3 Health Policy Predictions To Watch For in 2017

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Back in December of last year we ran a webinar titled “So What’s Next for the ACA?” Then, as now, there was a lot of “sky is falling” commentary around health policy and how the current government would completely dismantle the health safety net for millions.

Our webinar had two goals. The first was to place the Patient Protection and Affordable Care Act (ACA) within the context of broader healthcare industry trends. The second was to highlight the aspects of the ACA that would realistically change with the current administration.

We also made three predictions based on the emerging healthcare industry trends.

  1. Repeal & Replace would quietly evolve into merely an amendment of the ACA
  2. Emergence of regions with a market-based single payer
  3. Emergence of value-based reimbursement as the standard

It’s early days yet, but its worthwhile to see how well our predictions are holding up.

Health Policy That Amends, Not Replaces ACA

There have been three major healthcare bills proposed from the GOP congress since the beginning of the year. The first was the Patient Freedom Act, introduced to the senate by Senators Bill Cassidy and Susan Collins on January 23. The second was the Obamacare Replacement Act, introduced to the Senate by Rand Paul a day later. The third was the American Health Care Act (AHCA), introduced to the House by Representative Diane Black on March 20 and passed in a hurry by the House on May 4 after failing a previous vote.

All three are touted by their authors and supporters as ACA replacement bills. How accurate is that? Let’s briefly examine all three.

Patient Freedom Act Highlights

-Allows states who choose to continue with the ACA to do so (including Medicaid expansion and the federal exchanges), and maintains much of the ACA’s infrastructure to enable that

-The “replacement” piece of the legislation revolves largely around allowing states to develop their own health insurance alternatives without federal assistance

-The bill’s authors explained their “Obamacare-lite” approach as a practical measure to ensure bipartisan support (that is no longer necessary).

Obamacare Replacement Act

-Repeals virtually all of the ACA’s major mandates such as the individual mandate, employer mandate, essential health benefits, and more

-It leaves in place the ACA’s subsidies for purchasing insurance via federal exchange as well as Medicaid expansion

-Tax credits up to $5000 for individuals who contribute to a Health Savings Account (HSA)

-supplements the current, uncapped exclusion on employer-provided health insurance with a new, uncapped deduction for individual-provided health insurance

American Health Care Act

-Retains key ACA provisions such as

  • Prohibiting insurance from denying coverage for a pre-existing problem
  • Children can stay on parent’s plans until age 26
  • Insurance exchanges stay in place
  • Insurance premium subsidies, though at roughly 60% of the level of the ACA

-Helps people making below certain income levels purchase insurance on their own through refundable tax credits that scale based on age

-Like Rand Paul’s proposal, eliminates the mandates put in place by the ACA

-Federal payments to state Medicaid programs switches to capitated model, although states also have the option for block grants for non-expansion Medicaid participants

-States have the option to impose a Medicaid work requirement for anyone who is not pregnant, elderly, or disabled.

-Tax incentives for HSA’s

You can find a more detailed, point-by-point comparison of the proposals here.

Big To-Do About Small Philosophical Differences

A true repeal and replace would not use the ACA’s core infrastructure as a starting point – it would start from where things were before ACA. We stated this in our webinar and it bears repeating: these proposals are all merely a step further in the same direction that the ACA was already moving. Remember, before it was Obamacare, the core concepts of the ACA were implemented by GOP governor Mitt Romney in Massachusetts. Calling any of this “repeal and replace” should be seen as nothing more than pandering.

These proposals come across as unempathetic.  Particularly the AHCA after the first Congressional Budget Office impact report.  With so many news outlets screaming bloody murder, it’s easy to get lost in the emotion.  Health is such a deeply personal topic, and unlike most hot topic issues, actually effects everyone.

