Health Insurance

On Friday I posted on Consumer Driven Health Care.  These consumer driven health plans (CDHPs) involve individuals having direct discretion about how health care dollars are spent.  If you are interested in CDHP, there may still be some confusion over which H?A you prefer.  Is a HRA (Health Reimbursement Account or Health Reimbursement Arrangement) or a HSA (Health Savings Account) better?  Scott Borden of OFM Benefits Consulting gives some simple explanations in his Kansas City Star article (”…Health Insurance for Workers“).

Consumer directed health plans (CDHP) seem like an attractive option for small businesses. CDHPs utilize high deductible health plans (HDHP) making patients pay more money out of pocket. Because of this, insurance premiums are lower. These HDHPs can be linked to Health Reimbursement Arrangements (HRAs) or Health Savings Accounts (HSAs). Since small businesses do not benefit from economies of scale with respect to the purchase of insurance, HDHPs may be especially attractive for this group.

A paper by Gates, Kapur and Karaca Mandic (2008) find this not to be the case, however. Firms employing 3-49 people are no less likely to offer high deductible health plans than are large firms–conditional on offering insurance. Midsize firms employing 200-499 workers are less likely to offer HDHPs than larger firms.

If the firm offers a HD health plan, will they offer an HSA? One may guess that small firms are less likely to offer HSAs if there are fixed costs to implementing an HSA. Small firms will have higher average costs to offering HSAs, if offering HSA is a true fixed cost and its cost to the employer is not proportional to the number of employees in the firm.

It turns out that small firms between 3-49 workers and firms with 200-499 workers are less likely to offer HSAs–conditional on offering HDHPs–than large firms with 500 or more workers. Middle sized firms with between 50 and 199 workers are just as likely to offer HSAs as large firms.

Other findings of the study include that HSAs are most popular in the Midwest and the South and, surprisingly, firms with a higher proportional of low-income workers are more likely to offer HSAs.

• Susan M. Gates, Kanika Kapur, and Pinar Karaca-Mandic (2008) “Consumer-Directed Health Plans and Health Savings Accounts: Have They Worked for Small Business?,” Forum for Health Economics & Policy: Vol. 11: Iss. 2 (Health Economics), Article 4.

John Tierney writes in The New York Times (”Appeasing the Gods…“) that “”We buy insurance not just for peace of mind or to protect ourselves financially, but because…we think buying health insurance will keep us from getting sick.”

A rational person would believe that buying insurance against an event will not alter the probability that it will occur–ignoring issues of moral hazard.  For instance, the act of buying health insurance should not make us less likely to be sick.  Using more preventive care which is cheaper due to insurance can prevent illness, but the act of buying health insurance should not effect the probability one gets sick holding constant the medical care levels.

A better example may be travel insurance.  “Last year, tens of millions of people bought life insurance for scheduled flights of airlines in the United States. Not one of those insured passengers died in a crash.”  Is this a waste of money?  Not if you are superstitious and believe that the act of buying life insurance affects the probability your plane will crash.

“So when we think about passing up flight insurance, we conjure up disaster just as easily as ancient Greeks imagined a thunderbolt from Olympus, and we too figure we can avert it through the equivalent of a bull sacrifice. Intuitively, we haven’t made great strides since Homer’s day. But at least our gods take credit cards.”

• Hat tip to Arnold Kling at EconLog.

Throughout its history, Medicaid provided health insurance for the nation’s poor. It did this by reimbursing providers on a fee-for-service basis. In the 1990s, however, California and other states decided to let private insurance companies bid for the right to provide services for Medicaid patients. These HMOs would receive a fixed per patient per month payment and the private insurer would be responsible for providing health care to Medicaid enrollees.

HMOs may be more efficient than the government since 1) they have an incentive to keep enrollees healthy to save cost, 2) they can negotiate lower input prices, and 3) competition may lead to higher quality, lower priced medical care. On the other hand, keeping the government run fee-for-service program may have been more efficient if 1) the government’s size and negotiating power could decrease input costs, 2) there may be increasing returns to scale, 3) the HMOs may include significant markups in their bids, and 4) HMOs may offer medical services which do not appeal to unhealthy enrollees (i.e., adverse selection).

A paper by Mark Duggan in the Journal of Public Economics in 2004 aims to see if contracting out Medicaid health care provision to private HMOs decreased costs. Duggan uses the fact that California enacted a mandate that all AFDC Medicaid enrollees must switch to a private HMO. For other individuals, such as those on SSI and those who were disabled, deaf or blind, the switch to the HMO was voluntary. This mandate was enacted between January 1993 and December 1999 depending on the county. The author uses variation in the county enactment date to find the effect of Medicaid HMOs on cost.

Background

The manner in which California instituted the transitioned individuals into private managed care plans can be categorized into 3 groupings:

1. Geographic Managed Care. “the state government contracts with several commercial HMOs to coordinate care for Medicaid recipients. Plans initially applied by submitting a menu of prices at which they would be willing to insure each type of Medicaid recipient. The government then awarded contracts to the plans most likely to deliver high quality medical care at a low price, though the weight placed on quality and spending was not specified.”
2. County Organized Health System (COHS). “Under this model, the not-for-profit, community-based HMO was reimbursed a fixed amount per recipient-month that varied by eligibility category.” Individuals did not have any plan choice and the state did not allow bids from for-profit firms.
3. “Two plan” counties. In these counties, the Medicaid enrollees would be able to choose between one private, commercial plan and one not-for profit plan. “…the state solicited bids from private companies and awarded a contract to just one of the plans.”

The following chart gives the type and date of managed care mandate by county.

Methods

Duggan uses the following equations to estimate spending.

• ManCare_jkt = α₁ + γ₁Mandate_kt + μ₁X_jkt + θ_1j + λ_1t + t*ρ_1k + ε_1jkt
• Spending_jkt = α₂ + γ₂Mandate_kt + μ₂X_jkt + θ_2j + λ_2t + t*ρ_2k + ε_2jkt

Subscripts j, k, and t index individuals, counties, and years respectively. The variable Mandate is equal to the fraction of individual j’s Medicaid eligible months in which a mandate was in effect. ManCare is equal to the fraction of the j’s eligible months in which he is actually enrolled in an HMO. Spending is equal to the Medicaid spending for person j at time t.

Results

Duggan finds that the managed care mandate increased Medicaid spending. Medicaid spending increased by between 17% and 23% for counties in which the mandate came into effect. These results, however, were less pronounced where there was competitive bidding between insurance companies (i.e., the Geographic Managed Care and “Two plan” counties).

Also, despite the increased spending, the author finds no evidence of increased quality in terms of better infant birth outcomes.

• Duggan, Mark (2004) “Does contracting out increase the efficiency of government programs? Evidence from Medicaid HMOs” Journal of Public Economics, v 88(12): 2549-2572/

Consumers are starting to pay a larger share for high priced drugs.  According to the N.Y. Times (”Co-payments“), insurance companies “…are charging patients a percentage of the cost of certain high-priced drugs, usually 20 to 33 percent, which can amount to thousands of dollars a month.”  Medicare’s drug plans have introduced new fee schedules where patients pay larger copayments for Tier 4 and Tier 5 drugs.  Private insurers now followed Medicare’s lead.

