Public Policy

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California Health Benefits Review Program

June 10, 2010 in Public Policy, Regulation | No comments

If California were to enact a mandate for insurance companies to cover certain services, how much would this cost?  How would it affect public health?  Would utilization change?

To answer these questions, the California legislature charged the California Health Benefits Review Program (CHBRP) to estimate the medical effectiveness, public health and cost implications of proposed health benefit mandates.  A paper in Health Services Research discusses the methods used to evaluate these potential mandates.  In particular, legislators want the following two questions answered:

  1. the present baseline coverage for the benefit and baseline per unit costs, utilization, and total per-member, per-month (PMPM) health care expenditures, and
  2. projected changes in coverage, per-unit costs, utilization, and PMPM expenditures following the implementation of the mandate.

The data sources used to answer these questions include:

These reviews estimate not only the short term impact of a mandate, but also the long term impact.  For instance, if a certain mandate increased utilization in the short run, costs likely will rise.  If the increased utilization improves patient health in the long run, however, costs may decrease over a longer time horizon due to decreased hospitalization rates.

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Explaining the Stimulus Bill’s affect on Medicaid

June 8, 2010 in Medicaid, Medicaid/Medicare, Public Policy | No comments

The Stimulus Package, also known as the American Recovery and Reinvestment Act (ARRA), key goal was to boost a flagging economy.  A number of the provisions in the $787 billion package went towards health care provisions.  The Kaiser Family Foundation notes that “the Act includes $149 billion in health spending of which $87 billion is for a temporary increase in the federal share of Medicaid costs, $25 billion for temporary COBRA subsidies, and other spending for health information technology (HIT), the National Institutes of Health and for Community Health Centers.”

To summarize the impact of ARRA on Medicaid funding, I have made the following table.

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Explaining how Health Reform will alter Medicaid and CHIP

June 7, 2010 in CHIP, Medicaid, Public Policy | No comments

Health Reform, also known as the Patient Protection and Affordable Care Act (PPACA), drastically altered the health care landscape.  Congress included health exchanges, and individual mandate, and a number of other reforms into the bill.  Today, I focus on how Health Reform will affect existing programs which care for the nations poor.  In particular, CHIP funds medical care for many of the nation’s youth and Medicaid provides health insurance coverage to low-income Americans.  Both programs operate under a federal mandate, but are run at the state level.  The Kaiser Family Foundation outlines the Health Reform provisions that will alter both the Medicaid and CHIP programs.

To summarize these findings, I have created the following table.

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California Task Force on Affordable Care’s Top 10 Recommendations

May 17, 2010 in Public Policy, Supply of Medical Services | 2 comments

How can we improve health care?  The California Task Force on Affordable Care gives its top 10 recommendations in this report.  The report’s slogan is “ten ways Californians can save over $300 billion.”  These recommendations include:

  1. Implement bundled payments
  2. Hold hospitals accountable for progress in reducing utilization in targeted areas such as imaging
  3. Directly act to reduce hospital readmissions and hospital acquired infections
  4. Develop best practice guidelines that protect providers who use appropriate medical judgments in  targeted high-cost areas
  5. Common standards for billing, eligibility, and contracting
  6. Merge California’s two health insurance regulators, the Department of Insurance and the Department of Managed Healthcare.
  7. Create a sole-source insurance exchange for individuals and small businesses
  8. Increase support for shared decision making
  9. Impose a tax on high calorie, sweetened beverages.
  10. Make walking, biking, and the use of public transit viable, affordable, safe, and attractive

I will divide these ideas into the Good, the Mixed and the Bad.

Read the rest of this entry »

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The Impact of Comparative Effectiveness Research on Health Care Spending

April 14, 2010 in Health Insurance, Public Policy, Quality | 3 comments

Comparative Effectiveness Research (CER), as it name suggests, compares how well different medicines treat a given disease.  Politicians claim that using CER findings can help improve quality and decrease cost.  If one treatment produces better health outcomes on average than another and also costs less, we should always make people use that treatment, right?