However, it’s important to note that the ACA is attempting to be all things for everyone. A social safety net that subsidizes access to the most vulnerable, and a market-based solution that shifts financial risk from payers/employers to providers by incentivizing capitation and value-based reimbursement. The GOP proposals appear unpalatable to the vast majority involved.  However, there is nothing to turn back to.  The ACA does not provide a financially sustainable solution to the aspects of healthcare that are badly broken.  Let’s not forget that the country is in the middle of diabetes, obesity, and opiate addiction epidemics that collectively are decreasing our life expectancy.  Living in America has become a literally toxic experience for all but the wealthiest. Neither the ACA nor any of these proposals explicitly address any of these problems.

On the other hand, the Senate and House will eventually come up with a version of AHCA they both like.  And it will probably be something that is budget positive without creating much value to providers or healthcare users. So we will end up with a Frankenstein’s monster version of the ACA with Medicaid on financial life support. That lays the groundwork for our second prediction

Market-based Single Payer

The most distinctive feature of the federal insurance exchanges nearly 4 years along is the lack of choice. There are 7 states in which participants have either only one private insurance option or none at all. There are 4 more where a majority of regions face the same lack of options. These are areas where we are already seeing government-subsidized single private payer options.

health policy of ACA


The current GOP government seems to have two major philosophies for controlling cost

  1. Capitation and block grants for state Medicaid programs to make providers share in financial risk
  2. Health policy that pushes more financial risk onto Medicaid recipients

Most actors in the healthcare industry have already accepted value-based payment as the near future.  Nearly 58% of all payers today have value-based reimbursement protocols in place.  That’s up 10% from 2014. Capitation and other fixed-reimbursement models force a focus on value-based care by putting the provider financially at risk for care delivery costs in excess of the fixed, per-capita payments they receive.

The second philosophy treats places primary responsibility for health outcomes on the patient. This is arguably an unreasonable expectation, given the opacity of health services pricing and heavy stratification of health outcomes by income.

Consolidation – the Road to Private Single Payer Healthcare

In addition to pushing for value-based care, payers have another tool for controlling cost. Consolidation.

Since the late 90’s, we have seen a consistent wave of provider, and payer-provider consolidation.


While provider consolidation is largely around increasing reimbursement margins for physician practices, payer-provider consolidation centers on tighter control of the entire care delivery value chain.

Since the ACA passed into law, roughly 13 million previously uninsured people have entered into the health insurance pool. The majority of this group are high utilizers and were, prior to the ACA, deemed “uninsurable.” Assuming that the final version of the AHCA does not kick tens of millions out of the insurance pool, the few payers who remain on the exchanges have a strong financial incentive to exact even tighter controls on the providers in their networks.

The financial opportunity is huge for any payer who can figure out how to do population health.  The exchanges present a massive captive audience of potential insurance customers.  These are customers who will bear high out-of-pocket costs regardless of income. However, payers who remain on the networks need deep reserves they can dig into, because it will take them a few years still to scale profitable cost control. This is where we will start to see a third type of consolidation accelerate and get us closer to private single payer markets – payer to payer consolidation.

The Department of Justice under Obama took a dim view to mega mergers between large payers.  By contrast, the market philosophy of the current administration might be more friendly. I would even argue that payer to payer consolidation is part of the natural long term strategy behind the AHCA. If that is correct, it would make sense for these GOP plans to all use the core infrastructure of the ACA as a way to gradually push Medicaid recipients onto private insurance plans.

Value-Based Reimbursement as the Standard

As stated above, roughly 58% of payers currently use value-based payments as part of their reimbursement mix. As the payer-provider and payer-payer markets consolidate even more, the mega providers will have enough market power to push virtually all financial risk onto providers.  Beyond at-risk reimbursement, we will likely start to see the same kind of punitive health policy placed on providers who cannot control costs as states advised by Seema Verma place on Medicaid recipients.

Volume-based reimbursement, particularly for areas like primary and acute care with high downstream costs, will likely disappear completely over the next decade.

