April 2007

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Health care systems in East Asia

April 18, 2007 in Academic Articles, International Health Care Systems | Permalink

A recent Health Economics article by Adam Wagstaff gives a good comparison of five East Asian countries: Japan, Hong Kong, Korea, Singapore and Taiwan. While Japan (1961), Korea (1989) and Taiwan (1995) have introduced universal health insurance, Singapore and Honk Kong have not. Singapore began using medical savings account (MSAs) in 1984, but MSAs only make up a 8%-10% of health care spending. Below is a table which summarizes some of the distinctions between the health care systems in each of the five countries.

  Hong Kong Japan Korea Singapore Taiwan
Finance Taxes, OOP Soc. Ins. Soc Ins., OOP OOP Soc Ins., OOP
Who pays? Progressive Regressive Proportional   Proportional
Payments FFS FFS FFS FFS FFS
Clinic Ownership Private Private Private Private Private
Hosp. Ownership Public Private Private Public Private
           

Financing the Health Care System

From the chart above we can see that there are a variety of mechanisms to pay for medical care. Private health insurance pays for less than 10% of care in all of these countries, likely due to the universal health insurance (UHI) introduced in 3 of the countries. These three countries with UHI systems are mostly funded through a social insurance scheme. Hong Kong mainly uses money from general revenues while most citizens of Singapore pay for a large portion of their medical care from their own pockets [i.e.: out-of-pocket, (OOP on the chart)].

Because Hong Kong relies so heavily on general revenue and because taxation is progressive, Hong Kong has the most progressive health financing system. Japan has the most regressive system due to the fact that its social insurance scheme has contribution ceilings.

Payment and Ownership structure.

All five of the countries pay primary care providers on a FFS system, but some are experimenting with per diem rates for secondary and tertiary care. Japan uses a ‘diagnostic-procedure combination’ (DPC) groups for the prospective portion of its payments to hospitals. Taiwan has attempted to use a DRG system for the 50 most common diseases and Korea launched a DRG pilot program in 1997 for inpatient care.

Primary care clinics are privately owned in all countries and hospitals are privately owned in Japan, Taiwan and Korea. In Hong Kong, general revenue funds hospital operations. In Singapore, the government has created a single corporation which now controls about one quarter of Singapore’s hospitals and one half of its stock of beds.

Me too drugs

April 18, 2007 in Pharmaceuticals | Permalink

There is a very interesting series of blog posts at the Economist’s Free Exchange blog.

Here’s a quotation from part I: “In what other industry does anyone under the age of sixty still believe that each product category should have one, and only one, product produced by a single company—that competition is not a sign of a healthy market, but profligate waste? Has not one person making this argument (doctors included!) ever had to try multiple drugs for a condition until they found one that worked, or had bearable side effects?“

The growth of convenience clinics

April 17, 2007 in Nonphysician Clinicians | Permalink

About a year ago (“Attention Shoppers“), this blog noted the rapid expansion of walk-in health clinics staffed by nurse practitioners. This week, the Economist magazine (“McClinics“) highlights growing popularity of walk-in clinics such as RediClinic, MinuteClinic, and Health Stop. Patients appreciate the convenient locations, shorter wait times, and lower costs.  More information can be found at the Health Care Law Blog.

Seemingly Unrelated Regressions

April 17, 2007 in Econometrics | Permalink

Let us pretend you have a system of M equations, with N observations for each equation. For example, if we are estimating supply and demand independently over 20 years, M=2 and N=20.

If each of the regressors is predetermined in each equation and we have an exclusion restriction, we can use the Seemingly Unrelated Regressions (SUR) methodology to improve the efficiency of the estimates. SUR is simply computing the generalized least squares (GLS) estimate in the multivariate case. A more detailed explanation is given here.

An example is the following:

  • PTS = α0 + α1EXP + α2MIN + u
  • REB = β0 + β1EXP + β2MIN + β3HT + v

Let us assume each basketball player’s points are a function of only their years of experience (EXP), the number of minutes they play per game (MIN) and a constant. The number of rebounds they get per game is also a function of a constant, EXP, and MIN but the person’s height (HT) also affects their rebounding totals. This system of equations would be the same as:

  • PTS = α0 + α1EXP + α2MIN + α3HT + u
  • REB = β0 + β1EXP + β2MIN + β3HT + v

where α3 was constrained to be 0. The fact that α3 is constrained to be 0 is our exclusion restriction. SUR uses a typically instrumental variables approach but our vector of instruments, z, is equal to the union of the regressors from all equations.