Not according to a working paper by Basu and Philipson (2010).  Let us assume that health outcomes for Drug A are better than the health outcomes for Drug B.  If the results from this research were released, the public’s demand for Drug A would increase and the demand for Drug B would decrease.  However, this may not save money.  The demand for Drug B will decrease since fewer people want to buy it; this will reduce expenditures.  As the demand for Drug A increases, however, the price and quantity purchased will increase.  Thus, the net effect on spending is indeterminate.

In addition, if insurance companies or the government decided to subsidize or cover the entire cost of treatment using Drug A, the demand will increase even more.

Basu and Philipson, however, assume that the marginal cost to produce a drug increases as the quantity rises (i.e., the supply curve is upward sloping).  However, because there are economies of scale in the production of pharmaceuticals, the price of Drug A could actually decrease (increasing returns to scale) or stay the same (constant returns to scale) as demand increased.

The key assumption in the above analysis is that it assumes that all people with a given disease respond in a homogeneous way to Drug A.  If two-thirds of people have better health outcomes when treated with Drug A and one-third have better health outcomes when treated with Drug B, then it may be suboptimal to cover Drug A, but not Drug B.

To prove this, Basu and Philipson look at the Clinical Antipsychotic Trials of Intervention Effectiveness project (CATIE).  They find that “if Medicaid would have eliminated coverage for the least cost-effective treatments of the CATIE trial then under homogeneous effects, it would save about 90% of the $1.3B Medicaid class sales annually in non-elderly adult patient with schizophrenia. However, taking into account the observed heterogeneity in treatment effects, it would incur a loss of health valued annually at about 98% of class spending and thus a net loss of about 8% of annual class spending.”

However, one of their key assumptions is that not covering the less effective medicines means that no patients will take the uncovered drug.  This may be a fair assumption for the Medicaid population, but not for the population at large.  There is a big distinction that needs to be made between not covering a drug (but allowing for the purchase to purchase it out of of their own pocket) and prohibiting the drug entirely.  Basu and Philipson are looking at the most extreme case where not covering the drug means, de facto, that the drug will not be taken, but this need not be the case.

What is important to take from this research, however, is that the drug that is most effective on average may not be the best drug for everyone.  One must take into account heterogeneous treatment effects when designing any insurance benefit plan.

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CLASS Act: Will it work?

April 6, 2010 in Health Insurance, Public Policy | 1 comment

One aspect of health reform that has received little attention is passage of the Community Living Assistance Services and Supports(CLASS) Act.  This act creates a long-term care (LTC) insurance program.  However, the insurance plan in its current form is fairly limited.  Those who require assistance with activities such as bathing, dressing, getting out of bed and using a toilet would receive about a $50 per day benefit.  This is of course not enough to pay for full-time care in a nursing home, but would help defray some of the cost for assistance in one’s home.

Milliman notes that currently, the CLASS act would be voluntary and would include guarantee issue (meaning that no one could be denied coverage).  Separately, each of these provisions could allow for a sustainable long term care insurance product.  The private sector currently uses the voluntary insurance model with underwriting.  On the other hand, a guaranteed issue policy could work if purchasing LTC insurance was mandatory.

Together, however, these provisions may be problematic.  “The voluntary aspect of the program allows low-risk individuals to never sign up for the program while the guaranteed issues enables some of the highest-risk individuals to join the program.  This is a formula that is virtually certain to create financial instability in any insurance program unless there are other important provisions to control risk.”

The CLASS act does have some additional risk control provisions.  To qualify for these benefits, one must pay into the plan for 5 years.  Employers can decide to offer this LTC as a benefit and employers who choose to this option will have employees automatically enrolled with the premium deducted from each paycheck.  Individuals would have to specifically ask to be removed from the program.  Also, individuals who opt-out of the program will have to pay a higher premium if they decide to opt back in.  The purpose of the vesting and opt-out penalties is to minimize adverse selection.