There is still a long way to go before Congress passes a final version of the AHCA. Much of the GOP’s philosophical agenda is contingent upon maintaining a complete government mandate beyond the 2018 midterm election. But the shifts we are already seeing around consolidation and adoption of value-based reimbursement are independent of possible legislation.

Stay with us – we’ll keep you updated as we see the healthcare market and health policy progress.

Is There A Silver Bullet to Fixing Patient Engagement?

Fashion and makeup retailers tell women they are too old and ugly. Beer sellers and truck sellers tell men they aren’t manly enough.

Why? Because it works

We have an obesity crisis, yet doctors are telling patients they are too big to absolutely no effect.  Why?  Because the biggest issue with low rates of behavior change in patients isn’t non-compliance by patients.  It’s the unwillingness of providers to commit to innovating how they engage with patients.

Right now, most hospitals that do “innovation” make a big fuss about how digital health is the future, and maybe throw money at an innovation center or get grants for research. And make big press around the products that come out of these efforts. The problem is that they aren’t prepared to operationalize their successful pilots because their organization has no channels for integrating these innovations into regular practice beyond a one-off basis.

This is because innovation isn’t building workplaces that looks like Twitter headquarters – it isn’t disruption, it isn’t necessarily upheaval and displacement.  It’s very simply taking principles and practices that are commonplace in one context, and applying them in a new context. That might result in disruption, or it might result in a smooth transition.  Or better yet improve the lives of patients.

One big problem is that the bureaucracy in the hospital world is what insulates the day to day business of care practice from innovations introduced by startups, industry outsiders, individual contributors or c-level forward thinkers. Bureaucracies built to handle regulatory compliance, reduce liability risk, and negotiate billing rates with payers are not built for constantly changing business practices.

Another other big problem is elitism – the thinking that medical practice is somehow different as a business than retail or every other industry. That top down interaction between doctors and patients is the only right way to engage, and that patients themselves are not qualified to have a say in how they are diagnosed or treated.  But obviously if “doctor knows best” were true, obesity wouldn’t be so bad that it is considered a national security threat.

The fact is, many of the communities who need the most support in addressing chronic disease also have a historical distrust of the healthcare system due to years of marginalization, experimentation, and downright lack of basic respect.  The doctor-patient relationship is badly broken and needs to be repaired first before anything else.  Bureaucracy and elitism together prevent us from rapidly incorporating lessons from other industries into how this relationship can be more effectively managed.

So how do we change?

1. Two way communication and information sharing

We need to move away from one way communication between doctor and patient.  Simply ignoring input from the patient if you as a doctor don’t trust the info you are getting from patients can be problematic, if understandable at times.  Ignoring it as a health system means you are systematically excluding your patients from their own care, treating them as objects rather than people.  If as a system, you are getting bad data from your patients, you need to innovate in information gathering so that you can improve the quality of the patient-doctor dialogue.

Additionally, providing patients with the means of getting more involved has been shown to reduce passivity in self-management.  It can be as simple as open access scheduling, or establishing channels where patients can within minutes get a human response to questions that they have.

2. Create space for experimenting

Don’t just talk about change.  Put skin in the game and fund a pilot.  If you don’t have the money, find partners, apply for grants.  Nearly 40% of hospitals operated in the red last year, and fee-for-service is dying.  Waiting for the healthcare market at large to figure out processes for you to follow is a dangerous game to play if you are just treading water and are short on ideas.  Invest whatever you able to in trying out new things, and exploring alternative care delivery and business models.  It doesn’t have to be organizational culture change – even just iterating on solving simple problems that create financial pain or impact patient outcomes can lead to positive progress.

It’s looking very likely that the memo for the next four years at least from the Capitol and White House is to accelerate value-based care. Financial risk will be pushed more aggressively onto providers and patients than with the ACA, which means that providers and patients will need to find more effective ways of working together to manage chronic disease.

Reimbursement for Chronic Care Management

A patient with a chronic disease such as Type 2 Diabetes typically receives regular specialized care from up to 7 different providers each year. Emergency Room visits for this type of patient are more than 100% higher than baseline, while utilization rates for the 1 in 4 adults in the US with more than one chronic disease are even higher.