Should consumers bear a larger burden of their health care costs?  On the one hand, moving towards more out-of-pocket costs will reduce premiums.  Further, higher co-payments will reduce moral hazard (i.e., the use of unnecessary medical care simply because insurance pays for it).  Also, this moves us closer toward insurance as a policy to insure people against catastrophic risk and not as a mechanism to pay for all medical care.

Still, health economist James Robinson from UC-Berkeley states that “It is very unfortunate social policy.  The more the sick person pays, the less the healthy person pays.”

David Whelan chronicles the rise (and possibly future fall) of Medicare Advantage programs in his article “Unfilled Prescription” in Forbes.

Earlier laws privatizing Medicare, starting with a pilot program in 1985, were written to give insurance companies only 95% of the money otherwise spent per Medicare member. The insurers were supposed to figure out how to make up the difference. It was a blunt way to save the Treasury money, but few companies stepped up…

The 2003 law hiked the payments to lure more insurers into the market. In some counties minimum payments to these plans reached as much as 128% of the amount Medicare traditionally spends per patient. Insurers rushed in, and costs soared. In the most remunerative counties, two times as many old people are enrolled in Medicare Advantage as the national average. As a result, taxpayers now pay an average of 12% more per private-plan beneficiary, not 5% less.

Whenever we talk about cost we also need to talk about quality.  Are people who opt for Medicare Advantage plans getting higher quality care than in traditional Medicare?  Are they able to see doctors in a more timely manner?  Is care more coordinated?  If this is the case, then the extra costs may be worth the money.

Nevertheless, an economist would guess that Medicare Advantage plans should be cheaper.  Even though the private plans have higher administration and advertising costs, they likely are more efficient than the government plans.  Further, one would anticipate that healthier seniors would choose the Medicare Advantage plans and sicker senior would be more likely to choose traditional Medicare.  This selection problem should make Medicare Advantage cheaper.

I agree that the federal government should not pay more money for private plans than it does for traditional Medicare.  It should reimburse the plans the same (or less if there is adverse selection) as it costs for the government to administer traditional Medicare and if firms want to increase the price, than seniors can pay the difference.  If seniors do not want to pay the difference, they can always opt for traditional Medicare.

Gruber (1994) shows that the costs of employer-provided health insurance benefits are passed on to employees through lower wages. But do employees with higher expected medical expenses have their wages reduced by a higher amount to reflect the additional medical costs to employers? This may not be the case if employers can not observe the health of employees when they hire them. On the other hand, for obese individuals, the fact that they are obese is easily observable. Papers such as Finkelstein, Fiebelkorn and Wang (2003) show that annual medical expenditures for obese individuals are $732 more than those of normal weight. Is this additional cost passed on to obese employees through lower wages?

This is what an NBER working paper by Bhattacharya and Bundorf (2005) aims to investigate. The authors compare the wages of obese and non-obese individuals in companies without health insurance. Then they compare the differences in wages of obese and non-obese employees in companies with health insurance. Since no health insurance costs will be passed on employees if no insurance is offered, the difference between the two wage gaps may be able to identify if higher health insurance premiums are passed on to employees through lower wages. If there are differences in wages between obese and non-obese workers (i.e.: due to discrimination, lower productivity, etc.) these differences are likely constant across firms with and without health insurance.

The authors find that “the incidence of obesity on wages for workers insured through their employers is -$1.68.” After controlling for a variety of covariates, this estimate lowers to -$1.44. This difference is mostly due to the fact that wages of obese workers with health insurance grew slower than thinner workers with health insurance. This may be due to the increasing price of medical care, the increasing severity of obesity–the BMI of individuals at the 95th body weight percentile has increased over time–or the aging of the population in the panel.

As a falsification test, the authors use a similar difference-in-difference estimation strategy comparing the obese vs. non-obese wage gap between employers with and without other fringe benefits (e.g.: life insurance, dental insurance, retirement benefits, child care, maternity leave, etc.). If obesity does not affect the cost of these fringe benefits, than we should see no difference in the obese/non-obese wage gap between employers who do and do not offer these benefits. The authors find that this difference-in-difference estimator is not statistically different from zero.

There are a few problems with this analysis. First the authors admit that “those with relatively low productivity due to health consequences of obesity may consume more medical care and, as a result, self select into firms offering health insurance.” Also, the data the authors have only reveals whether or not the individual has health insurance, and does not give the insurance premium paid by either the employer or the employee. Thus, these estimates are likely to be very imprecise.

Nevertheless, if this study’s results are true, then it would imply the following:

“If there are no externalities in these decisions, then “twinkie” taxes will only distort already optimal decisions. But if employer-provided insurance pools the health risk of the obese and non-obese, it will create an externality that reduces incentives to maintain a normal weight. Our evidence on the incidence of the obesity wage premium suggests that pooling of the obese and non-obese does not occur in the employer-sponsored insurance market; hence the externalities caused by health insurance on decisions about body weight are small.

• Jay Bhattacharya and M. Kate Bundorf (2005) “The Incidence of Healthcare Costs of Obesity,” NBER WP #11303.
• Finkelstein, Fiebelkorn and Wang (2003) “National Medical Spending Attributable To Overweight And Obesity: How Much, And Who’s Paying?,” Health Affairs, Web Exclusive, May 14, 2003.

In this blog, I have written about the Swiss (part one, part two) and Dutch healthcare system extensively. Both systems have a “regulated competition” where insurance is mandatory and insurance companies are mandated to provide a specific insurance benefit package. In the Swiss system, 85% of medical expenditures are financed by insurance premiums and 15% are financed by user fees. In the Netherlands, 50% of expenditures are paid by income-related contributions, 45% are paid by insurance premiums and 5% are paid by user fees. In both systems, the government pays a risk equalization premium to insurance companies who have a higher percentage of sick people to help eliminate cream skimming. However, does this risk equalization system still function when voluntary deductibles are introduced?

This is the question which a paper by van Kleef, et al. (2008) attempt to answer. Currently, the Swiss only count net claims (medical claims paid by the insurance company, ignoring out-of-pocket payments by insurers). Is this a problem? Let us give one example:

Let us assume that Healthy Hank spends $1000 on health care per year and is insured by HealthNet and Sick Sally spends $2000 on health care per year and is insured by SickFund. In the Swiss system, insurance companies receive (pay) a risk equalization payment based on whether they have above (below) average medical expenditures. This would mean that insurance premiums would be $1500, the average of Hank and Sally’s expenditures. HealthNet would pay $500 into the risk equalization pool and SickFund would receive $500.

What happens in the presence of deductibles? Let us assume that HealthNet offers an insurance package with a $500 deductible and HealthNet offers an insurance package with no deductible. Healthy Hanks will sort into the HealthNet deductible package and Sick Sallys sort into the no deductible SickFund package. Now, we have that HealthNet will have $500 of net claims on average since Hank will pay $500 and the insurance company will pay $500. SickFund will still have $2000 of cost.

Now the insurance premium will be $1250 since the insurance premium is based on net claims [(2000+500)/2]. HealthNet will have risk equalization payment of $750 and SickFund will receive $750. The insurance premium for Healthy Harry will be $1250 ($500 + the $750 equalization payment) . The premium for SickFund will be $1250 as well ($2000-the $750 risk equalization payment). Thus, there will be no benefit to choosing the deductible since there is no premium benefit. Yet policy makers would like people to choose the deductible plan to reduce moral hazard. The paper gives a few other scenarios where the risk equalization scheme fails and cream skimming occurs.