  • z=union of (x1,…xM)

In this example, M=2 so: x1=(1, EXP, MIN)’; x2=(1, EXP, MIN, HT)’; z=(1, EXP, MIN, HT)’. Our orthogonality conditions are that E(zu)=0 and E(zv)=0. Our parameter estimates become:

  • δ= …[σ11A11 , σ12A12 ]-1[σ11c11 , σ12c12 ]
  • ……..[σ21A21 , σ22A22]….[σ21c21 , σ22c22]

Amh=n-1Σi ximxih.

cmh=n-1Σi ximyih.

OLS can also be used because the regressors are predetermined. In fact, if each equation is just identified, SUR is mathematically equivalent to OLS. If at least one equation is overidentified—which would be the case in the first (PTS) equation in our example—then SUR is more efficient than equation-by-equation OLS.

For more information of Seemingly Unrelated Regressions, see Hayashi (2000) Econometrics, pp. 279-283.

Simultaneous Equation Bias

April 16, 2007 in Econometrics | Permalink

One estimation procedure preformed by many novice economists is to use OLS to regress quantity on price. Let us assume the following framework (omitting the i subscripts on the variables):

  • qd = α0 + α1p + u
  • qs = β0 + β1p + v
  • qd = qs

If we regress qd on a constant and p in order to try to estimate the demand equation for some good, the OLS estimate of α1 is given by the formula α1OLS =Cov(p,q)/Var(p). I solve Cov(p,q) below:

  • Cov(p,q)=Cov(p, α0 + α1p + u)
  • = E(α0p + α1p2 + pu) – E(p)*E[α0 + α1p + u]
  • = α1Var(p) + Cov(p,u) [1]

To find Cov(p,u) we can solve the first system of equations above.

  • p= [(α0 - β0) + (u - v)]/(β1 – α1)
  • Cov(p,u)= Var(u)/(β1 – α1) [2]

So, substituting [2] into [1], we have:

  • Cov(p,q)= α1Var(p) + Var(u)/(β1 – α1)

Thus, our bias term for the OLS regression is:

  • Cov(p,q)/Var(p) – α1 = Cov(p,u)/Var(p) [3]

Since we see in equation [2] that Cov(p,u) is not equal to 0 unless Var(u) = 0—which is unlikely—we know the OLS estimate is biased. This phenomenon is known as simultaneous equation bias or endogeneity bias. The problem is that the error term (u) is correlated with the independent variable (p). The main way to solve this problem is to use an instrumental variables methodology.

How to fix L.A. traffic

April 15, 2007 in Current Events, Economics - General | Permalink

As a resident of Southern California for the last 3 years, I have gained intimate knowledge of the price of perfect weather: traffic.  How do you fix traffic in a “a sprawling mid-density city” such as Los Angeles or San Diego?  This Sunday’s L.A. Times (“How to fix traffic”) gives some suggestions that most economists would agree with.

  • End the MTA’s monopoly: The Metropolitan Transportation Authority has a “virtual monopoly” on public transportation in the Los Angeles area.  Monopolies always raise prices and reduce choices.
  • Increase parking meter rates: Pricing metered, on-street parking spaces at a significant discount compared to parking lot prices gives drivers the incentive to cruise around the city looking for these discounted meters.  This increases traffic and creates more pollution in the city.
  • Creating a better bus system: Make it easier to ride the bus by creating more connecting services
  • Turn carpool lanes into toll lanes: An article in Friday’s L.A. Times (“State’s drivers…“) shows that despite an increase in the number of drivers and the number of cars on California’s roads, the amount of gasoline used between 2005 and 2006 actually declined due to the increase price of gas.  If high volume freeways had toll lanes—where the fare could vary depending on whether or not it was rush hour—it is likely that traffic would drop.  In London, commuters pay a tax of $16 in order to drive in the city during rush hour; this initiative has significantly reduced traffic.

The article even has a catchy ending: “If L.A. is to continue growing, Angelenos do have a choice: They can pay more time in traffic delays on free roads, or they can pay more in tolls to avoid traffic. But either way, it’s gonna cost them.”

