Being a data junkie and always wanting to see the numbers for myself, I decided to look at actual trends in US healthcare expenditures to see where the dollars are actually going. I went to the US Health and Human Services website and downloaded annual expenditures on healthcare from 1960 through 2007.
I often turned to my father for advice. I would ask him, “What’s the right decision to make?” And he would invariably reply, “There’s no right or wrong. There are only consequences.”
By taking the morality out of the equation, my father forced me to focus not on the action itself, but rather on the outcome of the action: Which action would get me to the best overall outcome?
This taught me that actions have consequences. More than that, though, he taught me that since we choose our actions, we control (to a greater or lesser extent) our outcomes. Since the outcomes we get follow from the actions we take, we should then be led to choose those actions that end up benefitting us.
It can get complicated, though. Suppose we’re given the choice of whether or not to eat a big, gooey, glazed donut. Eating the donut will give us pleasure now as we consume it. However, it will also cause angst the next time we want to wear our tight jeans. Or farther down the road, the donut may be the final straw in causing a heart attack, which will not only be traumatic, but also expensive. What do we do?
The US medical cannabis market is currently in its early stages of adoption: the market has gained some penetration, but not enough to warrant adoption by the early majority, that is, more mainstream users. My book, Winning the Hardware-Software Game, describes the technology adoption lifecycle in detail. A brief summary and illustration (Figure 1) of the technology adoption process taken from the book indicates:
[T]he consumption lifecycle of a new innovation entails adoption by four general groups of users: (1) innovators and early adopters, risk takers, who are attracted to novel innovations that offer new and different features and capabilities; (2) the early majority, who are more deliberate in their purchasing decisions, requiring bug-free products whose value has been validated by early adopters; (3) the late majority, a skeptical lot, who demand low prices and large amounts of product support; and finally (4) laggards, the traditionalists, who adopt new innovations only when forced to do so.
Figure 1
By understanding the wants and needs of majority adopters, we can ask: how must the medical cannabis market evolve to become amenable to adoption by more mainstream users?
Our goal is to surmise the wants and needs of more mainstream adopters. We can achieve this, first, by considering how cannabis provides value to those adopters. Once we understand the value proposition, we can then determine how the market will evolve to increase value to users.
In 2018, Americans spent $3.67 Trillion on healthcare, amounting to 19.5% of GDP, up from 5.2% of GDP in 1960. It might not be such a bitter pill if Americans were becoming correspondingly healthier over time. But we’re not. Everyone knows that despite our hefty increases in spending over the decades, we’ve also become heftier ourselves, causing our health to deteriorate.
Essentially, we’re not eating right nor getting enough exercise, which has led us to become fat. And it’s not just the disadvantaged classes who have weight problems. Laziness and bad eating habits pervade society, from the rich (about 1/3 are obese) to the poor (almost half are obese). In fact, our bad habits (poor diet, inactivity, and smoking) contribute to 8 of the 10 top causes of death (2/3 of all deaths) in the US (see Figure 1).
Figure 1
What’s so tough about being healthy that so many of us have so much trouble with it?
In 2005, a physician-scientist research pioneer, John Ioannides, published what has come to be a widely circulated paper, “Why Most Published Research Findings Are False.” The replication crisis we’re having in science embodies the concern voiced by Mr. Ioannides. Yet, despite much evidence that so many studies are not valid, scientific professionals continue to rely almost exclusively on study results when deciding on best practices.
So many studies are flawed. As a simple example, please take my survey by answering the following question:
Over the past 12 months, how many times have you visited a doctor?
Take as much time as you need to answer the question…
Got your answer?
Okay, now let me ask you a few questions about the number of visits you just “reported” for my study.
First, to answer my question, did you just think back in your mind, or did you actually check your records? Most people will probably come up with a “good estimate” based on what they can quickly recall. Relatively few people will make the effort to reference records to help them come up with a more accurate estimate.
As for what we remember, researchers continue to discover new ways in which our memories paint an inaccurate portrait of “the truth” (to the extent the truth exists). For example, the telescoping effect is a common cognitive bias affecting our memory, where we tend “to displace recent events backward in time and remote events forward in time, so that recent events appear more remote, and remote events, more recent.” The telescoping effect is just one of many different cognitive biases – Wikipedia lists 42 different cognitive biases that affect our memories – any one of which may cause your reported number of visits to the doctor over the past 12 months to be more or less than the “true” number.
Second, what types of providers did you include in your estimate? Did you include any visits to a dentist, nurse practitioner, therapist, optician, optometrist, pharmacist, herbalist, or other allopathic provider? Different people will have different interpretations of what’s included in the category “doctor.”
