Conventional health insurance: a decade later

In 1977, the National Center for Health Services Research conducted the most comprehensive survey of health insurance and use of health care services in this Nation’s history. From this survey emerged a vivid picture of the American health care system in the 1970’s-a system almost entirely financed by conventional insurance (defined as non-health maintenance and non-preferred provider organization health plans). It is from this survey that much of our understanding of the economics of health care has been derived.

In this article, after a decade of extraordinary change in American health care, we examine the 1987 conventional health plans. Where there are comparable data, we compare private health insurance of 1987 with that of 1977. The focus is on conventional health insurance, the source of protection for approximately 96 percent of Americans in 1977 and 73 percent in 1987 who secured health insurance through their employers.

Conventional fee-for-service insurance has been the traditional form of health coverage for Americans. This type of arrangement has few incentives for the provider or the patient to minimize the cost of treatment. Historically, insurers reimbursed providers’ charges with few questions asked. The insurer’s role was simply to forecast expenditures, determine risk, collect premiums, and pay the bills.

As health care costs escalated, employers and insurers turned increasingly to health maintenance organizations (HMO’s) and preferred provider organizations (PPO’s) as the means of controlling costs (Gabel et al., 1988; Rice et al., 1989). Patients in these plans no longer have unrestricted access to physicians and hospitals, and they almost always have to secure approval for admission to a hospital. HMO’s and PPO’s may review other steps in the medical treatment to make sure the treatment is necessary. If a patient does not follow guidelines, the HMO or PPO may deny payment (totally or partially), and the patient may face larger out-of-pocket costs.

This article is organized as follows:
* We review the health insurance data available in the
past decade.
* We review the methodology for the Health
Insurance Association of America (HIAA) health
benefit survey.
* We compare characteristics of conventional health
insurance plans of 1987 with those of 1977.
* We take a closer look at conventional plans of 1987 according to their sponsorship and employer size.

Our conclusion assesses the future of conventional insurance. Need for new information
To examine 1977 conventional health insurance, we turn to the landmark National Medical Care Expenditures Survey NMCES)-a household interview survey during which family health insurance coverage and use and costs of services were investigated (Farley, 1986). NMCES supplemental surveys explored in detail additional aspects of each person’s health coverage. During a smaller survey, the Employer Health Insurance Cost Survey (EHICS), employment-related health insurance plans were investigated by interviewing the employers of the individuals in the household survey (Taylor and Lawson, 1981). EHICS includes information about the availability of health coverage for employees, the cost of premiums, and how these were distributed between the employer and employee. For our analysis of health insurance in 1977, we used only the employer-based results from the EHICS. Data are on a national and a regional basis.

In recent years, health care analysts have relied on three sources of information for trends in health benefit coverage-consulting firm studies, coalition studies, and the Bureau of Labor Statistics (BLS) annual survey of mid-sized and large employers (Jensen et al., 1987). All of these studies have serious limitations, however, when one extrapolates the results to the U.S. population.

Consulting firms generally select their samples from their client base. They often fail to report their response rate or assess the representativeness of their sample. Thus, samples tend to be subject to selection bias and lack the ability to extrapolate findings to the entire U.S. population

Author: Steven DiCarlo