A drastic decision

April 13, 2007 in Current Events | Permalink

Anna Gorman was faced with a terrible decision: remove her ovaries and be faced without a life with the children she desired, or keep the ovaries and face a 54% higher chance of ovarian cancer and 81% chance of breast cancer.  Mrs. Gorman has the BRCA1 genetic mutation which puts her at great risk for many types of cancer.  In fact, her father—who had the same gene—died of cancer at age 59.  A story in the Los Angeles Times (“A threat of cancer…“) describes Mrs. Gorman’s dilemmas concerning child bearing and her personal health, as well as life and death in general.  The portrayal is very moving.

Market for elective surgery

April 13, 2007 in Academic Articles, Hospitals | Permalink

A frequent topic of investigation in health economics is to estimate the elasticity of the demand for medical procedures with respect to wait times.  A paper by Martin, Rice, Jacobs and Smith in the Journal of Health Economics uses quarterly data from 200 English hospitals between 1995-2002 in order to separately estimate the supply and demand curves for elective surgery.  On the demand side, patients care about the cost of the surgery as well as the quality of the doctor.  Quality is comes in two forms: clinical quality (i.e.: health-related outcome measures such as QALYs) and responsiveness (i.e.: notions of patient autonomy and convenience).  Clinical quality is measure by the mortality rate of each surgery, the staff sickness rate and the staff surgery rate.  Responsiveness is measured by patient wait times.  On the supply side, hospital managers care about the volume of care and quality of care as well as managerial effort. One issue to deal with is that British patients can elect to have either NHS or private treatment, but if NHS treatment is chosen then provider choice is usually limited.   Price is approximately the same for each person; the only difference in terms of cost is implicit cost of the accessibility of private facilities.  Thus, the authors include a term for ease of access to private acute hospital beds.  More private hospital bed availability should decrease demand for NHS services.
The major problem with estimating supply and demand separately is that the residuals of the two regressions could be correlated.  Since the demand and supply equations are overidentified (i.e.: there are explanatory variables in the demand equations which do not appear in the supply equation, and vice versa), the authors can use a seemingly unrelated regressions (SUR) framework.  Also, because of the time series nature of the data, a lagged dependent variable is also employed in some specifications.

Results

As predicted the authors find that longer wait times decrease demand.  The estimated elasticities are similar to figures found in  earlier studies [Martin and Smith 1999 (-.021), Gravelle et al. 2003 (-0.21), and Dusheiko et al. 2005 (-0.10)].   The SUR estimates give a lower elasticity of demand than those obtained with OLS.  A more surprising result is that longer wait times increase supply in terms of the number of admissions from the waiting list and the number of outpatient referrals seen.  The authors found the elasticity of supply with respect to wait time was small however 0.05 to 0.10, whereas Martin and Smith (1999) found an elasticity of supply of 2.93 and a later paper [Martin and Smith (2003)] found an estimated elasticity of supply of 5.29.

China’s short on water

April 12, 2007 in Current Events | Permalink

For those who were interested in my post earlier today on water quality in developing nations, NPR’s Marketplace has an interesting story on the high level of pollution in China’s lakes and rivers.

Fighting Diarrheal Diseases in Developing Countries

April 12, 2007 in Health Care in Developing Nations | Permalink

One of the UN Millennium Goals is to halve by 2015 the proportion of people without sustainable access to safe drinking water and basic sanitation. We know that large-scale investments in piped water have dramatic impacts on reducing childhood mortality. Piped water, however, may be prohibitively expensive for the nations to provide to rural residents in low-density areas. Thus, we need to find clean water alternatives for the 926 million people without access to a clean water source who are living in the rural areas of developing countries.

According to a paper by Iyer et al. 2006, nearly all of the $5.5 billion the World Bank invested in rural water and sanitation programs during 1978–2003 focused on improving water supply sources and quality through interventions such as well digging. During my time in El Salvador, many of the NGOs there were digging wells to provide clean water to the residents.

A recent NBER working paper by Alix Peterson Zwane and Michael Kremer, however, suggests that well digging is not an effective means to reduce diarrheal diseases. This diarrheal diseases kill over 2 million children in developing countries each year. One of the major reasons for this are the significant maintenance costs which need to be incurred each year in order keep the well functioning. In fact, one third of rural water infrastructure in South Asia is believe to be not functional. Other studies found that more effective rural interventions included: exclusive breastfeeding, immunization, oral rehydration therapy, micronutrient supplementation, point-of-use water treatment systems, and increased hand washing.

Careful evaluation of future clean water initiatives is necessary in order that money spent on infrastructure in the developing world is used in the most effective manner possible.

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