The configuration of our current healthcare system is a product of its history: It has evolved into its current form as a consequence of two primary sets of factors. First, the healthcare system has evolved into its current form due to historical laws and regulations that have generally catered to the interests of healthcare payers and providers. And second, the system has evolved based on self-serving actions taken by payers, providers, and patients in response to those laws and regulations.
The current healthcare system is extremely convoluted, in large part because laws have been established to achieve an “unnatural” – inorganic – outcome: the cross-subsidization of healthcare for the old, sick, and poor by the young, healthy, and rich. Under a system of cross-subsidization, some groups (the young, healthy, and rich) pay more than their “fair share” of the total costs to support others (the old, sick, and poor) who pay less than their “fair share.” What is problematic with the current system is not the use of cross-subsidization per se. Many systems do fine with reasonable amounts of cross-subsidization between payer groups. Rather, the problem is the extent to which the level of cross-subsidization has evolved. Over time, the lower cost groups in our society – the young, healthy and rich – have been forced to take on increasing portions of the costs incurred by higher costs groups.
A victim of the increasing extent of cross-subsidization in the current system is any meaningful relationship between risk and payoff for different sets of participants in the system. The loss of this risk-reward relationship has created massive moral hazard situations for parties in the system. More specifically, people don’t bear the full healthcare costs of their risky – unhealthy – lifestyles. As such, they choose to take on more risks and unhealthy behaviors than they would if they had to pay the full costs of doing so. Our unhealthy populations simply offload their higher associated healthcare costs onto the rest of society. This has created a vicious cycle: As people have become less healthy, healthcare costs have increased. But costlier groups haven’t been able to afford to pay the costs they have incurred, so the degree of cross-subsidization has further increased. In turn, this has further decreased the portion of costs paid for by the unhealthy, which has led them to make even poorer choices.
This analysis considers how the US healthcare system would change if we were to transition from the current multi-payer system to a single-payer system. The analysis first presents facts that will be important in considering what a single-payer system might look like. Then, given these facts, the analysis considers specific issues about the transition.
Behavior, genes, environment, and healthcare services are the four factors that Impact people’s risks of premature death (Kaiser Family Foundation) (see Figure 1).
Figure 1
(i) Behavior: 40%
From Kaiser Family Foundation: “Health behaviors, such as smoking and diet and exercise, are the most important determinants of premature death.”
According to OECD, “Health at a Glance 2015”
While genetics is a risk factor, only about 5% to 10% of all cancers are inherited. Modifiable risk factors such as smoking, obesity, lack of exercise and excess sun exposure, as well as environmental exposures, explain up to 90-95% of all cancer cases.
(ii) Genes: 30%
(iii) Social and Environment: 20%
Figure 2 (from Kaiser Family Foundation) displays specific social and environment factors contributing to health.
Figure 2
More from the OECD report:
Recent analysis shows that, although overall spending on social services and health care in the United States is comparable to other Western countries, the United States disproportionately spends less on social services and more on health care.
(iv) Health Care: 10%
A recent article in the NYT, “E-Records Get a Big Endorsement” by Steve Lohr, describes how hospitals are seeking a competitive edge” by offering subsidies to doctors to join the hospitals’ digital networks:
Suppose a patient damages his knee. He goes to see an Orthopedic Surgeon. The surgeon conducts some tests and concludes that the patient has torn his meniscus and needs arthroscopic surgery to fix it (see Figure 1)
Figure 1
Source:http://www.newhealthguide.org/Meniscus-Surgery-Recovery-Time.html
After informing the patient of this, the patient then asks the surgeon, “How much will this surgery cost me?”
The surgeon replies to the patient’s question with something akin to, “I have no idea,” or “I can’t tell you.”
That simple statement goes a long way towards killing the patient’s trust of the doctor. And without trust, patients are less likely to comply with the doctor’s recommendations, which, in turns leads to worse patient outcomes, less satisfied patients, fewer patient referrals, and more billing disputes.
And all this happens due to a miscommunication between the surgeon and the patient.
A recent article in the NYT, “Weighty Choices, in Patients’ Hands” by Laura Landro, discussed the difficult choices patients face in making healthcare decisions, as treatment options become more complex. Due to the overwhelming nature of the information and the inability of physicians to provide patients with the ins and outs of all their options, some medical services providers are providing patients with “coaches” to help educate them about the upsides and downsides of all the patients’ choices and to help guide them in preparing relevant questions for the patients’ doctors. In the excerpt that follows, I’ve highlighted in blue the results reported in the article for this new patient education process.