In general, economist love choice. Yet in insurance markets, the more choice is given to consumers, the more incentive insurance companies have to cream skim. Despite policymakers best attempts to control cream skimming through risk equalization payments, no risk equalization scheme will be perfect. Like everything in life, there is a tradeoff. In this case, the tradeoff is between offering consumers more choice, and reducing cream-skimming.

• RC van Kleef, K Beck, WPMM van de Ven, RCJA van Vliet (2008) “Risk equalization and voluntary deductibles: A complex interaction,” Journal of Health Economics , 27(2): 427-443.
  

Devon M. Herrick writes an article (”Why rent…“) creating a clever analogy comparing HSAs to equity in a house. He likens traditional health insurance to renting a home, while having a Health Savings Account (HSA) is more like owning the home. Making contributions to HSAs in essence gives you “equity” towards future health care expenses. On the other hand, if you do not use any medical care with traditional insurance, you lose all of your rent annual health insurance premium.

Mr. Herrick claims that he could cut his health insurance premiums by half if he had an HSA. There are 3 main reasons why health insurance premiums are lower. First, in a mechanical sense, health insurance plans are combined with HSAs which have higher deductibles. This means the insurance company will not pay for the first $1000 or so of medical care. Secondly, since there are high deductibles, utilization will decrease because of a reduction in the moral hazard problem. Finally, healthier people sort into HSAs and thus if everyone was compelled to have HSAs, health insurance prices would not decrease as much because there would be less advantageous selection.

As I have mentioned before in this blog, HSAs are highly unequal, since the rich 1) are the ones most likely to benefit from this legislation and 2) they have higher marginal tax rates and thus will receive a larger tax break for every dollar contributed.

Nevertheless, shifting more costs to the consumers and forcing consumers to face the true cost of medical procedures will help to reduce costs and to ensure than only necessary medical procedures are conducted.

• DM Herrick (2005) “Health Insurance: Why Rent When You Can Own?” Health Care News, The Heartland Institute, May 1, 2005.

Many reform advocates have claimed that the federal government should mandate a package of insurance benefits that all private and public health insurers would be legally compelled to provide. Switzerland is one country in which the government defines a what the insurance benefit will be for all standard health insurers. The National Coalition on Health Care also proposes “…requiring insurers to establish explicitly separate premiums for the core benefit package.” Is having the federal or state government mandate a minimum benefit package a good idea?

Cons

Most neo-classical economists would say that having the government mandate an insurance package is a bad idea. Regulation restricts choice. If consumers would prefer an insurance company to cover mental illness and another person would prefer their insurance company have more generous coverage for cancer treatment, then it would be welfare destroying to eliminate the individual’s choice. Even if regulators were able to determine an ‘optimal’ benefit package–even a benefit package deemed optimal for society is unlikely to be optimal for each individual–this optimality could only be achieved in a static setting. When new medical technologies and procedures became available would they be adopted? Adopting unproven medical technologies may not increase quality of care, but would increase the cost of premiums. Adopting technologies too late will harm the sick patients who could benefit from these advances.

Another issue is who would be deciding which procedures are included. Whether it is Congress or a medical “Federal Reserve,” these groups would be influenced by lobbying from the AMA, pharmaceutical companies, and patient interest groups. Further, Congressmen will have their own favorite diseases that they will include in the basic coverage plan, even when funding coverage for these diseases may not be as beneficial as for other diseases.

Pros

One benefit of the standardized medical package is that people would better be able to comparison shop. Currently, it is nearly impossible to determine what your insurance company covers unless you are an expert. With a mandated core benefit package, insurance companies would only be able to compete on the dimensions of price, service, and reputation. They would be no competition with regards to which procedures were covered. Also, this would help to attenuate the problem of adverse selection. Many insurers currently do not offer generous coverage since they know by doing so, they will attract the sickest individuals and likely decrease their profits.

Further with a standard benefit package there should be lower legal costs for both the insurance companies and patients. With a clear core benefit package, litigation would not be eliminated but it would certainly be curtailed since much of the payment ambiguity would be cleared up.

Supplemental Insurance

Regardless of whether or not you prefer a minimum insurance benefit, the government should allow supplementary insurance markets to exist. In this way, those who prefer more generous coverage could purchase additional insurance. Further, it is likely that supplemental insurance would be the first-adopters of new technology and could provide a testing group as to whether or not a new medical treatment should eventually be included into the core benefit package.

The San Diego Union Tribune has an article (”Cross-border coverage“) profiling entreprenuer Jim Arriola and his low cost health insurance plan covering medical care in both the U.S. and Mexico.

His company, Sekure Healthcare, provides a limited-benefit insurance program through employers along with a discount health card program. Both can be used by Sekure members and family members to visit doctors and hospitals on either side of the U.S.-Mexico border.

The health plan is not as generous as typical employer-provided health insurance, but may be an attractive option for low wage workers who can not afford top-of-the-line coverage.  Sekure specifically targets low wage Mexican workers in California.

While the plan certainly fills a niche, this type of cross border plan likely will not gain broad appeal.  First, most people want to receive their medical care where they live.  Thus, the option to have treatment in Mexico will likely only be attractive to frequent migrants or those living near the border (i.e. San Diego).  Secondly, the Sekuye plan does not cover catastrophic medical costs.

“Sekure pays up to $50 for each doctor’s office visit and a maximum of $300 a year for the service. Beneficiaries can get up to $800 a day and a maximum of $3,000 a year for hospitalization. They pay out of their own pockets for any charges exceeding their benefits. “

The Sekure plan is the exact opposite of health plans advocated by Republicans.  Instead of having catastrophic health insurance with a high deductible, the Sekure plan provides a minimal benefit and does not cover catastrophic costs.

Nevertheless, some insurance is better than no insurance for many low wage workers.

Yesterday, I spoke about the Swiss health care system. One of the main attributes of this system is that patients are allowed to choose from any health care plan and the health insurers can not refuse to cover them. Further, since the insurance benefit is mandated by law, there is very little quality difference between plans. Only 8% of health plans restrict provider choice in any way.

An NBER working paper by Frank and Lamiraud analyzes how the number of firms offering health insurance in Switzerland has affected price dispersion and expected price.

Economists generally believe that when more firms/products enter the market, this will increase the probability that a superior health insurer will be available to the public. However, when more products enter the market, search costs increase. Thus, it is theoretically possible for more health insurance offerings to decrease utility.

A paper by Janssen and Moraga-Gonzales (2004) show that an the welfare impact of an increase in the number of sellers depends on the consumers’ search intensity. When consumers search with low intensity, having more firms will reduce search, will not affect expected price and will to greater price dispersion. One can think that inexpensive and/or infrequently purchased items would fall in to this category. When consumers search with high intensity, an increase in the number of firms will increase searching and decrease prices. In the 401(k) market, when employees are offered more than 10 choices, there are reductions in consumer responses (i.e.: less investment switching occurs).

Frank and Lamiraud aim to analyze how the number of firms affects insurance choice in Switzerland. They use a panel survey from the Federal Office for Social Insurance (OFAS). It contains a sample of 2152 individuals and asks about their insurance coverage between 1997 and 2000. Yearly premiums are available at the Federal Office for Public Health (OFSP) website. While there was consolidation in the health insurance market among firms, the average number of health plans offered per canton increased from 39 in 1998 to 52 in 2003. The number of people switching plans was 4.8% in 1997, 5.4% in 1998, 2.7% in 1999 and 2.1% in 2000.

