Minnesota Governor Proposes Single Payer Study
Exciting news from Minnesota: following the recommendation of the state’s healthcare financing task force, Minnesota governor Mark Dayton asked the legislature last week to finance a study of the costs and benefits of a single-payer system.
Minnesota’s political landscape is one of the most promising in the country; the state is highly Democratic, and one of few to have a pro-single payer governor. A supportive executive combined with a Democratic Senate means that passing legislation is, down the road, feasible. All hands are on deck: PNHP Minnesota has also been collecting signatures in support of the study, and the Minnesota Nurses Association has even hired a staff person solely for the purposes of doing outreach and education on single payer!
Activists are optimistic that the governor’s single payer study will be financed, and expect that the results will be available sometime in 2017.
MN Governor Mark Dayton and MNA Director Rose Roach at Medicare’s 50th
How did it happen?
Last year, Dayton announced the creation of a task force on healthcare financing that would advise the state’s elected officials. While this committee was intended to focus on expanding access to care through existing channels – such as Minnesota Care or MNsure – the nurses’ long campaign to get MNA’s Executive Director Rose Roach on the task force paid off: last month, the task force submitted its recommendations, which included the single payer study proposal that the governor adopted.
Senator John Marty, author and lead sponsor of Minnesota’s single payer bill, joined Rose on the task force and also played a key role in this win.
The nurses’ savvy embrace of this opportunity is an instructive example of how local groups can move single payer activists into publicly-appointed roles that influence government.
Congratulations Minnesota!
If not in MN, then where? If not now, then when? Let’s end this mess of rising premiums, unrealistic deductibles, shifting networks, and skyrocketing health care costs! Health care is a basic human right that should be available to all.
I am quite supportive of this study. It will help in the needed decision process for making single payer the way in MN. It has been shown in almost all developed countries that it is very cost efficient and results in higher quality care.
Single payer medical and dental!! Sign me up!!
Will I still get ripped off?? My required
health insurance tripled, 200 to 600, 6500
deductible ,,per month etc. With no claims.
With personal data used
by third parties, govt and business…
I was directed to sign up for Medicaid,
which would be fraudulent for me!!!
Obama Care tripled my require health insurance costs!!
Expected to pay 600/month, 6500 deductible !!
Nonsense! It’s because you now have more coverage than the cheapskate insurance companies were willing to give in the past, until Obama forced them to meet some minimum standards! It has been a god-send for people who previously had no health insurance at all! I know a woman whose husband has lung cancer who would have lost their house by now trying to pay for chemotherapy!
I am proud of our governor for bringing to the forefront what I believe is at the root of the problem in the US healthcare system. Every other western country with a good health system uses a single payer process. When the people in Congress voted to protect insurance and pharmaceutical companies over the welfare of the US citizens was when the Affordable Healthcare act fell apart. Rather than punishing people with higher premiums, why aren’ the insurance and pharmaceuticals held accountable for unethically outrageous amounts? Thank you Governor Dayton!
Minnesota is going to be a leader in the single payer effort. The ACA is keeping us supporting the insurance companies and big pharma. As people affected by these outrageous costs promoted by these industries, we need to educate everyone and promote single payer everywhere. We don’t have to keep funding health care insurance and big pharma. We can stand up and say no. But we have to organize and stand up to them!
OK – First and foremost, the study should not cost a fortune. I am a mathematician, statistician, and nurse. I also spent a decade doing insurance and reinsurance rate-making, reserving and expense reporting. I quite literally wrote the book on why some health care finance mechanisms are great and why others are really bad: “Standard Errors: Our Failing Health Care (Finance) Systems And How To Fix Them”). For a free summary paper, pick up a paper from my website (http://standarderrors.org/WorkingPapers/2012/JSM073111PaperFinalWorkingPaper09262012.pdf). Both these documents explain why a “Medicare for All” plan, or a “national health insurer”, or a “single payer” will save money, not cost money. In fact, a single payer, at the national level, will save hundreds of billions of dollars every year.
Most people simply do not understand the probability theory, mathematics, economics, finance, and statistics that underlie insurance. So here is a crash course. Hopefully, someone who needs this information will end up reading this, and the Minnesota study will get done a lot faster and at a far lower cost.
For those with some knowledge of statistics, insurance is simple “sampling theory”. The normal curve, and the math underlying the normal curve, which explains the advantage of insurance mechanisms, was described by the mathematicians, Legendre and Gauss in the first decade of the nineteenth century, more than 200 years ago. Nothing has changed since then.
