHPs save money?

Written By: Jason Shafrin - Oct• 30•17

This is the question that Zhang et al. (2017) attempt to answer using data form people who switched to a high-deductible health plan (HDHP) compared to those who stayed in the same plan.  They found:

After enrollment in HDHPs, 28 percent of enrollees changed physicians for office visits (compared to 19 percent in the Traditional Plan group, p < .01); however, this did not result in a statistically significant reduction in price for office visits. About 25 percent of enrollees changed providers for laboratory tests (compared to 23 percent in the Traditional Plan group, p < .01), resulting in savings of about $2.09 or a 12.8 percent reduction in price per laboratory test. We found that HDHPs had lower negotiated prices for office visits but not for laboratory tests.

In short, there is some evidence for cost saving and very model price shopping effects.  Based on this study at least, demand curves do still slope down, but one shouldn’t expect the increased use of HDHPs to results in extremely large cost savings.

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How to pay for cures

Written By: Jason Shafrin - Oct• 29•17

Do you want to cure cancer?   Diabetes?  HIV?  Imagine if there was a single pill for each of these diseases that one could take to cure the diseases.  That would be a clear clinical advance, it would save lives, and also save money form reducing the cost of treating these disease.

Can we expect to see these cures?  This is partly a question of science and partly a question of finance.  On the science side, curing complex diseases is difficult and this fact should not be underestimated.  On the finance side, however, innovators have less an incentive to invent cures than to invent treatments.  For instance, let us say that someone had a drug that would treat diabetes, but patients had to pay $1000 per month over 50 years (60 months) in order to keep the disease in reemission.  This means that patients and health plans will spend $600,000 ($1000 x 50 years x 12 months) over this time period.  If someone could invent a drug that had the same efficacy in terms of long-term, 50-year disease remission, the treatment would be worth at least $600,000.  However, health plans may not be able to afford spending $600,000 per patient in the short-run.  Even if they could afford this price, many health plan enrollees leave the system after only a few years and thus health plans that pay for the $600,000 will not accrue the full benefit.

One clear solution to the first issue is to just finance the purchase of the cure with debt.  Many individuals want to own a house, but most people cannot afford to make a lump sum payment for the house.  The solution is that people take out a mortgage and spread the payments over time.  Tomas Philipson and Andrew von Eschenbach have proposed debt financings of high-value cures.  This approach, however, does not solve the free rider problem that occurs if there is frequent health plan turnover.

Another innovation is the concept of a HealthCoin developed by Basu (2015).  In this approach, the health advantages of a cure turn into an asset.  For instance, by giving someone Sovaldi to cure Hepatitis C, a health plan could earn a “HealthCoin.”  If a person who received Sovaldi later leaves the plan, he new plan where the person was enrolled would need to pay the original plan the value of the HealthCoin. A more general description is below from Yeung et al. (2017).

HealthCoin is a potential tradable currency that would be backed by Medicare, wherein Medicare guarantees payment to the private payer for each treated person entering the Medicare program.20 This option incentivizes private payers to invest in upfront coverage for cures, since cured individuals would likely have lower morbidity, and the private payer can sell the remaining value of the HealthCoins when the member switches plans

Although the concept of a HealthCoin may seem esoteric, managed care pharmacists seem to appreciate the value of this idea, once it is clearly explained to them.

Regardless if you think HealthCoins are the right answer, we need to have the right incentives in place to make sure innovators have the incentive to develop cures for highly prevalent, high-burden diseases.

 

Will CVS buy Aetna for $66 billion?

Written By: Jason Shafrin - Oct• 27•17

CVS is in talks to buy Aetna for $66 billion.  This would be a merger between one of the largest pharmacy benefits managers (PBM) in the country and the third largest insurer.

A successful deal could push millions of Aetna’s members toward CVS’s retail pharmacies, walk-in Minute Clinics, and services such as home visits for infusion drugs at a time when retail pharmacy companies are facing stiff competition.

It would also give Aetna the ability to move deeper into the lives of the 44.7 million people it serves and manage their health more efficiently. For example, the insurer might be able to get better insight into whether patients are taking their drugs by gaining access to data from CVS clinics and retail counters.

However, there may be another reason for the deal.  Amazon may be entering the medical device and even eventually the PBM business.

Amazon has received approval for wholesale pharmacy licenses in at least 12 states, including Nevada, Arizona, North Dakota, Louisiana, Alabama, New Jersey, Michigan, Connecticut, Idaho, New Hampshire, Oregon and Tennessee.

However, the CVS-Aetna deal may never happen. According to Bruce Japsen of Forbes:

Anthem just last week said it was forming its own pharmacy benefit management company, IngenioRx, with CVS, which operates a PBM. That was seen as a way to compete with the nation’s largest health insurer, UnitedHealth Group, which owns the PBM OptumRx.

But  for  CVS to operate a PBM with Anthem, the No. 2 health insurer, while owning Aetna, the No. 3 insurer, would be highly unusual coming off a period of intense antitrust scrutiny of the health insurance industry. Aetna and Humana, the nation’s fourth-largest insurer, pulled the plug on their merger last year after intense antitrust scrutiny over the potential creation of a monopoly purchaser of health services.

