Academic journal article Health Care Financing Review

Cost of Smoking to the Medicare Program, 1993

Academic journal article Health Care Financing Review

Cost of Smoking to the Medicare Program, 1993

Article excerpt

INTRODUCTION

Interest in the costs related to smoking has never been higher. Previous research has looked at the cost borne by taxpayers to treat people with smoking-related diseases under Medicaid. For the first time, we use these methods to look at the costs to Medicare, which covers the medical expenses of 34 million Americans age 65 or over and 5.5 million persons with disabilities. The numbers are significant: 16 percent of Medicare enrollees in 1994 reported themselves as current smokers, and another 44 percent reported themselves as former smokers (Olin and Liu, 1998).

The published literature during the past three decades abounds with estimates of the annual costs of smoking in the United States (Hedrick, 1971; Luce and Schweitzer, 1978; Kristein, 1977; Rice et al., 1986; Office of Technology Assessment, 1985 and 1993; Bartlett et al., 1994). Several studies include only the direct medical care costs; others include the indirect costs, the value of unpurchased resources lost attributable to smoking. These studies yield national cost estimates. Recently, two articles were published that presented State-level estimates of Medicaid smoking-attributable expenditures (SAEs) (Miller et al., 1998a) and total SAEs (Miller et al., 1998b).

In this article, we present State estimates of Medicare expenditures attributable to smoking for the Medicare population, including those with disabilities. Estimates are reported by type of expenditure. Also presented are the Medicaid, residual public and private, and total SAEs for each State. Presentation of these State estimates enables each State to quantify its financial burden of smoking by source of payment.

METHODS

The estimation of Medicare SAEs involved four steps: (1) a national model of Medicare SAEs was estimated; (2) the national model was applied to the States; (3) a national estimate was derived from the sum of the State estimates; and (4) interval estimates from the national model were applied to the State estimates.

National Model

We estimated the Medicare expenditure models with data from respondents who were age 65 or over in the National Medical Expenditure Survey (NMES) (Agency for Health Care Policy and Research, 1991). The model has three parts: a sample-bias correction equation; two morbidity equations estimating the effect of smoking history on smoking-related diseases and poor health status; and six expenditure equations estimating the effect of health status and smoking history on the likelihood of three different types of expenditures and on their positive magnitudes. Although there are separate models by sex, we shall refer to these models in the singular. We discuss these three parts in turn. A more detailed description of the national model and its estimation is contained in the Technical Note.

Sample Bias

There may be sample-selection bias introduced by the fact that the NMES obtained data on smoking history through its supplemental survey, which was conducted approximately 4 1/2 months into its annual study. Not every NMES respondent completed the survey. For example, participants who died in the first quarter did not participate. Any bias in participating would reflect two countervailing tendencies. First, the likelihood that people who were more concerned about health issues, and hence were more likely to participate in the supplemental survey, were likely to have a higher demand for medical services. Second, participants who were sicker and needed more medical services were less likely to participate. Bias is likely to occur in the estimation of ambulatory care, which is more likely a function of demand (i.e., discretionary) than for hospital or home health care, where services are more determined by supply than demand.

Morbidity

The morbidity portion of the model estimates the effect of smoking history (current, never smokers, or former/unknown smoking status) on previous disease and the effect of smoking history and the propensity for previous disease on self-reported poor health status. …

Search by... Author
Show... All Results Primary Sources Peer-reviewed

Oops!

An unknown error has occurred. Please click the button below to reload the page. If the problem persists, please try again in a little while.