How do people choose their plan?

…40% of people choose a health plan following their parents’ and friends’ choices, and what they see as tradition. Furthermore, as many as 25% individuals declare that they do not strive to pick the health insurance plan with the lowest premium. A substantial number of people explicitly report staying with their health plan based on habit (13.5%) or because they are satisfied with their arrangement (79%)

What do the authors conclude from the data?

First, we show that consumers that switch health plan pay 15% to 16% less in health insurance premiums per month holding ceteris paribus. Second, we show that among consumers expressing dissatisfaction with their health plans those in markets with fewer choices are more likely to express intent to switch. Finally, consumers that used an agent to help them purchase insurance consistently paid significantly lower premiums. This set of results suggests that “mistakes may have been made”.

Despite what orthodox economic theory states, no market is perfect. Understanding these market imperfection imparts important knowledge for economists and health policy makers.

• Richard Frank, Karine Lamiraud, 2008. “Choice, Price Competition and Complexity in Markets for Health Insurance,” NBER Working Paper #13817.

Doctors often complain that health insurers are squeezing their profit margins. These insurers offer the physicians access to patients as part of their network in exchange for discounted fees. Physicians can decide not to join the network and charge higher prices, but may be left with fewer patients. The bargaining power of the health insurer depends on how many patients they are able to channel towards these physicians.

In the U.S., most health insurers restrict provider choice ex ante by using either prohibiting patients from visiting providers outside the network or charging the patients significantly higher co-payment rates if go to a provider outside the network. In the Netherlands, almost all care is free to patients so insurer need to use ex post incentives (e.g.: bonuses, gift certificates, and extra services) in order to entice the patients to use the services of the preferred provider.

A paper by Boonen, Schut and Koolman in the most recent edition of Health Economics examines how well the ex post incentives function in the Netherlands’ pharmacy market. Since pharmacies are regulated and prescription drugs are a homogeneous commodity, quality differences between pharmacies are negligible. The authors use data from two health insurers who attempt to direct their enrollees to specific pharmacies.

Using a multinomial logit framework, the authors find that convenience (i.e.: distance to the pharmacy) has a large impact. The financial incentives offered by health insurer A and B cause many enrollees to use the preferred provider. Health insurer A, however, gave a 10 € for the patient’s first visit to the pharmacy and 5 € for their second visit to the pharmacy. Under this incentive structure, individuals were more likely to switch to the preferred provider and then return to their original pharmacy after the incentives had disappeared. Only 25% of those who switch to the preferred provider continue to use them after the financial incentives disappear.

Health insurer B offered a discounts on products offered at the preferred pharmacy and these incentives were made permanent. Unsurprisingly, enrollees also were more likely to go to the preferred provider after the financial incentive regime was enacted.

One interesting item of note is that Health insurer B’s preferred pharmacy was in the same building as a general practitioner (GP). Since GPs function as gatekeepers in the Dutch system (i.e.: one cannot a prescription without the GPs approval), having the GP in the same building as the pharmacy was a huge convenience. Further, the GP could influence the patient to use the preferred pharmacy.

In summary, it was shown in the Dutch setting that even small incentives can have a large effect on provider choice.

• Boonen LH, Schut FT, Koolman X. “Consumer channeling by health insurers: natural experiments with preferred providers in the Dutch pharmacy market.” 17(3):299-316.

What is the cost of the last article of clothing you bought. This is easy to determine, just check your credit card statement.

Which is cost of health insurance? This answer is more difficult to find. Sure, there is the price of the premium, but different insurance plans have different co-pay/co-insurance levels and different deductible amounts. How do these insurance product design parameters affect the demand for insurance?

This is the question tackled by Marquis et al. (2007). The authors use a nested logit model to examine plan characteristics within the individual insurance market. In their nested logit, the authors assume individuals first choose whether to be insured or not. Then, they must choose which type of insurance (PPO, POS, HMO, etc.). After they choose which type of plan they prefer, then a carrier is chosen. This methodology is based on the work of McFadden (1978).

The authors find an elasticity estimate of -2.0 for plan choice among purchaser. This means that those who are insurer are very price sensitive. However, Marquis and co-authors also find that once a particular company is selected, there are significant switching costs to changing companies. The elasticity of switching companies once a plan type (PPO, HMO etc.) is chosen is only -0.4.

The authors also find that:

…a 3 percent decrease in the actuarially adjusted price (or a 4 percent decrease in the nominal premium) would induce a healthy consumer to switch to a plan with a 50 percent higher deductible. For a riskier consumer, however, it would take a 4.5 percent decrease in the actuarially adjusted premium (or a 5.5 percent decrease in the nominal premium) to make the switch. This suggests that there is potential for selection in consumer-directed health plans—an outcome that concerns many critics of these new plans. In addition, the findings suggest that introducing new high-deductible products is unlikely to play a major role in reducing the number of uninsured.

Consumer education regarding the choice of different plans and help to expand coverage by introducing consumers to low-cost (actuarially) insurance options.

• Marquis MS, Buntin MB, Escarce JJ, Kapur K. (2007). “The Role of Product Design in Consumers’ Choices in the Individual Insurance Market” HSR 42(6) : 2194-2223.
• McFadden, D. 1978. “Modelling the Choice of Residential Location.” In Spatial Interaction Theory and Residential Location, edited by A. Karlquist, pp. 75–96.
  
  Amsterdam: North-Holland.

Typically, economists when economists look at the health insurance market, they focus on the insurance side of it. By this I mean to define insurance as the purchase of a product which will reimburse the buyer in the case of an adverse event. However, one must also look at the concept of protection. Protection is defined as expending a costly effort to reduce the probability of an adverse event. This costly effort, however, will not effect the amount of the loss, only the probability that it occurs.

A seminal paper by Ehrlich and Becker (JPE 1972) finds the optimal levels of self-protection and how optimal self-protection change when insurance markets are introduced. Let us assume that the probability of a loss is p(e) where e is the effort expended and p’<0. An expected utility maximizer optimizes the following function:

• max_e [1-p(e)]*U(I -e) + p(e)*U(I - L - e)

The first order condition is:

• -p’*[U(I -e)-U(I - L - e)]=(1-p)*U’(I -e) + p*U’(I - L - e)

Ehrlich and Becker note that “[t]he term on the left is the marginal gain from the reduction in p; that on the right, the decline in utility due to the decline in both incomes, is the marginal cost.”

When we introduce an insurance market, the expected utility maximizer faces a new objective function.

• max_e,s ,s [1-p(e)]*U(I-e-s*π(e)) + p(e)*U(I - L - e + s)

Here s is the insurance benefit and π(e) is price of the insurance; s*π(e) is the insurance premium. Let U(0)=U(I-L-e+s) and U(1)=U(I-e-s*π(e)). The first order conditions now become:

• -(1-p)U’(1) + p*U’(0)=0
• -p’*[U(1)-U(0)] - (1-p)*U’(1)*[1+s*π'] - p*U’(0)=1

How does self protection change when insurance markets are introduced? According to Ehrlich and Becker “On the one hand, self protection is discouraged because its marginal gain is reduced by the reduction of the difference between the incomes and thus the utilities in different states, on the other hand, it is encouraged if the price of market insurance is negatively related to the amount spent on protection through the effect of these expenditures on the probabilities.”