A 1999 study, “To Err Is Human: Building a Safer Health System” by the Institute of Medicine reports “that that at least 44,000 Americans die each year as a result of medical errors,” and “the number may be as high as 98,000…Total national costs (lost income, lost household production, disability and health care costs) of preventable adverse events (medical errors resulting in injury) are estimated to be between $17 billion and $29 billion, of which health care costs represent over one-half.”
A May 2009 study, “To Err is Human – To Delay is Deadly: Ten years later, a million lives lost, billions of dollars wasted” by the Safe Patient Project laments that since the 1999 report was issued, nothing has changed, and “we believe that preventable medical harm still accounts for more than 100,000 deaths each year – a million lives over the past decade.”
Over the past several months there has been an absolute deluge of articles in the media regarding how out-of-hand US healthcare spending has become. Many are convinced that the provision of healthcare involves various unique situations, which make the private markets unable to efficiently provide healthcare. For example, Jim Heskett of the Harvard Business School presents 10 reasons why participants in the healthcare market may be "less rational" than participants in other markets:
Based on the incentives facing different players in the US medical cannabis market, I believe the market will not achieve mainstream adoption unless or until the US overcomes several hurdles: (i) the classification of cannabis as a Schedule I drug, (ii) cannabis’s lack of FDA approval, (iii) the lack of clear information about and trust in cannabis as a safe and medically efficacious product, and (iv) the social disapproval of cannabis use by a significant portion of society.
Let’s start by examining the incentives facing the main participants in the medical cannabis market.
Everyone knows that America has a weight problem. According to one source, “More than two-thirds of U.S. adults are overweight or obese.” Everyone also knows that all you have to do to lose weight is to consume fewer calories than you burn off. So why can’t so many people just do it?
A copy of the full analysis can be downloaded by clicking on the link at the bottom of this blog entry.
The healthcare industry has been undergoing a massive state of transition recently, especially since the American Recovery and Reinvestment Act of 2009 (ARRA) was signed into law in 2009, and the Affordable Care Act (ACA) (Obamacare) was signed into law in 2010.
The ARRA required healthcare providers to adopt electronic medical records in order to continue to receive current levels of Federal reimbursements. More specifically, “Federal Mandates for Healthcare: Digital Record-Keeping Will Be Required of Public and Private Healthcare Providers” states:
As of January 1, 2014, all public and private healthcare providers and other eligible professionals (EP) must have adopted and demonstrated “meaningful use” of electronic medical records (EMR) in order to maintain their existing Medicaid and Medicare reimbursement levels.
A copy of the full analysis can be downloaded by clicking on the link at the bottom of this blog entry.
In Part 1 of this analysis, I described the main issues facing Doctors: (i) decreasing reimbursements, (ii) divergent reimbursements by location, (iii) transition from fee-for-service to pay-for-performance, (iv) increasing costs, and (v) increasing regulations.
In this part of the analysis, Part 2, I describe the main isssues facing Patients and Payers.
In the last part of the analysis, Part 3, I will discuss the tensions (conflicts) between the different sets of players that are engendered by the different incentives each player faces.
A copy of the full analysis can be downloaded by clicking on the link at the bottom of this blog entry.
In Part 1 of this analysis, I described the main issues facing Doctors.
In Part 2 of the analysis, I described the main isssues facing Patients and Payers.
In this last part of the analysis, Part 3, I discuss the tensions (conflicts) between the different sets of players that are engendered by the different incentives each player faces.
I was thinking about the various situations and implications associated with the current healthcare system and some of the changes that have been proposed. I wanted to get a better handle on what, exactly, each of the issues means in terms of dollars spent by people paying into the healthcare system. To this end, I created a little numerical model that lets me play with the different scenarios to see what they each mean in dollar terms.
The assumptions I’m making that form the general layout of the model are:
A copy of the full analysis can be downloaded by clicking on the link at the bottom of this blog entry.
Infectious diseases are the second leading cause of death worldwide. Since their discovery in the 1940s, antibiotics have been the primary treatment for infectious diseases. However, over time, many diseases have become resistant to the antibiotics that have been used to treat them, causing tens of billions of dollars in added treatment costs and millions of deaths globally.
This analysis analyzes the factors (game) involved in (i) the supply and use of antibiotics to treat disease, and (ii) the eventual resistance of many of these diseases to the use of antibiotics.
A copy of the full analysis can be downloaded by clicking on the link at the bottom of this blog entry.
In Part 1 of this analysis, I provided a brief description of the Microbial Resistance Game, and I described the various pathways of microbial resistance to antibiotics.
In this section I describe the players involved in the Antimicrobial Resistance Game (as illustrated in Figure 1), together with their incentives.
Strategic Maneuvering in Dynamic Markets
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