Needless to say, care coordination can be a nightmare for both patient and provider as even primary care providers lack the proper financial incentives for helping a patient manage their personal network of providers they see. While the Centers for Medicare and Medicaid Services (CMS) established the chronic care management billing code 99490 in January of 2015 to support reimbursement of previously unpaid services, the development of programs to take advantage of this new revenue stream by hospitals has been slow and uneven.

The central issue lies in the four C’s of healthcare finance – rising costs, constrained capital/cash, and tightening controls. In an environment where systemic changes are needed in both healthcare finance and how chronic conditions are managed, the lack of clear direction on how to make change beyond increasing the financial risk borne by providers. As a result, providers are on their own in figuring out how to make the necessary changes to comply with quality measures set by CMS to ensure better cost-control.

Opportunities For Change

Most of the transition towards value-based care has been push-based, relying on sweeping pieces of legislation that alters the financial landscape. The intent of CPT code 99490 is to provide opportunity for more pull-based opportunities for change. It requires Providers to spend at least 20 minutes per month with Medicare patients who have at least two chronic conditions that are expected to last at least one year or that put the patient as risk of death or decline. Reimbursement runs at $43 per patient per month.

The new CPT code is meant to provide a pull-based incentive for providers to build new business models that incorporate more involved care coordination for high-risk patients beyond just throwing a patient file over a wall to the next provider in the referral network. Unfortunately, widespread adoption of these models has been slowed due to a range of concerns from providers, primarily around concerns over increased liability and time management challenges.

It is important to view this hesitance within the context of an industry that is generally slow to innovate or adopt advances that have benefitted other industries. The arguments around the lack of ROI in exploring revenue opportunities through CPT 99490 often assume the use of existing technologies prevalent within healthcare, rather than creatively imagine the use of technologies that other industries (such as retail or sales/marketing) have successfully used to manage one-on-one interactions with customers at scale.

Keys for Moving Forward

The real key to not only driving compelling ROI, but halting the out-of-control growth rate of chronic condition prevalence ultimately lies in providers leveraging modern technology to act as air traffic controller in coordinating care for high-risk patients.

This will require a re-envisioning of the relationship between provider and the patient. And will require a re-imagining of the types of roles that support the operating model of care coordination. We have already seen increasing responsibility handed to mid and lower-level clinicians as cost-saving measures – those same clinical positions can be baked into more longitudinal patient support roles.

Real Innovation

Healthcare can take inspiration from a myriad of forward-thinking industries in implementing customer relationship management technologies alongside artificial intelligence and machine learning in order to manage relationship for patients at scale. These technologies can help make significant reductions in the amount of cash and capital required to meet the heightened level of financial and outcomes control demanded by value-based care reimbursement schemes.

Furthermore, we also need to re-imagine the role of the provider within the broader social and economic environment that shapes health outcomes. The non-clinical support (housing, legal services, healthy food, fitness) that high-risk patients need is currently beyond the scope of the modern day provider. However, the utilization rates and costs faced by providers are heavily influenced by non-clinical risk factors.

Again, here is an opportunity to think creatively about how technology can be leveraged to support the revenue opportunities presented by CPT 99490. While coordinating non-clinical resources may not directly be reimbursable, providers can place themselves at the center of resource networks and leverage network effects to more effectively keep high-risk patients engaged in preventive care programs that do drive hospital revenue.

The objection of providers to change is understandable. The legal landscape of healthcare is very uncertain, and yet they find themselves bearing an increasing level of financial risk. Making a wrong investment might not just be costly, but can lead to insolvency. But this is a reason to aggressively look to other industries – particularly retail-oriented ones – to find lessons in the use of technology to manage patient-provider relationships. CPT 99490 presents a strong opportunity to do this from the chronic condition management perspective.