So, most people incorrectly assume that all insurers have the same probabilities of earning profits, avoiding losses, and remaining solvent at the end of a year of operations. NOT TRUE.
Assuming the premiums are adequate, but not excessive, covering the expected losses, expenses, including a modest profit margin for the insurer for the service of risk management, and a modest “risk premium” that compensates the insurer for the variation in their outcomes, there is only one loss ratio at which insurers, large and small, have the same probability of earning profits of a specified level.
All insurers that randomly select policyholders, as they should, and offer identical policyholder benefits,as they should, have probability 0.5000 that their losses will be at, or below, the level anticipated in their premium. At this expected loss ratio, all insurer convert their profit margin, and risk premium, to profits, cover their underwriting expenses and pay their claims. At lower loss ratios they make greater profits and at higher loss ratios they earn lower profits, incur losses, perhaps become insolvent and fail to pay their claims.
Insurers can have any loss ratio from 0.0000, if they never pay their claims, to many, many times the amount of money they take in as premium. Think AIG’s credit default swap unit. They wrote insurance on credit default swaps for premiums inadequate for the risks they were assuming and were it not for the federal government bailing AIG out it would have failed to pay any of its obligations to hundreds of thousands of policyholders.
So, how likely are insurers to have exactly the loss ratio anticipated in their premiums? The probability that any insurer has a loss ratio exactly as anticipated is 0.0000 Insurers’ loss ratios will either be higher, or lower, than anticipated, with probability 1.0000.
So, in insurance, the first objective is having a loss ratio close to the expected level. The core benefit insurance provides to society, is taking all the risks faced by policyholders, mushing them together, and effectively eliminating risk for itself, because the probability that a large insurer will have a loss ratio close to the anticipated level is very high. At the same time, the probability that a small insurer will have a loss ratio very close to the anticipated level is relatively small.
I can even give a really simple example of how different these can be. Let’s assume that we have an insurer with 1,000,000 policyholders. The numbers I will give are good across many lines of insurance. Let’s assume that the insurer incurs expenses of 15% of premium revenues. We also assume that the expected loss ratio is 0.7500. We also assume a profit margin of 5% of premium revenues and the insurer charges a “risk premium” of 5% of premium revenues. The profit margin rewards investors and the risk premium increases the insurer’s probability of being able to give its investors the desired profit margin even if the insurer’s loss ratio goes as high as 0.8000.
This means that the insurer expects to pay out about 75% of its premium revenues in policyholder benefits. Moreover, let’s assume that the probability this fairly large insurer’s loss ratio lies between 0.7000 and 0.8000 with probability 0.9500. This is a nice situation for this insurer, because the probability of a loss ratio less than 0.7000 is 0.0250 and the probability of a loss ratio greater than 0.8000, is also 0.0250. So this insurer is quite unlikely to incur losses so high that it will incur an operating loss. This insurer’s probability of a loss ratio greater than 0.8000 is far less than 0.0250. In truth, this insurer is highly likely, probability 0.9750, to earn profits greater than 5% of premium revenues, at loss ratios below 0.8000.
At the same time, suppose we have another insurer with only 10,000 policyholders. This insurer also selects policyholders at random and provides exactly the same policyholder benefits. But due only to the smaller portfolio size, this insurer’s loss ratio spread with probability 0.9500 runs from 0.2500, to 1.2500. This is really bad, and it is the reason that more competition between smaller insurers is the worst idea imaginable.
This insurer, like all same sized insurers, insuring people from this population, has probability 0.0250 of a loss ratio greater than 1.2500. This is really bad because this insurer incurs operating losses when its loss ratio exceeds 0.8500. In fact, with a little mathematical wizardry, I can tell you that this smaller insurer’s probability of incurring an operating loss, due solely to its smaller portfolio size is 0.3475. By contrast, the larger insurer, with 1,000,000 policyholders, has probability 0.0000 of ever incurring an operating loss, at a loss ratio in excess of 0.8500.
This is how the mathematics of insurance works: Large insurers, especially a largest possible insurer, a single payer, national health insurer is the most efficient risk manager possible.
Small insurers – VERY, VERY BAD IDEA!.
The only problem Minnesota is likely to run into, with a single payer, is that the population of Minnesota, in 2016, is only 5,303,925. In our example, the Minnesota single payer has probability 0.95 of a loss ratio between 0.7283 and 0.7717. Not bad at all but nothing like the advantage that a single payer, national health insurer, with 323,000,000 policyholders has, with probability 0.95 of a loss ratio between 0.7472 and 0.7528.
This is how insurance really works. Doesn’t cost a lot to figure this out. Hell, I will contribute my time just to see it get done faster.