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August 2004, Vol 94, No. 8 | American Journal of Public Health 1330-1332
© 2004 American Public Health Association

RESEARCH AND PRACTICE

The Benefit of Health Insurance Coverage of Contraceptives in a Population-Based Sample

Ann Kurth, PhD, CNM, Marcia Weaver, PhD, David Lockhart, BA and Lori Bielinski, LMP

Ann Kurth is with Biobehavioral Nursing & Health Systems, University of Washington School of Nursing, Seattle. Marcia Weaver is with the Department of Health Services, University of Washington School of Public Health and Community Medicine, Seattle. David Lockhart is with the University of Washington Center for AIDS & STD, Seattle. Lori Bielinski is with the Washington State Chiropractic Association, Olympia.

Correspondence: Requests for reprints should be sent to Ann Kurth, PhD, CNM, UW School of Nursing, Biobehavioral Nursing & Health Systems, Box 357266, Seattle, WA 98195-7266 (e-mail: akurth{at}u.washington.edu).


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 References
 

This study estimated the value of contraceptives, through a random-digit-dialed survey of willingness to pay for health insurance coverage of contraceptives among 659 Washington State adults. People valued contraceptives at 5 times the actuarial cost; in general, women and reproductive-aged persons were willing to pay more, but low-income men highly valued contraceptives. Most respondents (85%) said that contraceptives should be covered by health insurance plans. The full benefit of contraceptives exceeds their cost.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
METHODS
 RESULTS
 DISCUSSION
 References
 
Unintended pregnancy1 and sexually transmitted infections2 remain considerable public health problems in the United States. Contraceptive methods save more money than they cost, by reducing these adverse outcomes.3–6 Although more than 20 states have passed contraceptive coverage mandates, many health insurance plans continue to exclude contraceptives and safer-sex methods such as condoms.7

In this brief, we report public opinion regarding insurance coverage of contraceptives and estimates of the full economic benefit of contraceptives. Benefit was measured by contingent valuation methods8,9 and included the value to current contraceptive users, future users (option value10), and nonusers such as gay men, lesbians, and people beyond reproductive age (social altruism value).


   METHODS
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
RESULTS
 DISCUSSION
 References
 
We conducted a random-digit-dialed telephone survey of 659 Washington State household respondents aged 18 years or older in fall 2000. The response rate was 48%,11 comparable to that of other telephone12 and contingent valuation9 studies.

The opinion question asked whether insurers should cover contraceptives. For willingness to pay, we used an insurance perspective10 and a bidding game format,13 in which respondents were asked a sequence of possible prices to determine their final willingness-to-pay amount. We designed the willingness-to-pay questions to minimize strategic bias,9 which is the potential for a respondent to misrepresent his or her willingness to pay.

We had 3 validity tests: unit framing, scale, and starting point biases.14 Respondents gave their monthly and annual willingness to pay. Half of the respondents were told that contraceptives reduced pregnancy probability to 1%, and the other half were told that contraceptives reduced the probability to 12%.15 In addition, for half of the respondents, the starting bid was $2 per month (the estimated 2000 actuarial cost16 for contraceptive coverage was $1.93), and for the other half, the starting bid was $10. To test theoretical validity, we regressed willingness to pay against income,17 gender, age, and other key variables. We also assessed reasons for protest ($0) responses.15

Analysis
We used Stata 7.0 (Stata Corp, College Station, Tex). The opinion question was analyzed with a multiple logistic regression. We report the mean willingness to pay, which is the appropriate statistic for cost–benefit analysis, for the full sample and by starting bid. Associations with the mean log-transformed willingness to pay were tested by using tobit regression with robust variance estimators.18,19 We tested for interaction with a Wald test. All analyses tested the ratio between 2 willingness-to-pay amounts rather than the absolute difference. Results were transformed back onto the original scale and presented as a ratio of dollar values (willingness to pay per $1 willingness to pay in the reference group).


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
DISCUSSION
 References
 
Respondent demographics are summarized in Table 1Go. The sample characteristics were comparable to 2000 census data for Washington State adults, with some significant differences across age and ethnic groups.20 In particular, the percentage of respondents aged 18 to 24 years was lower in our sample than in the census data, which is generally true of telephone surveys as compared with mail surveys.


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  		TABLE 1— Demographic Characteristics of a Random-Digit-Dialed Sample: Washington State, 2000 (N = 659)
 
Most respondents with an opinion (85%; 537 of 630) said that contraceptives should be covered by health insurance plans. Women were more likely to favor coverage than were men (adjusted odds ratio = 4.95; 95% confidence interval = 2.83, 8.67).

The unadjusted mean willingness to pay was $9.59 per month (SD = $9.38). The willingness to pay of nearly all (94%) respondents was higher than the actuarial cost. We saw no evidence of unit price framing bias when the mean monthly willingness to pay was compared with the annual willingness to pay (P = .21).

The multivariate tobit regression model included gender, income, reproductive age, sterilization status, contraceptive effectiveness scenario, willingness to pay bid starting point, and an interaction term (Table 2Go). For example, men earning less than $10 000 per year were willing to pay 2.35 times as much as men earning $20 001 to $50 000 per year (reference group). People of reproductive age (women ≤44 years, men ≤54 years) were willing to pay 2.12 times as much as respondents no longer of reproductive age.