A Model of More Effective Chronic Condition Management

At ProjectVision, we talk a lot about two elements that are essential to building condition management programs and interventions that not only retain patients, but keep them actively engaged in behavior change:

  • Personalization
  • Quantifying environmental barriers to behavior change

Because of the difficulty in gathering complete behavioral data, many chronic condition management programs focus “personalization” based on clinical risk – A1C level, BMI, blood pressure, etc. Using historic demographic data, they can predict with reasonable accuracy when a patient will shift from Pre-Diabetes to full Type 2 Diabetes.

However, clinical risk doesn’t tell us the “why” in the same way that behavior risk does. Focusing on clinical risk also pushes providers into a mental trap of treating patients with the same clinical risk and demographic characteristics as monolithic. Studies have shown that not more than 20% of patients who successfully lose weight in a structured program are able to maintain that weight loss in the long term.

The unsatisfactory long term outcomes of current condition management programs points to three key issues with the current models of chronic condition management:

  • The program is disconnected from the social, cultural, and environmental reality for most of the patients
  • Behavior risk stratification is not used to further tailor the program to each patient’s unique psychological needs
  • The environmental barriers faced by patients are beyond the scope of clinicians and care providers

So let’s dive deeper into each of these three issues:

Programs Disconnected From Patient Reality

In early November, I presented a webinar centered on more effectively engaging low-income and minority patients in health behavior change. I started that presentation by analyzing the rapidly growing amount of money retailers were spending on digital ads, making the point that in an industry where failing to understand your customers deeply means going out of business, companies make a big investment in tools to help them understand and speak directly to their customers.

A big problem in healthcare is that biases about certain patient groups – the overweight, the poor, the non-white – are allowed to drive program development without being acknowledged and confronted. Failures to recruit patients in adequate numbers or keeping patients engaged in programs often comes down to incongruent messaging on the part of providers. For example, using pictures of thin, white women doing yoga when advertising a condition management program to mothers of color in lower-income communities with high obesity prevalence will not create the necessary connection with those we are trying to reach.


Programs that don’t acknowledge and build behavior change around existing deep structures within a community can expect to continue to get unimpressive results. Making this change requires letting go of assumptions about how people in certain communities think and feel, and instead, relying on observations from actual data gathering.

Behavior stratification

Simply put, a good program is responsive to psychological variance within the participating patient population. In an inpatient setting, the frequency and intensity of care is based on the clinical risk faced by the patient. Good chronic condition programs should be able to similarly moderate the level of care provided based on the behavioral risk faced by each patient. We need to move away from one-size-fits-all models of intervention. There are many different paths a person can take from being healthy to becoming diabetic.



Effective Interventions Are More Than Just Clinical

We are shaped by our environment, and we generally take the path of least resistance when making day to day decisions. If a patient lives in a healthy environment – where they have walkable access to healthy food options that they can afford, with clean air, low crime, and easy access to recreation – they are more likely to be healthy. Obesity rate has a very strong negative correlation with income.

By the same token, it’s not within a hospital’s scope to provide adequate healthy food options in a food desert, or job resources for unemployed males in high crime neighborhoods, or for addressing a myriad of other social determinants of health that are not strictly clinical.

In order to be more effective, chronic condition programs run by clinicians need to engage with non-clinical resources in direct partnership. They need to work in concert with food banks, legal services, community health programs like the YMCA, and others to properly address the environmental issues that are causing their patients to fail in more traditional programs.

This more networked approach helps address the two key issues above around being disconnected from the patients’ reality and lacking true behavior stratification. If we understand what each patient’s personal goals are as well as their unique barriers, we can better understand the norms that shape their life and the specific type of support they need to get the most out of a clinical behavior change program. By partnering with non-clinical resources, we can now start actually tailoring the services around those unique needs in a scalable fashion.

By building networks of resources to support patients, we can start leveraging network effects to exponentially increase the value of condition management programs to patients as more resources and more patients become part of the network. You start to have opportunities to leverage past participants as peer advocates as well as your non-clinical partners to bring in billable, reimbursable patient cases.

