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Government Health Metrics: A Solid B+ Even Though Some Medicaid Patients Cannot Get an Appointment

In accordance with federal law, Colorado hired Health Services Advisory Group (HSAG) to do an on-site review of Denver Health Medicaid Choice plan performance in 2013. Denver Health is one of Colorado’s biggest Medicaid contractors. It runs a hospital, a pharmacy, 9 satellite primary care clinics, 4 dental clinics, and 16 school-based health centers. HSAG’s report on Denver Health’s performance was published in April, 2014. All Medicaid clients with a Denver address are automatically enrolled in Denver Health Medicaid Choice unless they choose another Medicaid option.

Denver Health scored well overall. It met 87 percent of all of the evaluative standards. Paperwork on coverage, utilization management, provider certification, and denial of claims documentation was in near perfect order. According to its annual Strategic Access Report, 99.8 percent of Medicaid members were within 30 miles of a Denver Health clinic and there were 54 bus stops within a quarter of a mile of its clinics. It had direct access to care for members with special needs, 24-hour emergency access, preventive health programs, and numerous “committees, workgroups, staff trainings, and evaluation of metrics regarding provision of interpreters and understanding of culture with respect to health care.”

The Federal Government’s Dismal Record on Corporate Income Taxes Drives Firms Offshore

Many companies in the healthcare sector are undertaking so-called tax inversions to move their headquarters overseas. Here’s an explanation of why the trend has picked up.

Because the U.S. federal government is refusing to respond to international competition for the headquarters of successful multinational companies, U.S. multinationals are moving their headquarters out of the U.S. in order to protect their shareholders from high U.S. corporate tax rates. The shareholders needing protection include large numbers of retired and working U.S. citizens who have investments in company stock, either directly or through various collective investment vehicles.

As the following graph from a Baker & McKenzie presentation at a 2013 meeting for tax experts shows, the U.S. federal government was a lot smarter about the realities of global competition back in the 1980s. In the 1980s, it responded to international competition by reducing the U.S. corporate tax rate. Since then, it has increased the U.S. rate even as other countries have been lowering theirs, driving corporate headquarters out of the country.


Political Control of Obamacare Insurance Pricing Harms Those with Lower Incomes

When Obamacare kicked off, Colorado State government had grouped its ski resort  counties into a single rating area. This makes sense geographically. But everything is more expensive in the ski resort counties, and under Obamacare pricing rules resort county residents ended up with the highest health insurance exchange premiums in the country. The resulting town meetings were spirited, county commissioners threatened to sue, and Colorado Insurance Commissioner Marguerite Salazar began looking for ways to redraw the rating areas to lower the political angst.

Before Obamacare, someone in the mountain towns might economize on health costs by buying a high deductible health insurance policy and making regular contributions to an HSA. He might use a local physician, hospital, or clinic. He could also save money with in-state medical tourism. A few hours of driving would let him seek lower priced care in Denver’s more competitive health care market.

Yet Another Reason Why Obamacare Health Insurance Prices Make so Little Sense

Proponents of government run health care have an inexplicable disdain for geographic variability. They often seem to assume that physicians, treatments, and outcomes should be constant across the entire United States. Any variations in price, treatment modality, or expenditure ranks as a sure sign of an improperly run health care system.

The problem is that normal human activities vary even over relatively compact geographic areas, and the variations often reflect the exigencies of daily life rather than administrative boundaries. For example, when a company took the trouble to analyze credit and loyalty card data about its customer’s shopping habits, it found that even a relatively compact area like a city had distinct variations in its shopping and retail use patterns.

The maps below are reproduced from a Boston Consulting Group article about what the company learned about its pricing power. In the beginning, the company had the single pricing zone for all of Georgia shown in the left hand map panel. The right hand map panel shows how its pricing zones changed after customer habits were considered. Of interest is the fact that Atlanta ended up with multiple pricing zones. High population density makes it harder to move around, limits customer mobility, and people’s ability to access goods and services. The report notes that in Atlanta, stores serving the same clusters of customers often are “located along commuting corridors.”


ObamaCare: The Perfect New-Keynesian Policy Prescription?

University of Chicago finance professor John Cochrane believes that slow economic growth “trumps every other economic problem.”

He and a number of macroeconomists believe that the Keynesian model drilled into your head in Econ 1 has a number of shortcomings that make it produce lousy economic policy, even in its New-Keynesian version. Shortcoming number one is that the New-Keynesian models do a very poor job of explaining reality. Just how poor a job is shown in the graph below.


Does Public Health Coverage Augment Private Coverage or Crowd It Out?

Expansion of government health care programs like Medicaid is sold with the explicit argument that expansion will cover the uninsured. However, expansion may also cause people who are already insured to cancel their insurance or let it lapse so that they can take advantage of a less expensive to them government program. Academic studies of the size of the crowd-out effect arrive at a variety of conclusions ranging from Lo Sasso and Buchmueller’s estimate of a 50 percent crowd-out rate for SCHIP to an 8 percent rate for Dague et al.