However, Scot Forman of Long Term Care Associates notes that many employees may not realize that if they opt out after just 1 payment and later opt in more than 5 years in the future, they would pay “a massive penalty,”  If a young worker who has just 1 deduction from her paycheck at age 38 later decides to opt-in when she’s 59, her premiums would be higher than they would have been had she stayed in the program. In the example given, “the rate increase will be no less than 250% on each payment, which is CLASS’s penalty for opting back in.”

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The Cost of Uncompensated Care

April 1, 2010 in Health Insurance, Public Policy | 4 comments

Because it expands health insurance coverage, one of the key effects of the recently passed health reform bill is that it will decrease the amount of compensated care.  According to an Urban Institute study:

“…the cost of uncompensated care will fall from $62.1 billion in 2009 to $46.6 billion in 2019 under the Senate bill, and to $36.5 billion in 2019 with the House bill…Without reform, the cost of uncompensated care will increase to between $107 and $141 billion in 2019, depending on growth in the economy and health care costs.”

Who currently pays for uncompensated care?  This chart provides a breakdown.  Surprisingly, physician’s in-kind free treatment makes up only 14% of uncompensated care.  On the other hand, Medicare and Medicaid fund the largest share of uncompensated care.  The reason for this is that Medicare has a disproportionate share hospital (DSH) payment program indirect medical education payments and Medicaid also has a DSH program as well as supplemental provider payments programs.  The authors count these programs as payment for uncompensated care.  The DSH payment system doesn’t make much sense to me.  If, Medicare or Medicaid payments are too low, why not raise the reimbursement rates rather than give lump sum handouts to hospitals in the form of a DSH payment.

State and local government also pay for a large share of uncompensated care.  In California, county-financed clinics are the last refuge for those without insurance, especially for undocumented immigrants.  According to the study, state and local governments pay for about 18% of unfunded care.

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Does spending improve outcomes?

March 12, 2010 in P4P, Public Policy, Quality | No comments

From a paper by Weinstein and Skinner (NEJM 2010):

“Moreover, there is considerable variation in health care expenditures and a weak or even negative association between spending and outcomes, such as mortality at the regional level and quality measures at the state level. This evidence has been interpreted to mean that cutting back on these putatively useless or harmful services would simultaneously reduce cost and improve health. In contrast, several cross-sectional studies that have shown positive associations between spending and outcomes have been interpreted to show that more spending leads to better outcomes.”

“A recent study using chart-review data from the 1994–1995 Cooperative Cardiovascular Project categorized “…hospitals as either high-adopting facilities or low-adopting facilities, according to their rates of use of aspirin, beta-blockers, and coronary reperfusion in the treatment of acute myocardial infarction. The researchers found that the high-adopting hospitals had consistently better rates of risk-adjusted survival, at no additional cost to Medicare. But after stratification according to the hospitals’ adoption rates, there was a positive but diminishing effect of spending on the health outcome (12-month survival)…The cost-effectiveness ratios at the margin were $95,000 per life-year or more but with slightly better returns for the hospitals that were slower to adopt cost-effective practices…”

“Another study showed that regions that had high rates of revascularization for patients with acute myocardial infarction received good health value for the expenditure on the intervention.  Despite this, there was essentially a zero association between spending and outcomes across regions. The explanation is that the high-revascularization areas were also less likely to use beta-blockers and aspirin for their patients.”

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Comparative Effectiveness vs. Cost Effectiveness Research

March 11, 2010 in Public Policy, Quality | 5 comments

Comparative Effectiveness has been a hot topic in health services research. According to a recent article in the New England Journal of Medicine, “the American Recovery and Reinvestment Act of 2009 authorizes the expenditure of $1.1 billion to conduct research comparing ‘clinical outcomes, effectiveness, and appropriateness of items, services, and procedures that are used to prevent, diagnose, or treat diseases, disorders, and other health conditions.’”

Comparative effectiveness compares how effective various medical treatments improve health outcomes.  This sounds like the course we want to take.  Most policymakers laud the health benefits of comparative effectiveness research, but some people claim that comparative effectiveness research can also save cost.