If insurance companies are actually able to measure self-protection and can price insurance accordingly, then individuals will have some incentive to increase prevention in order to lower their premiums. If insurance is priced in an actuarially fair manner (i.e., π=p(e)/[1-p(e)]) we can show that premiums will drop when self-protection increases:

• ∂π/∂e=p’/(1-p)²<0

However, if insurance companies are not able to observe self-protection efforts, than it is likely that moral hazard will occur–self protection will decrease. In the words of the authors, “Self-protection would then usually be discouraged by market insurance–moral hazard would exist–because the main effect of introducing market insurance would be to narrow the differences between incomes in different states.”

• Ehrlich I, Becker G. 1972. “Market Insurance, Self-Insurance, and Self-Protection.” The Journal of Political Economy, 80(4), pp. 623-648.

According to the San Diego Union Tribune, yesterday PacifiCare was fined $3.5 million and the California Department of Managed Health Care is seeking up to $1.3 billion in additional penalties for “130,000 alleged claims-processing violations…in California between July 1, 2005, and May 31, 2007.” PacifiCare is the second largest HMO in San Diego and the fourth largest health insurer in California.

These violations have prompted California Insurance Commissioner Steve Poizner begin an audit of the eight largest California health insurers to determine whether or not these companies have engaged in similar billing practice.

Joe Paduda of Managed Care Matters argues that the ruling is another piece of evidence which favors a  single-payer system.  Mr. Paduda states:

For those (including me) forever excoriating health systems and hospitals for their outrageous error rates, the debacle at Pacificare, the recently-acquired division of United Healthcare (one of my past employers) make the delivery sector look like a paragon of performance. I’m not overly surprised, as mergers involve systems conversions, the amalgamation of provider networks and contracts, and the shifting of work around to different call centers and processing locations. Duplicate staff positions are identified and people laid off, and when they walk out the door so does the expertise and understanding that enabled the operation to run smoothly.

The question remains, would a single-payer system perform better?  The government is not known as the paragon of efficiency.  With a single payer system, likely one of two things will happen:

• Government administrators will make claims processing errors just as health insurance administrators do now, or
• government administrators will deny less claims erroneously, but this will likely coincide with the acceptance of more unnecessary or false claims, thus increasing overall health care costs.

A single payer system may lead to improved claims processing.  However, for anyone to be convinced that a single payer system is the way to go, one must not only show that the present system is flawed, but that a single payer system is a significant improvement.

Adverse selection is often seen as a major impediment to the efficient functioning of insurance markets. Rothschild and Stiglitz (1976) create a model where high risk people buy full insurance while low risk individuals buy partial insurance. Yet empirically, one finds that in some insurance markets, low risk individuals purchase more insurance than high risk individuals.

An NBER working paper by Cutler, Finkelstein and McGarry (2008) claims that preference heterogeneity may explain this phenomenon. If low-risk individuals also have a stronger risk aversion preferences, than they may buy more insurance than a high-risk individual who has risk loving preferences. This work is an extension of the Finkelstein and McGarry (AER 2006) article discussed in one of my earlier blog posts.

Using data from the Health and Retirement Study (HRS), the authors measure risk tolerance using the following variables: smoking, having 3+ alcoholic drinks per day, job-based mortality risk, receipt of preventive health services, and seat belt usage. The authors find a negative relationship between individuals who engage in risky behavior (i.e., smoking, drinking, and those working in a high-risk occupation) and the percent who purchase various types of insurance, and a positive relationship between those engage in risk reducing behavior (i.e., preventive medical care, seat belt usage) and the purchase of insurance.

In the above chart, ‘+’ represents a positive statistically significant correlation, ‘-’ represents a negative statistically significant correlation, and o indicates that the relationship is not statistically significant.

The authors can also measure risk preferences based on respondents answers to income gamble questions. There is a weak relationship between risk preferences and risk behavior however.

The authors confirm that risk behavior lead to an increased probability of adverse events which would be covered by insurance. For instance, smoking increases mortality which would lead to an earlier life insurance payout. Increased preventive health activities decrease the probability of a nursing home stay.

Thus the authors conclude the following:

Our analysis yields two main findings. First, in all five markets, we find that individuals who engage in what are commonly thought of as risky behaviors (smoking, drinking, or prior employment in jobs with higher mortality rates) or who do not take measures to thought to reduce risk (preventive health activities or wearing of a seat belt) are systematically less likely to hold each of these insurance products. Second, we find that these same individuals tend to have higher expected claims for life insurance and long term care insurance, but lower expected claims for annuities; for Medigap and acute health insurance, there is no systematic relationship between the behavior measures and expected claims.

These results can help to explain the puzzle of insurance we started with: why is adverse selection not more common? In annuity markets, there is clear evidence of adverse selection: people who live longer are more likely to buy insurance. The standard adverse selection model is one explanation for this, but so is variation in risk tolerance; people who have less risky behaviors live longer and are more likely to buy annuities. In life insurance, our results suggest that differential risk tolerance can help explain why people with lower mortality rates have more insurance. Similarly, in the case of long-term care insurance, people who use more preventive care or are more likely to wear seat belts buy insurance more readily but also stay out of nursing homes.

• David Cutler, Amy Finkelstein, Kathleen McGarry. 2008. “Preference Heterogeneity and Insurance Markets: Explaining a Puzzle of Insurance,” NBER WP #13746.
• Finkelstein, Amy and Kathleen McGarry. 2006. “Private information and its effect on market equilibrium: new evidence from long-term care insurance.” American Economic Review 96(4): 938 – 958

Many of the Democratic candidates support having employers provide insurance for their employees with the threat of a fine or tax if an employer decides not to comply. This of course will increase the cost of an employee for firms. If employees truly value the health insurance, then the cost of insurance can be passed on to the employee through lower wages.

This cannot happen, however, if you are a low-wage worker whose wage is at or near the minimum wage. This is, of course, because employers can not pay wages below the minimum. Thus, a “Pay or Play” mandate may reduce employment for the lowest skilled workers. A paper by Baicker and Levy examines this issue.

The authors find the following:

“The authors calculate the average cost of a health insurance plan to be about $9,000 for family coverage during their sample period, or $3.66 per hour for a full-time worker. Assuming that a mandate required employers to provide coverage similar to the average plan and to pay 80 percent of premiums, wages would need to fall by $3 per hour to fully offset the cost of the mandate.

The authors estimate that one-third of all uninsured workers, or 5.5 million U.S. private sector workers, have earnings within $3 of the minimum wage.

…the authors estimate that the implied increase in compensation resulting from the mandate would cause 224,000 workers to lose their jobs. The affected workers would be disproportionately low education, minority, and female.”

From the NBER Fall 2007 Bulletin on Aging and Health.

According to the N.Y. Times (”…Benefit Cut at 65 in Retiree Plans“) in 2001it is estimated that one-third of large employers and fewer than one-tenth of small employers offered health benefits to retirees.  These numbers may trend towards zero in the near future after an Equal Employment Opportunity Commission (EEOC) ruling.

NPR’s Marketplace reports (”Employers let off one health-care hook“) the EEOC has ruled  “that companies can cut their retirees’ health-care benefits once they turn 65.”  This will lead to more government provided health care.  Is this a good thing?