Wisconsin runs its own population survey of health coverage. It samples from all Wisconsin households with landline phones (weights adjusted to represent what is known of the cell only population). The response rate is 47 percent, and 2,462 households were interviewed in 2011.

Here are two graphs showing what the survey has found over the last decade. What is most striking is that if the overall rate of coverage has increased, the increase is small. The increase in public coverage of children of about 25 percentage points mirrors a similar loss in private coverage; and the same effect ― but slightly smaller ― is observed in working-age adults.



Magical MAGI: Defining Who Gets ObamaCare Subsidies

A person who buys an ObamaCare health insurance policy can get a tax credit (subsidy) if his household’s Modified Adjusted Gross Income (MAGI) puts him below 400 percent of the Federal Poverty Level (FPL).

But what is a household?

It isn’t easy figuring out those magical MAGI groups when ObamaCare premium subsidies depend on family size and the definition of a family is, shall we say, rather flexible. As the Wisconsin training handout puts it, “the new MAGI methodology introduces tax relationships into the way we build BC+ [BadgerCare Plus] household composition. Under MAGI, household composition is formed using either ‘tax rules’ or ‘relationship rules.’ The use of tax rules versus relationship rules is based on whether or not the individual for whom the assistance group is being formed intends to file taxes or is a tax dependent.”

The manual goes on to say that it is important to remember that because Assistance Groups are person specific, “the household composition for each Assistance Group must be examined one person at a time and each Assistance Group is formed around a target (the individual who is requesting assistance). The target’s assistance group is formed based on that target’s age, marital status, tax filing status, tax relationships and/or family relationships.”

If you have a “target” living in a spare room or basement, here’s a flowchart that might come in handy:


The State of Medicaid Quality Measurement

Thanks to ObamaCare, the state of quality measurement in health care is rapidly approaching the state of quality measurement in public education. Process measures dominate. Many of these measures are worthless. They measure nothing that has anything to do with providing actual medical care that successfully cures or alleviates the suffering of sick people in a timely manner.

The following list gives the items chosen to measure the general performance of the Indiana Medicaid program for 2012 with an emphasis on access to care. The good news is that Indiana contracts for an independent outside evaluation of its program. The bad news is that 13 of the 16 measures depend upon whether or not a patient decides to visit the doctor.

In those 13 measures, quality is assumed to be higher if a higher fraction of covered individuals have at least one health care visit. The report continually equates visits with access as in “there were fewer differences in the rate of access to primary care for adults across the regions than was found for children” and “the adults in the 45-64 age range were more likely to access primary care services than the 20-44 range.”

The bulk of the measures show whether an otherwise healthy person came in for a check-up. One of the measures, nutrition and physical activity counseling for children and adolescents, which is satisfied by entering BMI data in a patient record, likely duplicates school programs. Others, like measuring the quality of mental health care by whether or not someone hospitalized with a psychiatric diagnosis shows up for an appointment 7 or 30 days later, are beyond the control of anyone but the patient.

Ignoring the Obvious? Choosing Suitable Metrics in Evaluating Health Care

One of the biggest problems in health policy is choosing the appropriate metrics to evaluate a complex good like health care. Value is in the eye of the beholder. All too often, the beholder is not the consumer, which leads to an affinity for numeric measures said to be more “rigorous” or “precise.”

As a result, many Medicaid evaluations use population health measures that have as much or more to do with individual behaviors as they do with the action of any part of the healthcare system. Things like number of primary care visits, BMI, cholesterol levels, and blood pressure, are easy to measure provided someone first decides to visit the doctor. And outcomes based on those measures depend upon whether someone decides to diet, exercise, and take the prescribed medications.

Because simple metrics abound, we have a lot of studies evaluating the health “system” that only observe changes in relatively simple and inexpensive treatments that are behaviorally dependent and are provided to a lot of people. Many policy makers are satisfied with this. It accords well with the views of U.S. health care reform advocates who favor more centralized gatekeeping and approve of policies that force people to consume more primary care as a condition of being allowed access to specialists. If people got more primary care, the mantra goes, they wouldn’t need to see specialists.

Puzzle of the Day: Medicaid Expansion and Unavoidable Emergency Department Visits

Ambulance at Emergency EntranceTo paraphrase John Wayne, evaluating health care is hard. It is even harder if you use percentages.

A 2011 report on whether or not Wisconsin’s BadgerCare’s coverage of childless adults affected their utilization of services concluded that people in a sample of about 10,000 very low income childless Milwaukee adults increased their total emergency department visits by 39 percent when they were newly enrolled in Medicaid coverage.

Seventeen percent of visits resulted in a hospital admission before Medicaid was expanded to cover the group. After expansion, 9.5 percent of emergency department visits resulted in a hospital admission.

The report spins this like it was a good outcome: “This significant 45% decline is notable in that Wisconsin Medicaid payment policy considers an ED visit ‘appropriate’ when it results in a hospital admission.” Later on, the report reminded readers that “the percentage of hospital admissions from the emergency department declined dramatically.”