This is most easily seen in the case where a treatment is completely ineffective.  If research can prove a treatment is ineffective, then insurers could save a lot of money by not covering this type of treatment.  This is especially true if the treatment is expensive.

However, comparative effectiveness treatment could also increase cost.  Assume that there are two treatment currently in use: Treatment A and Treatment B.  Let us say that treatment A costs $1,000 and has a 90% cure rate and Treatment B costs $10,000 and has a 95% cure rate.  According to comparative effectiveness research, we should always use Treatment B.  Yet this would significantly increase costs.

Most health economists argue that cost effectiveness research is provides a better way to improve health and decrease cost.  In the example above, should we cover Treatment B?  The answer is likely yes if this is a very serious disease (e.g., cancer) but likely not if the disease is less serious (e.g., the common cold).  Some readers may believe insurers should always cover Treatment B no matter what.  However, would you be willing to pay increased premiums that would occur if treatment B were covered?  Would you feel the same way if Treatment B cost $100,000?  or $10 million?  What if the cure rate was only 90.1%?

At some point, there must be a trade-off between cost and benefit.  Admittedly, these are very difficult decisions in practice, but because there are limited healthcare resources, we must ration care.  Yes, I said it, we must ration care.  I’ve said this before.  This rationing can take many forms: the scope of what your insurance company (or Medicare) will cover, waiting lines, or increased prices you must pay out of pocket for medical services.  The government wants to avoid making these tough choices because it is politically unpopular.  Politicians don’t want to be labelled  the sentator who “killed Grandma” or “instituted a death panel.”  But to truly decrease cost and improve quality, cost effectiveness rather than comparative effectiveness is the prescription we need.

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Health Insurance Subsidies (a.k.a Higher Marginal Tax Rates)

March 3, 2010 in Public Policy, Taxes | No comments

The health reform bills currently propose introduce health insurance subsidies for individuals who do not qualify for health insurance provided by the government.  The goal of these subsidies is to make health insurance more affordable for the lower and middle class. The subsidies gradually decrease for higher income levels.

In “Obama’s Prescription for Low-Wage Workers,” Michael Cannon notes that one also can see these subsidies as increasing the marginal tax rate.  For instance, let us John makes $16,000 and has a 25% income tax rate.  Under the new health reform bill, John would also receive a subsidy to purchase health insurance.  Let us assume the subsidy is $5000.  Thus, his after tax income is $17,000 [(1-.25)*16,000+5000].

What happens if John has the option to work at a new job that pays him $20,000?  Of course, he will earn more income but his health insurance subsidy will also decrease.  If the health insurance subsidy decreases to $3,500, then his after tax income in your new job is now $18,500 [(1-.25)*20,000+4000].  Although John’s gross income increased by $4000 when taking the new job, his after tax income only increased by $1500.  This is in a marginal tax rate of 62.5%.  In fact, Mr. Cannon’s research finds that mandates and subsidies impose effective marginal tax rates on low-wage workers “averaging between 53 and 74 percent.”  When marginal tax rates are high, extra hours worked lead to a smaller increase in after-tax income.  Thus, the labor supply decreases.

One thing Mr. Cannon ignores, however, is the current Medicaid poverty trap.  Poor individuals are eligible for Medicaid.  However, if they get a better job paying them more money, they may lose their Medicaid eligibility.  Poor individuals may refuse to take better paying jobs to keep their Medicaid coverage.

Once the subsidies are implemented, however, poor individuals will be more likely to take a better-paying job since they can receive subsidies to buy private health insurance even if they lose their Medicaid coverage.  The high marginal tax rates are more likely to affect the labor supply of the lower-middle class and middle class individuals.  These individuals are in the same scenarios as John is above.  Higher pre-tax earnings will not necessarily translate into significantly larger after-tax earnings.  I predict that the higher marginal tax rates Mr. Cannon mentions will decrease the labor supply most for individuals in the middle class.

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