Businesses will certainly benefit from not having to be in the business of planning for the health insurance of seniors.   According to the N.Y. Times, Dianna B. Johnston, a lawyer for the commission, said many employers and labor unions had told it that “if they had to provide identical benefits for retirees under 65 and over 65, they would just drop retiree health benefits altogether for both groups.�?

Further, a paper by Gopi Shah Goda, John B. Shoven, Sita Nataraj Slavov (reviewed on 10 Oct 07) claims that having Medicare as a Secondary Payer (MSP) creates an implicit tax for elderly workers.  The authors find that the tax is 15-20 percent at age 65 and increases to 45-70 percent by age 80.  While the authors claims are based on how MSP effects seniors’ incentives to work, it does not comment on whether or not implicit contracts guaranteeing retirees right to private insurance should be abolished or not.

In essence, this ruling is a transfer from retirees to businesses.  Retirees who believed they would receive private health insurance from their employer now must rely on Medicare or pay for private insurance in the individual market.  Businesses benefit from being able to eliminate costs from insuring retirees.

This raises the larger question of who should be paying for health insurance.  The government could do it, but this may lead to a monopolistic system with little choice and a potential for corruption.  Individuals could buy their own insurance, but without a mechanism to pool risk, sick individuals will have to pay significantly higher premiums than healthy individuals. Insurance is supposed to insulate individuals from income shocks due to changes in their health status and an individual market will not be able to accomplish this goal.  A natural risk pooling institution is the employer, but employers do not want to be in the business of planning their employees (large) health insurance choices.  Who should pay for health care is at the crux of the health care debate and needs to be resolved before policy reforms are implemented.

Recently, there has been much controversy regarding whether or not the RAND Health Insurance Experiment (HIE) results are truly robust. Many blogs have been questioning the results (see here, here and here). One of the major conclusions of the HIE are that higher co-insurance rates lead to lower levels of medical utilization and lower medical cost, but do not have any adverse impact on health outcomes.

A paper by John Nyman (2007) in the Journal of Health Politics, Policy and Law calls these findings into question. He notes that there was differential attrition in the insurance plans with cost-sharing for the patients compared to those with no cost-sharing. If people who became sick in the cost sharing insurance plans elected to drop out of the experiment and seek care from their previous insurance plan, then an attrition bias would occur. This bias would incorrectly deflate the medical utilization of the cost sharing group and thus lead to the erroneous conclusion that more cost sharing causes lower medical utilization patterns.

Nyman’s paper also wisely notes that moral hazard is only a problem with individuals afflicted with a disease. For instance, no matter if one has insurance that would reduce the price of a mastectomy to zero, no one ever elect to have a mastectomy unless they had breast cancer. There are personal costs of the side effects of treatment and time costs which imply that moral hazard will generally only be a problem for those afflicted with a disease. There are exceptions. For cosmetic surgery procedures, individual do not need to be sick to suffer from the problem of moral hazard with insurance.

Nyman’s points are valid, but I believe that the RAND HIE results are robust. First, each RAND HIE participant receive a participation payment each month. Even if the individual had large medical expenses and had to pay a large deductible (capped at $1000, which $4000 in 2007 dollars), the monthly participation fees would add up to more than $1000 so it was in the individual’s best interest to stay in the experiment. Nyman argues that cash flow problems many have affected some participants. If I receive $100 per month for a year, but have $1000 in medical expenses today, I may decide to leave the experiment. Yet because of this participation fee, it seem that this would not be a major problem.

Also, the problem of attrition was recognized in the original RAND HIE. Nyman himself states on his website:”When the RAND data were re-analyzed to account for the differential utilization from attrition, the difference in hospitalizations between free care and all cost-sharing arms was about 19 percent, not 25 percent as has been reported (Manning, Duan, Keeler, 1993, p. 13).” While the magnitude of the cost sharing effect may be somewhat smaller once we take into account attrition, the general finding remains the same: more cost sharing leads to less utilization.

Finally, while RAND is the only large scale RCT that has been conducted, many other studies have shown that increased cost sharing leads to lower medical utilization. Newhouse states that “enormous number of observational studies over many years, in many settings, with many different methodologies, that find utilization of medical services responds to relatively modest cost sharing.” Nyman’s response is that:

“I do not dispute that cost sharing reduces utilization. I think it does and agree that the non-experimental studies that Newhouse et al. (2007) refer to are generally convincing. The issue that I am addressing, however, is whether cost-sharing in the RAND Experiment actually produced a 25 percent reduction in equally effective hospitalizations and whether such a reduction would actually have no effect on health.”

One question you may still have is how is it possible that lower medical utilization leads to the same health outcomes. One possibility is that the moral hazard may have resulted in only the excess use ineffective medicine. It could be the case that much of medicine has little impact in the overall health of the patient and too much treatment can actually harm the patient (see my post on Overtreated). It could be the case that health was measured poorly by the HIE, but Nyman concedes that a “broad spectrum of health status measures” where used in the RAND experiment.

Overall, I do believe Nyman brought up some reasonable points. No experiment is ever perfect…even the RAND HIE. Attrition was a problem and may affect the magnitude of the result. Nevertheless, the conclusions from the RAND HIE remain robust and I believe that the attrition issue was addressed previously.

Can we still conclude that more cost sharing reduces medical utilization? Is moral hazard a problem in health insurance markets? We can still confidently say: YES!

• Nyman, John A. “American Health Policy: Cracks in the Foundation,” Journal of Health Politics, Policy and Law vol. 32, no. 5, October 2007, pp. 759-783.
• Newhouse et al. (2007) “Attrition and Refusal in the RAND Health Insurance Experiment” (from Newhouse and the Insurance Experiment Group, Free for All: Lessons from the RAND Health Insurance Experiment, pages 17-26).
• Nyman, John A. (2007) Attrition in the RAND Health Insurance Experiment: A Response to Newhouse et al. (2007).
• Manning, Willard G., Joseph P. Newhouse, Naihua Duan, Emmett B. Keeler and Arleen Leibowitz. “Health Insurance and the Demand for Medical Care: Evidence from a Randomized Experiment.” American Economic Review, 1987, 77 (3), pp. 251-277.

When I pay for health insurance, is most of my monthly premium going for medical care?  Or does most of the money go towards administrative expenses and insurance company profit?

John Aloysius Cogan Jr. of the Regulating Health Insurance blog finds that most of the money spent on insurance premiums in fact goes towards providing medical care.  The post looks at two Northeastern insurance companies: Blue Cross & Blue Shield of Rhode Island and UnitedHealthcare of New England.  The results are as follows:

While the administrative and profit costs are much higher for these two firms than for Medicare, the higher admin cost percentage does not tell the whole story. As mention on my July 27, 2006 post,  Medicare does not take into account the deadweight loss from the taxation needed to raise money to fund Medicare.  Further, Medicare assumes a zero cost of capital and likely is less vigilant about pursuing unnecessary claims than a private insurance plan.  And finally, a lower administrative cost may simply be due to the fact that Medicare spends more money per person (i.e.: the denominator of the administrative expense percentage grows large).

