Unbiased Analysis of Today's Healthcare Issues

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.


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.


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.

Friday Links

Written By: Jason Shafrin - Dec• 14•17

Plus, please check out the Happy Holiday Health Wonk Review at Workers’ Comp Insider.

Does the value-modifier improve quality and reduce health disparities?

Written By: Jason Shafrin - Dec• 13•17

In short, no.  That is the answer Roberts, Zaslavsky and McWilliams reach in their 2017 paper in Annals.

Some background on the value modifier program.  In 2013, practices with 100 or more eligible clinicians were rewarded just from reporting quality measures. By 2014, however:

Practices with 100 or more clinicians were subject to upward, downward, or neutral performance-based payment adjustments, those with 10 to 99 were subject to upward or neutral—but not downward—adjustments, and those with fewer than 10 were unaffected. In 2015, all practices with 10 or more clinicians were exposed to full VM incentives (both penalties and bonuses). Base payment adjustments ranged from 2% to 2% on the basis of 2014 performance and from 4% to 4% on the basis of 2015 performance, but high-performing practices have received much higher bonuses (for example, rate increases of 16% to 32% in 2016), because the VM’s budget neutrality provision stipulated that penalties for failing to meet reporting requirements be redistributed as bonuses.

Because of the eligibility cut-offs at 10 and 100 clinicians and the staggered role-out of the design, the authors use a regression discontinuity approach based on practices around the 10 and 100 clinician threshold.  They use 2014-15 Medicare claims data to examine three outcomes: (i) inpatient admissions for ambulatory care–sensitive conditions, (ii) Medicare spending per beneficiary, and (iii) all-cause readmissions within 30 days of hospital discharge.  Using this approach, they find that:

…differences in hospitalization for ACSCs, readmissions, Medicare spending, and mortality between practices above the size thresholds and those below (the adjusted discontinuities) were small in 2014 and not statistically significant…size. Analyses of the threshold of 100 or more clinicians that used 2015 data revealed no statistically significant discontinuities associated with a second year of full exposure to the VM.

In short, no effect was found. In addition, they found that risk adjustment was inadequate.  Adding addition risk adjustment factors narrowed differences in performance between high and low performing groups in particular among practices that served a disproportionately disadvantaged population.  While the value modifier is built from good intentions–pay more for high quality, low cost care–in practice, the results are not overwhelming.



How one project will change the way value is measured in healthcare

Written By: Jason Shafrin - Dec• 12•17

That is the title of a recent article in Managed Healthcare Executive on the Innovation and Value Initiative’s new Open-Source Value Project.  The magazine interviewed Mark Linthicum, IVI’s Director of Scientific Communication.  An excerpt is below:

Linthicum: Many healthcare stakeholders are now being asked to make decisions based on value, but few are also given the tools to make those decisions in an evidence-based manner. IVI seeks to solve that problem. The OSVP allows unmatched input by giving diverse stakeholders a seat at the table, especially patients. Future changes to the model and supporting research to advance the underlying methods will all be based on the feedback received from these stakeholders. This process—as well as the open-source nature of the models themselves—incentivizes stakeholders to offer their feedback to ensure that their unique viewpoint is captured in the tool and can be built upon in further iterations.

Do read the whole interview.

U.S. Healthcare Spending

Written By: Jason Shafrin - Dec• 11•17

The CMS Office of the Actuary released their 2016 estimates for U.S. health care spending.  We’re getting close to health care taking up 18% of the economy.

Total nominal US health care spending increased 4.3 percent and reached $3.3 trillion in 2016. Per capita spending on health care increased by $354, reaching $10,348. The share of gross domestic product devoted to health care spending was 17.9 percent in 2016, up from 17.7 percent in 2015….Enrollment trends drove the slowdown in Medicaid and private health insurance spending growth in 2016, while slower per enrollee spending growth influenced Medicare spending. Furthermore, spending for retail prescription drugs slowed, partly as a result of lower spending for drugs used to treat hepatitis C, while slower use and intensity of services drove the slowdown in hospital care and physician and clinical services.

As baby boomers continue to age, expect health care to continue to rise as a share of GDP, at least in the short- to medium-run.


Will MIPS work?

Written By: Jason Shafrin - Dec• 10•17

CMS in the past was on a value-based binge. They aimed to reward physicians based on quality of care (PQRS), based on cost (a component in the value modifier), based on use of EHR (meaningful use bonuses).  However, this imposed a large reporting bonus on physicians, pulling them away from patient care.  To solve the problem, CMS implemented Merit-based Incentive Payment System (MIPS) to consolidate all these value-based reimbursement schemes into one.

