17 Jan Substantial uncertainty

1. Unlike with most types of goods, deriving a demand curve for health care is quite simple because people rarely skimp on health care.

2. The RAND study was especially useful for measuring price elasticities because it randomly assigned insurance plans to participants (as opposed to letting them choose).

3. The Oregon Medicaid Experiment is not truly “randomized” because lottery winners did not all end up with insurance, and some lottery losers did end up with insurance.

4. The RAND HIE found that people assigned to the free health plan had the same rate of hospitalization as people assigned to the cost-sharing plans.

5. In the RAND HIE, the arc elasticity of demand for inpatient care was larger (in absolute value) than the arc elasticity of demand for outpatient care.

6. Unlike the usual measure of elasticity, an arc elasticity can be calculated from just one price-quantity data point.

7. Both the RAND and Oregon studies find that demand for health care is approximately unit elastic, that is, ? ?1.

8. In the RAND HIE, being assigned more generous insurance did not generally improve participants’ health outcomes, except among certain subgroups.

9. To date, no major health insurance experiment has studied the impact of uninsurance, just different levels of insurance.

10. Results from the Oregon Medicaid Experiment suggest that having health insurance has a positive impact on health status.

11. Suppose you are collecting data from a country like Japan where the government sets the price of health care. Each prefecture in Japan has a different set of prices (for example, Tokyo has higher prices than rural Hokkaido). Data for 1999 are displayed in Table 2.12.

Table 2.12: Outpatient utilization

in Tokyo and Hokkaido, 1999.

Region Outpatient visits Price/visit

Tokyo 1.25/month 20U

Hokkaido 1.5/month 10U

(a) What is the arc price elasticity of demand for health care consumers in Japan (using only these data)?

(b) Suppose that incomes are generally much higher in Tokyo than Hokkaido. Is your answer to the last question an overestimate or underestimate of price elasticity? Justify your answer.

(c) Using your estimated elasticity, what would the demand for health care be if the price in Tokyo were raised to 30 U per visit? What would the demand in Hokkaido be if the price were lowered to 5 U per visit?

You continue your observations of the Japanese health care system into the year 2000. For inscrutable reasons having to do with internal Japanese politics, the government changed the price in both Tokyo and Hokkaido that year, and you observe the demand recorded in Table 2.13.

(d) Calculate the price elasticity of demand for health care in Japan using only data from the year 2000.

(e) Use data from both years to calculate the elasticity of demand for health care for Tokyo and Hokkaido separately.

(f) Using your estimated elasticities, what would the demand for health care in each prefecture be if the price were raised to 60U per visit next year (for both prefectures)?

(g) Combine the Tokyo and Hokkaido estimates from exercise 11(e) to get a single estimate of the price elasticity of health care demand for all of Japan. Assume that Tokyo is five times as populous as all of Hokkaido.

12. Preventative care refers to care taken to prevent future diseases rather than to treat current ones. Compared to emergency room care, preventative care is rarely urgent, and benefits can be difficult to measure – if you had the flu vaccine this year but did not catch the flu, it is impossible to tell if it was the shot or assiduous hand washing that preserved you.

(a) Given this description of preventative care, would you expect preventative care to be more or less price sensitive compared to inpatient care? Why?

(b) Table 2.14 shows evidence on preventative care from the RAND HIE. Summarize the data in the table and note any interesting patterns. Was your prediction correct?

13. In this exercise, assume that the term “admission” in Table 2.15 refers to inpatient care, while “any use” refers to inpatient and outpatient care. Table 2.15 contains a lot of information. Without looking at any specific values, summarize what type of data the table contains. Give an example of a broad question about income levels and demand for health care that the table might have the potential to answer.

Essay Questions

14. Here is a selection from an abstract of a recent study entitled “The Effect of Health Insurance Coverage on the Use of Medical Services” by Michael Anderson, Carlos Dobkin, and Tal Gross:

Substantial uncertainty exists regarding the causal effect of health insurance on the utilization of care. Most studies cannot determine whether the large differences in healthcare utilization between the insured and the uninsured are due to insurance status or to other unobserved differences between the two groups. In this paper, we exploit a sharp change in insurance coverage rates that results from young adults “aging out” of their parents insurance plans to estimate the effect of insurance coverage on the utilization of emergency department (ED) and inpatient services. [In the United States, children are eligible for insurance coverage through their parents’ insurance only up to their 23rd birthday, at which point they lose eligibility.] Using the National Health Interview Survey (NHIS) and a census of emergency department records and hospital discharge records from seven states, we find that aging out results in an abrupt 5 to 8 percentage point reduction in the probability of having health insurance. We find that not having insurance leads to a 40 percent reduction in ED visits and a 61 percent reduction in inpatient hospital admissions.

(a) This study does not use randomization to assign people to different insurance plans. What two groups are being compared in this study?

(b) Identify at least one important methodological differences between the design of this study and the RAND HIE. Give a hypothetical reason that this difference would bias the results.

(c) Are the findings of this study generally consistent with the findings from the Oregon Medicaid Experiment?