In 2005, for small employers, BC/BS cost $399/month and United Healthcare cost $392/month. The Regulating Health Insurance blog notes the following:

“Even if Blue Cross and United had slashed their 2005 small employer market administrative costs and profits by one-third, their base rates for 2005 would have still been quite high. Blue Cross’ rate would have been $377.30/mo. and United’s would have been $361.35/mo.

Wal-mart recently released the details of its new health plan for 2008 (see company press release or the Houston Chronicle article).  Here are some highlights of the plan.

• Employees now have “50 ways of customizing their health care coverage options…a substantial increase from last year, when most associates had only nine choices.”  However, it seems that the employees will not be able to choose different coverage options (i.e.: what medical procedures are covered), but can only alter their insurance on the dimensions of the deductible/health care credit and thus their premium.  More choices may be good, but it also may create an adverse selection death spiral in which the more generous plans become more and more expensive in the future.
• All Wal-mart employees will have deductibles (up to $2000 in the case of the cheapest plan), but employees will also receive a health-care credit of $100, $250 or $500.  I believe that that the reason for the credit is so that employees don’t forgo, low cost preventative measures (e.g.: regular doctor check-ups, immunizations) simply because they would have to pay out of pocket.
• There is no maximum insurance coverage which is good.  Insurance is made alleviate the risk of large-scale medical problems.
• Their plan offers $4 co-pay for over 2,400 covered generic prescriptions.

The Houston Chronicle reports:

As of the start of this year, 47 percent of Wal-Mart’s 1.34 million U.S. employees were enrolled in company coverage, compared with 46 percent a year earlier and 43 percent at the start of 2005.

Wal-Mart has said most of the remainder are insured through other plans, such as a spouse’s or a second job. That justifies its contention that 90 percent of employees have health coverage.

I am not sure whether this 90% figure is reliable.  It may count spousal coverage, but may also include those on Medicare or Medicaid, which would mean that John Q. Public would be footing the bill for these employees and Wal-mart should not implicitly take credit for providing insurance to these employees.

Is this good?

Having Wal-mart offer health insurance is not an unequivocal good thing.  When Wal-mart offers affordable health insurance plans, that means that Wal-mart will be a more desirable place to work.  The supply of individuals willing to work for Wal-mart will increase and thus the wage of Wal-mart employees will decrease.  In a reality with sticky wages, wages will likely not decrease, but the rate of increase of future Wal-mart employee wages will be lower than the wages of similarly-skilled employees working at companies without health insurance.  Risk loving people will not appreciate that some of their wages are taken to pay for health insurance.  Risk averse individuals–which likely represent the majority of Americans–will fully value the increased health benefits and will not mind a slight wage decrease.  Further, because of Wal-mart’s buying power, they will receive less expensive, more comprehensive health care costs than they would have on the non-group market.

Despite much public rhetoric, why is preventative and chronic care so poor in the U.S.? The easy answer is that patients switch plans so frequently that insurance companies who invest in preventative care will incur the cost, but not reap the benefits. The harder question is why patients are switching health plans.

According to a working paper by Cebul, Herschman, Rebitzer, Taylor and Votruba featured on Slate, the answer may be “search frictions.” In the paper, turnover is generated from two sources: 1) from employees leaving the company for new jobs and 2) by having the employer switch to a new health plan. Data from the Community Track Study in 1996/7, 1998/9, 2001 and 2003 show that average annual insurance cancellations are about 21%. More than one third of the turnover is caused by employers switching health plans. Small employers were more likely to switch insurance plans than larger employers. Why don’t they just stay with one plan?

The search friction model is developed from a labor economics paper by Burdett and Mortensen (1998). The authors argue persuasively that extending the model to the case of health insurance makes perfect sense.

“The market for health insurance is a natural place to expect search frictions. Health insurance is a complex, multi-attribute product and this complexity makes it difficult for clients to meaningfully compare more than a handful of proposals. Informal discussions with insurers suggest that they offer customers hundreds if not thousands of different policies. This complexity also makes the marketing of insurance costly so that companies can make only a limited number of appeals to employer groups in a period.”

The authors explain how the price friction mechanism works. The price of the insurance policy is p, the marginal cost of the policy is c, and the firm’s reservation price for buying insurance is p^R.

Suppose all firms made the same price offers p=c and so earned zero profit. Then one maverick firm could clearly increase profits by charging some discretely higher price (less than or equal to the reservation price p^R). This high offer would be rejected more frequently than the going price because any potential client who fielded more than one offer in a period would obviously reject the high offer. But on occasion the contacted client would have no other offers, and a policy would be sold. This would produce positive profit for the firm. Similarly, in a candidate equilibrium in which all firms were charging the same price (a price such that c<p<p^R ), a maverick firm could always increase profit by undercutting slightly the price charged by competitors, thereby increasing the number of clients while reducing by profit per client by only a trivial amount. In short, an equilibrium must entail a distribution of price offers.

Once market friction reach a sufficient level, in equilibrium we will observe a churning of employers going through different insurance policies each year. Introducing the issues that come along with adverse selection is likely to only increase market frictions because insurance companies now will want to screen employees.

Possible Solutions

The authors offer arguments made that may be solutions to the problem.

• Patient-financed health investments. Health care investments (i.e.: preventative care) should be financed by the client. This way, the person reaping the rewards from preventative care will also incur the costs. If the patient switches insurance plans, this will not be a problem since they will be eligible for lower premiums because of their preventative care history. On the other hand, determining what type of care is an expense and what is an investment may be very difficult practically. Further, shifting more risk onto the patient is the antithesis of what insurance is supposed to do. Finally, when switching insurers, it will be very difficult to verify the actual amount of preventative care received without a nation-wide standard for electronic medical records.
• Long term contracts. Another simple solution is just for employers to purchase long term contracts from insurance companies. This way, insurers will be able to reap more of their rewards from earlier years’ health investments. On the other hand, “given constantly-evolving medical technology and treatment protocols, as well as hard to predict changes in governmental regulation and mandates, it is difficult to see how long-term contracts might be implemented.”
• Price Caps. Government set price caps are probably the worse option. As Slate states, “But where should the government set the ceiling? If it’s too low, the government could end up destroying insurance companies’ incentives to stay in business at all.”
• Legislate a basic insurance package. The authors conclude the paper with the following: “It follows from this that much of the distortions resulting from frictions could be mitigated if there were a simple, easily understood and reasonably priced alternative insurance policy that would be available to all market participants. In the context of our search models, we believe we can prove that by making this alternative insurance available on a voluntary basis to all purchasers the inefficiencies resulting from search frictions could be greatly reduced.” Another option would be to offer everyone the choice of a nationalized health plan (a la Medicaid). People who did not want Medicaid, could choose to have vouchers (see Healthcare Vouchers) used to pay towards a private insurance plan of their choice. Many of the basic private insurance plans will likely mimic the nationalized Medicaid, but some plans will offer alternatives which will be more flexible and easier to adapt to new technology advances.

In a blog post (”Sicko Sticko Shock“), Marc Cooper discusses his recent hospital bill for a heart procedure of “moderate complexity.” He finds that the amount billed was $116,749. However, the procedure was much cheaper for Mr. Cooper since he had Blue Cross insurance. “In a column lateral to the “amount billed” I then find the “amount allowed” i.e. the amount that Blue Cross is actually willing to pay the hospital. That amount: $4730, or less than 4% of the total charge.” Further the $4730 was paid for entirely by his insurance company. Mr. Cooper wonders how he could have paid the $100,000 if he wasn’t insured. He concludes that “the system is absurd, insulting and inhuman.”