Will this new system work?  After reviewing the program, MedPAC was skeptical of MIPS:

MIPS, as designed, is unlikely to clearly identify highvalue or low-value clinicians and hence may be of limited utility for beneficiaries (in selecting high-value clinicians), for clinicians themselves (in understanding their performance and what to do to improve), or for the Medicare program (in adjusting payments based on value)

Specifically, they cite the low reliability of measures due to small patient counts for most measures for any individual physician; the fact that since physicians can select their own measures, comparing across physicians is difficult; budget neutrality rules mean that some physicians could get very high or very low bonus payments in the future.

One paper by Joynt Maddox (2017) looks at participation in MIPS based on previous data found that:

5.0 percent of the 899 practices would have received a performance-based bonus and 7.7 percent a performance-based penalty

Thus, the vast majority of practices would receive no bonus or penalty in practice.

Measuring quality of care is a good thing.  Imposing significant reporting requirements on physicians is not.  Thus, identifying a way to measure and pay for quality is valuable but the data collection burden and overall reliability must be increased to be able to do this.  Another approach–balance billing–would allow high-quality physicians to charge more to Medicare patients, where quality would be defined not by bureaucrats, but by the consumers and patients actually receiving this care.  Letting the market work, just might work.

Webinars for IVI’s Open-Source Value Project

Written By: Jason Shafrin - Dec• 07•17

On November 8th, the Innovation and Value Initiative (IVI) launched a new effort to help redefine the way we measure value in health care: the Open-Source Value Project (OSVP). A first-of-its-kind effort that engages all health care stakeholders in an open process to advance the way we measure value in health care treatments and services, the OSVP is creating flexible, transparent, iterative, and consensus-based modeling platforms for specific diseases. The first model released as part of the OSVP focused on rheumatoid arthritis, and additional models targeting other diseases are planned. For a quick overview of the OSVP, take a look at this a brief whiteboard video.

IVI is actively seeking input from everyone across the health care system ahead of the January 2018 deadline for public feedback. To facilitate widespread participation, IVI is hosting two public webinars next week to provide information and answer questions:

 WEBINAR 1: Measuring the Value of Health Care Treatments: Time for a New Approach

  • Traditional value assessments are often “black boxes” that only account for a single perspective or a single population. The OSVP is designed to better measure value through an iterative and transparent process driven by input from all health care stakeholders. To better understand how the OSVP process works, learn about our first model in rheumatoid arthritis, and find out how to get involved, join us for our upcoming webinar on December 12, 2017 at 4pm EST/1pm PST. Register here.

 WEBINAR 2: Creating Open-Source Models for Value Assessment: A Detailed Discussion of the IVI Rheumatoid Arthritis Model

  • OSVP models are built to be entirely open-source, allowing anyone to customize the tool depending on their own assumptions and understanding of value. Learn more about how the IVI model generates customized information on rheumatoid arthritis treatments and how to apply the information in assessing value in health care on December 14, 2017 at 4pm EST/1pm PST. Register here.

 The first webinar is designed to be an overview of the OSVP and our IVI-RA model for a general audience, whereas the second is intended for a more technical audience and will dive into the details of the model and our modeling approach. Both webinars are free and open to the public.

Health insurance expansion and physician supply

Written By: Jason Shafrin - Dec• 07•17

When new bills pass in Congress or state legislatures that expand health insurance coverage, most researcher look at the demand side effect.  How does the insurance expansion affect the number uninsured?  How does it affect access to care?  How does it affect out of pocket cost?

What is less frequently studied is the supply side effects.  Namely, does expanding insurance coverage increase the number of doctors, nurses, medical assistants and other stuff in the U.S?  This is the question that Chen et al. (2017) examine.  In particular, they look at the re-authorization and expansion of the Children’s Health Insurance Program (CHIP) in 2009 and they test whether the number of pediatricians increase after the CHIP expansion.  They find:

…newly trained pediatricians are 8 percentage points more likely to subspecialize and as much as 17 percentage points more likely to enter private practice after the law passed. There is also suggestive evidence of greater private practice growth in more rural locations. The sharp supply-side changes that we observe indicate that expanding public insurance can have important spillover effects on provider training and practice choices.

Very interesting study.