The health care market is rapidly evolving.  In the words of Heraclitus, “you cannot step twice into the same stream” or put more simply, “The only thing that is constant is change“.

HWR is up

Written By: Jason Shafrin - Oct• 26•17

Health Wonk Review: Disaster edition is freshly posted by David Williams at the Health Business Blog.  Check it out!

How much is your life worth?

Written By: Jason Shafrin - Oct• 24•17

According to the Environmental Protection Agency, the answer is $10 million.  Other agencies place use a somewhat lower number.  The Food and Drug administration pegs the value at $9.5 million and the Department of Agriculture places the value at $8.9 million.

Technically, what these agencies are calculating are the value of a statistical life (VSL).  Although measuring the value of a life is an interesting academic exercise, it has real world implications.  Notably, VSL is used in federal agencies cost benefit analyses.

For instance, consider a new regulation to reduce pollution that saves 10 lives but costs $50 million.  Should society undertake this intervention?  If VSL is $10 million, then the answer is ‘yes.’   Each of the 10 lives is worth $10 million so the regulation leads to $100 million in benefits but only costs $50 million.

On the other hand, consider a more drastic intervention for reducing population: making privately owned cars illegal.  In this case, let us say the intervention saved 10 lives still but the cost now is $1 billion is lost economic activity.  In this second example, the costs outweigh the benefits and so based pursed on aggregated costs and benefits, we would not implement this intervention.

For the politically minded, those who prefer more regulation would prefer a higher VSL and those who prefer less regulaion would opt for a lower VSL.

Improving catchment area definitions when measuring quality of care

Written By: Jason Shafrin - Oct• 23•17

Oftentimes, we want to measure the quality of care of a give hospital or health care system.  The easiest way of doing this is to measure the quality of care received by patients who go to that hospital.  These patients, however, may attend multiple hospitals during they year.  Further, if quality of care includes avoiding hospitalizations, we need to identify not only patients who had a hospital admission but patients who were at risk of going to that hospital if a preventable admission occurred.

One way to model quality of care is to use catchment areas.  Catchment areas are typically aggregations of geographic units.  For instance, hospital service areas (HSAs) are aggregations of ZIP codes.  However, previous research has shown that HSA-based catchment areas only capturing 50% to 80% of hospital admissions for their given population.  One could use larger geographic regions—such as hospital referral regions (HRRs)—but then one is susceptible to assigning patients to hospitals over which they are unlikely to have responsibility for their care.

My previous research on the hospital wage index (see here and here) proposed assigning a weighting of the geographic units  While that approach aimed to measure geographic variation in wages where data was available by geography rather than by person, an interesting paper by Falster, Jorn and Leyland (2017) proposes a different approach using individual patient data and a methodology known as multiple-membership multi-level model multi-level.

To explain this model, consider first a standard approach whereby where I people are clustered within J hospitals or HSAs.

 

Yij is the outcome, xpi are the regression parameters for P person-level variables, and xqj are the regression parameters for Q hospital-level variables.  This multilevel model captures the effects of clustering by allowing both regression parameters and error terms to exist at different hierarchical levels.

A multiple-membership multilevel model extends this approach by allowing a weighted structure for each of the hospital-level components as follows:

Here, the superscripts represent the different model hierarchy levels.  Faster and co-authors apply this model to date on preventable hospitalizations in NSW Australia using weighted hospital service area networks (weighted-HSANs).  The authors contend that:

Between-hospital variation in rates of preventable hospitalization was more than two times greater when modeled using weighted-HSANs rather than HSAs. Use of weighted-HSANs permitted identification of small hospitals with particularly high rates of admission and influenced performance ranking of hospitals, particularly those with a broadly distributed patient base.

 

While this approach is a significant improvement for an academic setting, it is problematic to operationalize in terms of quality improvement.  In order to improve quality, hospitals need clear rules regarding the patients to which it is attributed.  While the authors compellingly argue that multiple-membership multilevel models do a better job mof measuring quality retrospectively than would be the case using HSAs alone, operationalizing the use of weighted HSANs in practice would be more difficult due to the model complexity.  Nevertheless, this approach clearly highlights the challenges of using HAS-based catchment areas to measure quality of care.

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Health plans getting into the PBM game

Written By: Jason Shafrin - Oct• 22•17

Bloomberg reports that Anthem is creating is own pharmacy benefits manager (PBM).  Why?  It says it wasn’t getting a good deal from PBMs.

Health insurer Anthem Inc. plans to set up its own pharmacy benefits management unit, signaling a final break with Express Scripts Holding Co. after accusing it of overcharging by billions of dollars.

The move means Express Scripts will not only lose its biggest client but also face a new rival. Anthem’s new unit, called IngenioRx, will grow its own business with a “full suite” of services, the insurer said in a statement on Wednesday.

How much was the overcharging?  Anthem says the amount was $3 billion.

With drug prices on the rise, both pharma and PBM’s blame each other for high prices.  PBMs say that drug list prices are too high.  Pharmacetuical firms say they need to raise prices in order to offset large discounts and rebates that PBMs are demanding.

Anthem may not be the only firm entering the PBM market.  Amazon is also considering entering the PBM market.  UnitedHealth–Anthem’s top competitor–already has an in-house PBM known as OptumRx.

The one thing that is certain in the PBM world is that things are changing.