The Coyote Blog states (”You better shop around“) that the conclusion shouldn’t be that the current health care system should be scrapped, but instead that “we should find a way to have individuals experience both the cost and benefits of care, because only they can make these tradeoffs for themselves and shop around for better options.” The Coyote Blog makes the following analogy:

Sure, this [hospital bill] looks like a rip-off. But if you went in to buy a car, concerned only with the quality of the car, and never asked the price and then got a bill for $100,000 a few weeks later, would you be surprised? Would anyone give you sympathy if you complained you paid $100,000 for the car but admitted you never asked what the price was? So this is a dead-obvious outcome from the health care system we have, where no one has the incentive to shop.

This is of course the moral hazard trade off with insurance. People buy insurance because they are risk averse and fear an extremely medical care…or care repairs…or home repairs…or in whatever other areas people buy insurance. When one buys insurance, however, there is the moral hazard problem that people will not shop around for a better deal, they may not take as many precautions to protect their health if they know their insurer will pay for treatment. However, insurance is economically optimal when people are risk averse. Finding the correct balance between insuring people against losses while minimizing moral hazard is a delicate and difficult matter to resolve empirically–especially in the health care setting with so much asymmetric information and uncertainty.

Should hospitals with long waiting times have higher or lower budget transfers? Offering hospitals who have low wait times more money will increase a hospital’s incentives to decrease wait times. On the other hand, thus policy may hurt the busier hospitals and may not alleviate the wait times of those who are waiting the longest. In the case of public school transfers, if the best schools are rewarded, this encourages achievement, but may punish the worst off kids (i.e.: those at poorer schools). Transfers to low-performing school may mute incentives to increase achievement.

The issue of hospital payment structure is analyzed by Luigi Siciliani in his article on optimal contracts B.E. Journal of Economic Analysis & Policy. As with any thesis which claims to give an optimum solution, this optimum is based on some assumptions. This paper uses four major assumptions.

1. Demand for treatment can be controlled by dumping some patients. Doctors can tell patients who wish to have medical treatment that they either a) don’t really need it or b) that they will not provide it
2. The purchaser (i.e.: NHS, an insurance company, Medicare, etc.) can not observe the number of people dumped.
3. Dumping is costly for the specialist. By dumping patients, the specialist receives more complaints about their service level. Thus, either the physician’s reputation is tarnished (a cost) or the physician must spent more time (another cost) convincing the patient that they do not need treatment.
4. Hospitals differ in potential demand for treatment, either due to the catchment area of the hospital or from having a better or worse reputation.

Another key assumption is that no co-payment charges can be issued. This assumption is plausible, because it basically represents the British NHS system. Thus, the optimal solution must be seen not as the ideal optimal, but as the optimal with a centralized payer and no co-payments.

The Model

Hospitals have parameter θ which describes the public hospital type. This parameter θ indicates potential demand in the absence of a rationing system.

For each treatment, patients differ in the value they would receive from treatment. For instance, healthy patients would not benefit from heart surgery, but individuals with coronary artery blockages likely would benefit from surgery. Thus the author assumes that individuals’ value from treatment is uniformly distributed between v₀ and v₁.

Patients have three options:

1. They can be treated at a public sector hospital after a wait of time w, [u^p(v,p)]={∫^T₀ v dt} -p=vT-p]
2. They can be treated in a private sector hospital with no wait, but pay a price of p, [u^NHS(v,w)]={∫^T_w v*g(w) dt} =vg(w)(T-w)]
3. or they can receive no treatment[u^none=0]

There are two costs to going to the public hospital. First, the individual has to wait w weeks longer, so they do not get to enjoy the benefit of the treatment for as extended a period of time. Secondly, since 0<g(w)<1, the treatment becomes less effective or less valued the longer the patient waits.

Thus, from the math above, we can see that a person will choose a public hospital if and only if:

• v<V(w)=p/{T-g(w)*(T-w)

The comparative statics show that longer wait times decrease the probability of using a public hospital, higher prices, p, decrease the probability of using a private hospital, and higher valuations, v, increase the probability of using a private hospital.

Demand for public hospital services is written as:

• D(θ,w,x)=θV(w)-x
• x is the number of patients who are dumped (i.e.: not added to the waiting list)

The number of treatment supplied by hospital θ is y(θ) and since supply must equal demand, we have:

• θV(w)-x=y(θ)

The authors claim that providers receive disutility from dumping patients. Also, hospitals receive more disutility when they dump patients who value the treatment more (i.e.: high v, this is more likely to be the sicker patients). Thus, we are lead to our first major conclusion.

• Conclusion 1: The patients who are dumped are the ones with the lower benefits from treatment. This means that hospitals dump the patients who don’t really need the treatment.

After some more math, the Dr. Siciliani states a second conclusion:

• Conclusion 2: A mix of explicit rationing (through dumping) and implicit rationing (through waiting) is therefore optimal. Siciliani explains that: “Rationing by waiting alone induces excessive disutility for patients. Rationing by dumping alone generates excessive disutility for the specialists.”

The author continues to conclude that a separating or pooling equilibrium may occur.

“Under symmetric information, the optimal contract is for the purchaser simply to over a transfer in exchange for the provision of the desired level of activity and waiting time, without leaving any rent to the provider…Under asymmetric information, we found that a separating equilibrium exists when it is optimal for the purchaser of health services to contract more activity and higher waiting times to hospitals with higher demand. In this case providers with low potential demand have an incentive to mimic hospitals with high potential demand. To induce hospitals to self-select, the purchaser needs to pay a rent to hospitals with lower potential demand. [But] if it is not optimal for the purchaser to contract more activity and higher waiting time to hospitals with higher demand, then a separating equilibrium may not exist.”

Problems

One main problem with the paper is that it assumes that patients with a high value, v, cost the same to treat as low value patients. If v is a proxy for sickness, this is likely not to be the case; sicker patients with a high v are more expensive to treat. If this were the case, then conclusion 1 would not hold. Public hospitals would instead treat patients with the lowest benefit and dump patients with intermediate benefits–the high benefit patients would still go to the private sector hospital.

Also, the paper does not take into account any strategic interaction between hospitals. “If hospitals with higher potential demand are contracted higher waiting times, then patients will switch from the hospitals with high potential demand to hospitals with low potential demand, increasing excessively the amount of dumping and consequent disutility for hospitals with low potential demand.”

• Luigi Siciliani (2007) “Optimal Contracts for Health Services in the Presence of Waiting Times and Asymmetric Information,” The B.E. Journal of Economic Analysis & Policy: Vol. 7 : Iss. 1 (Contributions), Article 40.

What is the optimal way to pay physicians? If there were a singular variable ‘health’ that could be easily measured, patients could pay physicians for each unit of health they receive. Of course, this is not how the physician-patient relationship operates in the real world. Physicians are paid either a base rate per person per month or receive a fixed fee for each service provided. In physician contracts with health plans, the physician effort level to gather information (diagnosis) is non-contractible and pay based on the patient’s health condition (physicians’ private information) is also non-contractible. In a setting with so much uncertainty, what is the optimal physician contract?

This is the question which Izabela Jelovac attempts to answer in her 2004 paper in Health Economics. In her model, pa