Bringing Things Together

Current condition management programs have long-term success rates that are anything but impressive. Given the cost concerns of CMS, it is imperative that we aggressively identify new models that can more reliably support behavior change.

Successful new models will address implicit bias and involving high-risk patients more directly in care planning, focus data collection on behavioral risk stratification, and build close partnerships with non-clinical resources.

The Irrelevance of Life Expectancy, Part 2

I previously discussed why life expectancy isn’t a good measure of the quality of a nation’s healthcare system. In spite of numerous economic indexes that focus on it, life expectancy is also a rather poor proxy for quality of life. There is a persistent narrative that Japan, Western Europe, and the Scandanavian countries, due to high per capita income, top of the charts lifespans, and asset ownership rates must be the “happiest” people in the world, with the highest quality of life. While it is understandable that people who create these indexes will be biased towards considerations that make their own countries or cultures look the best, these indexes are also used to defend or promote public policy decisions based on specific cultural norms. To those like me who are proponents of health-centered public policy, Quality of Life indices that ignore the daily health experience are more popularity contests than useful measures.

Specifically looking at indexes such as the Economist’s Where-to-be-born index, we can see that although there are compelling normative variables used – such as gender equality, political freedoms, and corruption – few of the variables directly address the actual experience of happiness. For example, focusing on high level statistics such as gender equality (which is defined very narrowly as the number of women who hold elected seats in legislature) it ignores the actual daily experiences of sexism that still occur even when women are nominally awarded seats at the table.  Further, all of these indices exclude qualitative data directly from the citizens of the countries being measured.  Given that national bodies like the federal government and supra-national bodies like the WHO and UN set spending priorities based on these metrics, not including data points generated from the people themselves misses a huge part of the picture of public health.

Some questions that are left unanswered by using only the Western normative criteria for measuring quality of life:
1) What is the marginal cost of keeping a citizen alive each year beyond retirement age?
2) What is the rate of drug or alcohol addiction?
3) What is the suicide rate?
4) What is the rate of death from preventable chronic disease?
5) What portion of the population believes they require medication for normal daily functioning?
6) What is the level of air and water pollution? What types of pollutants are present in food and water consumed?
7) How sustainable is the current level of energy consumption?
8) What is the prevalence of chronic mental health issues such as depression, anxiety, or schizophrenia?
9) What level of tolerance do people have for others who have different values or religion than themselves?
10) How much do citizens earn in income relative to the value they produce?
11) How much time do citizens spend at work vs with their family or friends?  How much time would they prefer to spend with either?
12) How much time is spent on a computer or smartphone per day?
13) In what direction and speed are each of the above elements trending?

The questions above focus more closely on how citizens relate to the world around them – their economy, their medical system, their neighbors, and themselves. They offer a much more honest look at the true level of satisfaction the average citizen extracts from their daily life experience

The fundamental challenge here is the question who is better off?
A) Person A: Makes $80k/year, will live to 83, is chronically depressed, requires copious amounts of alcohol (or Facebook, or porn, choose your addiction) and painkillers to get through the day, overweight with arthritis in the knees, spends 10 hours per day in front of a computer or smartphone, lives in Sweden
B) Person B: Makes $30k/year, will live to 77, surfs everyday, drinks minimally, babysits their grandchildren several days per week, lives in Brazil

According to most normative measures, Person A is considered to be better off simply because the normative values of Sweden are preferred over that of Brazil. However, physically and mentally, Person B is clearly better off. From a policy perspective, Person B has the much better daily life experience, and such a daily life experience is clearly more economically sustainable in the long term than that of Person A – especially when you consider that birthrates in many of the countries at the top of indexes like the Where-to-be-born index are below replacement.

