Unbiased Analysis of Today's Healthcare Issues

Quotation of the Day

Written By: Jason Shafrin - Oct• 20•17

To achieve greatness, two things are needed: a plan and not quite enough time

  • Leonard Bernstein


Written By: Jason Shafrin - Oct• 20•17

Measuring hospital quality requires understanding what a hospital is

Written By: Jason Shafrin - Oct• 19•17

Many programs–such as Medicare’s Hospital Value-Based Purchasing (HVBP) program–aim to reward hospitals with high quality through higher reimbursement and penalize hospitals with low quality through lower reimbursement.  Will this approach be successful?

A commentary by McMahon and Howell (2017) says that hospitals are not really unified entities but rather a collection of workshops.

Thus, the authors claim:

A policy that applies penalties across the entire Medicare line of business in a hospital based on the outcomes of selected tracer conditions is problematic.  The hospital providers caring for patients with an acute myocardial infarction are different from those caring for patients with pneumonia: the doctors are different, the nurses are different, the social workers are different, the physical locations in the hospital are different. Penalizing the entire hospital for deficiencies in a specific type of disease neither makes sense nor is it likely to be an effective way of changing behavior.

So if value-based payments at the hospital level won’t work, what makes sense?  The authors argue for better alignment between hospital and physician value-based purchasing programs.

Some physicians base the bulk of their practice and payment on hospital-centric services (for example, cardiac surgery); while others, like psychiatry, are less linked between inpatient processes and subsequent patient outcomes. For these hospital-centric product lines, the hospital-based penalties and quality metrics must necessarily be aligned with the physician-based penalties and quality metrics

More importantly, they argue that a better understanding of the key decision-makers, culture, and organization of hospitals is a necessary condition to affect any key quality improvements.

An interesting perspective and worth a read.


Why are hospital prices crazy?

Written By: Jason Shafrin - Oct• 18•17

Sarah Kliff of Vox has an interesting article looking at hospital pricing.  She provides examples of $629 for a Band-Aid in an emergency department to over $3,000 to look at a bruised finger.

Part of these high costs are not just physician time and treatment materials but a facility fee.  The facility fee is basically the cost of keeping the emergency department open in terms of overhead, lighting, the availability of high-tech equipment, etc.  This cost is often spread across all visits.  However, the facility fee cost can range from $500 to $3000 according to the article.  Is this cost reasonable?

“I see both sides,” says Renee Hsia, a professor at University of California San Francisco who studies emergency billing and helped me analyze that bill. “I think there are going to be facility charges regardless of the actual service that will always be part of ER care. But where this father has a reasonable point is that when you look at the cost of the Band-Aid and the proportional overhead, it just feels really crazy.”

Clearly if hospitals were setting prices for consumers, the cost for a $600 Band-Aid would be problematic in a market setting.  However, because there is less competition for emergency room business–patients often have to go to the closest facility–the market may not work well.  Additionally, hospitals are not pricing for patients but their primary customers–insurance companies.  Prices are often set strategically to maximize reimbursement from health plans.

As more cost sharing is shifted to patients through high-deductible health plans, however, patients are being exposed to more of these pricing irregularities.  For a health plan, any pricing anomaly for one patient is not a problem if prices are unreasonably lower for other patients.  Further, health plans don’t plan the sticker price but rather a negotiated lower rate.  Thus, there is a further disconnect between health plan and patient prices.

I can’t tell you if hospital prices for specific services are too high or too low as providing health care services is expensive.  If more cost sharing is moved towards patients, however, additional pricing transparency is needed to insure that patients know what to expect financially when they need health care services.

Are new cancer treatments improving survival or quality of life?

Written By: Jason Shafrin - Oct• 16•17

This is the question that a recent study in BMJ by Davis et al. (2017) attempts to answer.  They use data from 48 cancer drugs for 68 indications that were approved by the European Medicines Agency (EMA) between 2009 and 2013.  Among these 68 indications, they found that:

only 35 (51%) were associated with significant improvement in survival or quality of life over alternative treatment options, placebo, or as add on treatment. For 33 (49%), uncertainty remains over whether the drugs extend survival or improve quality of life.

Now clearly we need to mention (citing Carl Sagan) that “Absence of evidence is not evidence of absence!”  In other words, the evidence did not show that overall survival (OS) and quality of life (QoL) did not improve, rather that this information was not collected.  The authors argue that the lack of evidence is a clear issue.  While as I researcher I would of course prefer more evidence on OS and QoL, creating studies that measure OS and QoL are costly and time-consuming.  Thus, how big an issue is it that the EMA is using surrogate outcomes to estimate treatment benefits?

One factor is how closely surrogate and OS/QoL outcomes are correlated. One of my studies showed that real-world OS benefits were about 16% lower in the real-world compared to the benefits shown using surrogate endpoints.  Thus, we see that the correlation–at least for the tumors studies–is fairly strong but far from perfect.

Second, we need to look at the cost of collecting the OS and QoL data.  If the cost of very high, it is better to rely on surrogate outcomes.  If the cost is low, then regulators or payers should incentivize the collection of OS and QoL data.

Third, we need to look at the benefits of early access to medicines relative to the cost or approving treatments that not likely to have OS or QoL benefits.  There clearly is a tradeoff, but patients have been shown to have preferences for treatments with some positive chance of long-term durable survival gains.  The authors look at median gains in survival and also median survival gains across treatments, however.