An additional point that should not be forgotten is how high levels of inequality can paint a picture that is rosier than reality if metrics focus on average results, rather than median or mode.  For example, in the US, the prevalence of obesity for people in the bottom quintile of income is 15% higher than that of people in the highest quintile.  This 15% difference translates into a difference of tens of millions of dollars worth of care consumed, a much higher rate of hospital utilization, and significantly worse overall health outcomes.  For many communities within the US, patients would likely receive higher quality care and better health outcomes if they lived in Cuba.  Likewise for a country rated poorly on the standard quality of life scales – if you are born to a rich family in Zimbabwe, your quality of life and health outcomes will resemble those of someone born in Sweden more than a fellow Zimbabwean born into a poor family.

Some alternative measures to the normative Quality of Life index include the the Happy Planet Index, which measures the average quality of life in a nation based on Experienced well being (qualitative polling), life expectancy, and ecological footprint. While again, life expectancy is not a desireable variable to use, at least the HPI heavily focuses its methodology on how citizens relate to the world around them, rather than on easily doctored normative metrics like unemployment (are we using U3, U5, or U6?), “political freedoms”, or corruption (is lobbying post-Citizen’s United not merely a legalized form of corruption?). More importantly, the New Economics Foundation – makers of HPI – acknowledge that from a policy perspective, HPI should be used in conjunction with other measures such as “economic performance and environmental pressure.”

Ultimately, it is important to move away from normative measures of quality of life that merely reinfornce our cultural biases. Doing so will allow us to take a critical look at the serious stresses that our current economic habits place on our overall mental and physical health. Pretending that a place is paradise or even merely possesses superior public policy/culture simply because life expectancy and incomes are higher than anywhere else is a very dangerous delusion.

The Irrelevance of Life Expectancy, Part 1

There are a number of points of view that argue that life expectancy is not the best total outcome to measure effectiveness. While I agree in principle, I disagree with the arguments presented. Generally, the argument against using life expectancy (or infant mortality) comes down to the fact that they don’t measure outcomes when interacting directly with the care system. In other words, if I mortally injure myself shooting off fireworks on July 4th and die before paramedics can treat me, they argue that my premature death should not be counted against the healthcare system.

Avik Roy’s piece “The Myth of Americans’ Poor Life Expectancy” expands upon this point, and even includes a counterpoint – that the US has the highest cancer 5-year survival rate in the world.



In certain situations, they have a point. Dangerous irresponsibility or absurd misfortune are not the responsibility of care providers to mitigate. And looking from purely a talent perspective, the US is hard to beat when it comes to surviving an exotic or life-threatening condition.

Conversely, what the data tells us is something that is already widely discussed – that the US healthcare system is a misnomer. It is a reactive, “sickcare” system that is rather ineffective at preventive screening and intervention, and relies heavily on surgery and expensive invasive therapy to stop issues after they have become huge problems.

As a consumer of healthcare, it is not a reassuring argument to say that my stroke or heart attack survival rate is much higher in the US than anywhere else. Congenital heart problems aside, a heart attack for a young person represents a massive failure of the primary care system. That I can pay exorbitant healthcare insurance premiums for decades, only seeing a care provider maybe once every one or two years while cardiovascular disease slowly kills me from the inside, should be a signal that the reactive way of practicing medicine that dominates care delivery in the US is broken. As a consumer of healthcare, I would rather have a system that is effective at early detection and intervention of preventable diseases than one that relies on the heroics of clinicians to save my life at the brink.

Instead of measuring by life expectancy, we can measure by Type 2 Diabetes prevalence, Hyptertension prevalence, Cardiovascular Disease deaths, or Obesity Rate. All of these issues generally result in increased contact with the medical system over time.




Next to other OECD nations, the US obesity rate compares even worse than its relative life expectancy rate. Even going back to the cancer survival rate argument, studies have shown that certain types of cancers such as esophagus, colorectal, gall bladder, pancreatic, prostate, post menopausal breast, non-Hodgkin’s lymphoma, and leukemia all have significant positive associations with obesity.