Thus, I agree with Davis and co-authors that more data on overall survival and quality of life would be good.  The relevant policy question, however, is whether collecting this additional information is worth the cost.  This clearly is an area for further research.


Outcomes-based contracts: Where are we now?

Written By: Jason Shafrin - Oct• 15•17

“Value” is the latest trend in health care.  However, how does value get integrated into reimbursement?  One approach to tying value to prices is through and outcomes based contract (OBC) where the reimbursement for a drug will depend on the real world outcomes experienced by the relevant patient population.

A study by Nazareth et al. (2017) aims to examine the number of outcomes-based contracts through targeted literature review, University of Washington’s Performance Based Risk Sharing (PBRS) database, and interviews with payers.  They find:

With approximately 10 OBCs per year implemented over the last 5 years, Italy was at the forefront of OBC activity at the national level, closely followed by Spain and Germany. The United States has been increasingly following suit, with several individual participants reporting up to 4 OBCs implemented over the last 5 years.

The United Kingdom and CMS in the United States are 2 notable exceptions in terms of OBC activity. In the United Kingdom, after 5-6 OBCs were implemented in the early 2010s, no additional OBC activity was reported through 2015….In the United States, manufacturers, payers, and CMS are expressing greater interest in new contracting models. For example, CMS has been an early proponent of programs aimed at determining coverage for new health technologies through coverage with evidence development. CMS has expressed interest in exploring performance- or value-based payment for pharmaceuticals.

Another paper by Yu et al. (2017) conducts a systematic literature review of publicly available OBCs [or what they call performance-based risk sharing agreements (PBRSAs)–and finds that “26 publicly disclosed PBRSAs were identified. Of these, 16 (62%) were announced or initiated from 2015 to 2017, and 10 (38%) were announced or initiated from 1997 to 2012.”

However, the list of publicly known OBCs greatly understates the true number of OBCs.

The publicly available literature appears to greatly understate the actual level of OBC activity when compared with the activity reported by the interview participants in the past 5 years. For example, in the United States, while the targeted literature review identified only 3 OBC drug schemes in the past 5 years, some interviewed stakeholders reported enacting up to 4 OBCs over the same period (i.e., each of these research participants reported more than the total reported in the literature).

Another study by Goble et al. (2017) found that interviewed payers found that “A total of 51 PBRSAs were active among respondents at the time of the survey.”

Most survey respondents believed that there would be more OBCs over the coming decade, so the benefits and challenges of tying prices to real-world outcomes is likely to stay.


HWR is up

Written By: Jason Shafrin - Oct• 12•17

Hank Stern of InsureBlog hosts this week’s “Pink edition” Health Wonk Review. Check it out.

Also of note this week is that Richard Thaler has the 2017 Nobel prize in economics.  For more on Dr. Thaler’s work, check out the Nobel Prize website.


Written By: Jason Shafrin - Oct• 12•17

The 2017 MacArthur “Genius” Fellows were awarded this week.  One fellow of particular interest to this blog is mathematician and statistician Emmanuel Candès.  The Stanford University professor uses complex mathematical structures to improve the health care system.  As stated on the MacArthur website:

Using an approach that draws on concepts from linear algebra and L1 minimization (a concept of high-dimensional geometry), Candès and colleagues were able to reconstruct high-resolution signals from sparse measurements under specified conditions. In diagnostic healthcare, for example, reducing the number of measurements needed to create high-resolution MRI scans shortens the amount of time patients must remain still in the scanner, an outcome with particularly beneficial implications for children. The ability to process and/or reconstruct audio, visual, and wireless signals from limited data has also led to significant refinements in digital photography, radar imaging, and wireless communications.

But how does Candes technique work?  A Wired article explains how compressing sensing works.

Compressed sensing works something like this: You’ve got a picture — of a kidney, of the president, doesn’t matter. The picture is made of 1 million pixels. In traditional imaging, that’s a million measurements you have to make. In compressed sensing, you measure only a small fraction — say, 100,000 pixels randomly selected from various parts of the image. From that starting point there is a gigantic, effectively infinite number of ways the remaining 900,000 pixels could be filled in.

The key to finding the single correct representation is a notion called sparsity, a mathematical way of describing an image’s complexity, or lack thereof. A picture made up of a few simple, understandable elements — like solid blocks of color or wiggly lines — is sparse; a screenful of random, chaotic dots is not. It turns out that out of all the bazillion possible reconstructions, the simplest, or sparsest, image is almost always the right one or very close to it.

Very exciting insights that we all hope can greatly improve health care for today’s and tomorrow’s patients.

Mid-week Links

Written By: Jason Shafrin - Oct• 10•17

The problem of cutting Medicaid rates

Written By: Jason Shafrin - Oct• 09•17

A new paper by Sharma et al. (2017) finds that Medicaid patients living in states with lower Medicaid reimbursement have more challenges accessing primary care services.

We found that states with higher Medicaid fees had higher probabilities of appointment offers and shorter wait times for Medicaid patients, and lower probabilities of appointment offers and longer wait times for uninsured patients. Appointment offers and wait times for Medicare and privately insured patients were unaffected by Medicaid fees.

The authors also find that access differentials vary by beneficiary race.  Interesting throughout.