Looking at Cuba – a nominally poor country that nonetheless has an average life expectancy just one year less than that of the US – we can see to what extent our approach to healthcare is poorly designed.

Recognizing that it could not afford to be reactive in health management, Cuba focused over the past four decades on building out infrastructure for multi-specialty community based clinics in order to deliver proactive preventive care services to the entire population. There are focused efforts on gathering population health data for responsive deployment of preventive care resources around issues such as smoking cessation, hypertension, or allergies.

Perhaps the resistance to acknowledging our systemic failures comes from a fear that the only answer is socialized medicine. But a debate on socialized medicine focuses too much on the wrong issue – the political philosophy – and not enough on maximizing the overall quality of the healthcare product. In reality, we need to focus on identifying the best way to reduce the cost and prevalence of preventable conditions. The answer should have nothing to do with ideology.

Guns are a Red Herring in the Growing Frequency of Mass Shooting Events

The mass shooting at the Inland Regional Center in San Bernardino, CA on December 1 was the 355th mass shooting of the year, and was preceded by a mass shooting in Savanah, GA earlier in the day.  The usual responses from both gun rights supporters and gun ban supporters have been rolled out, but not much will likely change.  What does make the regular occurrence of such events so alarming is the fact that overall, all types of violent crime have been regularly decreasing over the past 20 years.


In spite of a very steep decline in the overall violent crime rate, we have seen during the same time period an increase in the frequency of mass shootings and active shooter events.  Unwrapping the issue is difficult because different data sources have different definitions of “mass shooting.”  The 355 number cited above comes from a definition of mass shooting as 4 or more people, including the shooter, killed or injured in a single event or related string of events without a cooling off period.  Mother Jones, another source of compiled mass shooting data, defines mass shootings as events in which 4 or more are killed in a shooting event.  Incidents with fewer than 4 deaths are not counted as mass shootings.


While the definitions of mass shooting vary, both sources show a clear upward long term trend in the number of shooting events.  Politicized debate around gun control aside, given the high correlation of mass shootings with shooters who have had prior history of mental illness, it is not immediately clear that an outright ban on guns would actually address the deeper factors behind mass casualty events.

Attacks like the Oklahoma City bombing, 9/11, or Pan Am Flight 103 have all demonstrated that those with a true desire for mass casualty have tools at their disposal that can cause far more carnage than automatic weapons.  There is a distinct possibility that an outright ban on guns – ignoring potential armed resistance by the more hard core gun activists – may unleash upon us an age of suicide bombings in the US, similar to what we see on a regular basis in many parts of the Middle East.

The real issue behind the gun control debate in the United States is that we lack a framework for truly understanding why such events occur with such regularity, and how to prevent them in the future.  One likely culprit is the nearly 20 year ban on the Centers for Disease Control conducting gun violence research.  Ban is perhaps a strong term – Congress has failed to approve CDC funding for any research related to gun violence since 1996, in spite of a 2012 executive order to resume such research in the wake of the Newtown mass shooting.  Given the political climate, it is unlikely that government funded research will resume anytime soon.

The tragedy is that, from a public health perspective, continued research would likely provide a deeper picture of the mental health issues that are manifested in mass shooting events.  Much like preventive care for chronic conditions, mental health services are currently more reactive than proactive.  This allows a large number of citizens fall through the cracks into homelessness, substance abuse, and violence which all are significant contributors to high cost utilization of emergency health services.  We currently have no effective behavioral models that we can use to predict whether a citizen is psychologically ready to commit a mass casualty act.  As a result, each Planned Parenthood clinic attack, each school shooting, or each Oklahoma City bombing comes as a surprise and each year a growing number of citizens are needlessly killed, maimed, or psychologically scarred.

There is an increasing cost associated with our unwillingness to have a non-politicized discussion of how we have gotten to a point where a mass shooting – however defined – has become a normal news event.  That cost goes beyond the immediate casualties, but can be mitigated with the development of new models for mental healthcare that can keep pace with the shifting dynamics of technology and the economy.