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  		TABLE 2— Factors Independently Associated With Willingness to Pay (WTP) for a Contraceptive Coverage Insurance Benefit: Washington State, 2000 (N = 624)
 
Respondents were willing to pay more for methods presented as being more effective for preventing pregnancy (P = .049). Individuals who were presented with an effectiveness scenario of 99% were willing to pay 1.24 times as much as those given an 88% effectiveness scenario. Willingness to pay varied by whether respondents received an initial bid of $2 or $10 (P < .001). Respondents given a $10 starting bid were willing to pay 1.63 times as much as individuals given a $2 starting bid. Equivalent proportions of respondents were unwilling to pay anything ($0 willingness to pay: 14.1% in $2 initial bid group, 16.8% in $10 group). Reasons for this $0 willingness to pay likewise were similar between the 2 groups.


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
References
 
This study found that insurance coverage of contraceptives was widely supported and valued by women and men, regardless of whether they used contraceptives.

Respondents were willing to pay on average $9.59 for contraceptive coverage that cost $1.93 per month, yielding a favorable cost–benefit ratio of 4.97. These results reassure payers, policymakers, and employers that adding this coverage is a valuable benefit to consumers.

One limitation was that we saw evidence of starting point bias; the cost–benefit ratio was 3.43 for the subsample with a starting bid of $2 and 5.84 for those with a starting bid of $10. However, mean willingness to pay increased by only 70% when the starting bid increased by 400%. Another limitation was that the choice of starting bid levels may have biased the cost–benefit ratio to be greater than 1.0.

Two of the 3 validity tests supported the validity of the estimates. No evidence of framing bias was seen, and the contraceptive effectiveness scale effect was in the expected direction. Additional strengths of the study included the population-based sample, a narrow range in the willingness-to-pay measure, and theoretical validity of data in the direction expected.

Cost–benefit analyses should consider the full value of contraceptives, and insurance products should cover the cost of contraceptive goods and services.


   Acknowledgments
 
Funding for this study was provided by unrestricted grants from the Nine West Settlement Award and by Planned Parenthood of Western Washington.

We appreciate the support of the Washington State Office of the Insurance Commissioner and the work of Dr Margaret Wooding Baker and the Women’s Health Benefits Study Advisory Group. The survey was conducted by the Gilmore Research Group, Seattle, Wash, with thanks to JoElla Weybright and Liz Muktarian.

Human Participant Protection
The study was approved by the University of Washington Human Subjects Division. All participants gave verbal informed consent.


   Footnotes
 
Contributors
A. Kurth conceived the study, oversaw its implementation, oversaw the analyses, and led the writing of the brief. M. Weaver assisted with the study design, instrument development, analyses, and writing. D. Lockhart conducted the analyses and assisted with the writing. L. Bielinski helped supervise study implementation and data collection. All authors helped to conceptualize ideas, interpret findings, and approve the brief.

Peer Reviewed

Accepted for publication December 18, 2003.


   References
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 References
 
1. Orr ST, Miller CA, James SA, Babones S. Unintended pregnancy and preterm birth. Paediatr Perinat Epidemiol. 2000;14:309–313.[ISI][Medline]

2. Aral SO. Sexually transmitted diseases: magnitude, determinants and consequences. Int J STD AIDS. 2001;12:211–215.[Abstract/Free Full Text]

3. Trussell J, Wiebe E, Shochet T, Guilbert E. Cost savings from emergency contraceptive pills in Canada. Obstet Gynecol. 2001;97:789–793.[Abstract/Free Full Text]

4. Trussell J, Koenig J, Stewart F, et al. The economic value of contraception: a comparison of 15 methods. Am J Public Health. 1995;85:494–503.[Abstract/Free Full Text]

5. Trussell J, Koenig J, Stewart F, Darroch JE. Medical care costs savings from adolescent contraceptive use. Fam Plann Perspect. 1997;29:248–255, 295.[ISI][Medline]

6. Chiou CF, Trussell J, Reyes E, et al. Economic analysis of contraceptives for women. Contraception. 2003;68:3–10.[ISI][Medline]

7. Law S. Sex discrimination and insurance for contraception. Wash Law Rev. 1998;73:1–40.

8. Deiner A, O’Brien B, Gafni A. Health care contingent evaluation studies: a review and classification of the literature. Health Econ. 1998;7:313–326.[ISI][Medline]

9. Mitchell RC, Carson RT. Using Surveys to Value Public Goods: The CV Method. Washington, DC: Resources for the Future; 1989.

10. Gafni A. Willingness-to-pay as a measure of benefits: relevant questions in the context of public decisionmaking about health care programs. Med Care. 1991;29:1246–1252.[ISI][Medline]

11. On the definition of response rates: a special report of the CASRO Task Force on Completion Rates. Port Jefferson, NY: Council of American Survey Research Organizations; 1982. Available at: http://www.casro.org/resprates.cfm. Accessed March 20, 2002.

12. Behavioral Risk Factor Surveillance System: BRFSS Summary Data Quality Report [Table 4]. Atlanta, Ga: Centers for Disease Control and Prevention; 2000:9.

13. Zarkin GA, Cates SC, Bala MV. Estimating the willingness to pay for drug abuse treatment: a pilot study. J Subst Abuse Treat. 2000;18:149–159.[Medline]

14. National Oceanic and Atmospheric Administration (NOAA). Report of the NOAA Panel on Contingent Valuation. Fed Regist. 1993;58:4607–4614.

15. Hatcher RA, Trussell J, Stewart F, et al. Contraceptive Technology. 16th ed. New York, NY: Irvington Publishers; 1994:Table 27–1.

16. Sobel H, Stitzel B, Buck Consultants for the Alan Guttmacher Institute. Cost of Covering Reversible Medical Contraceptives. New York, NY: Alan Guttmacher Institute; June 1998.

17. Jones-Lee MW. Personal willingness to pay for prevention: evaluating the consequences of accidents as a basis for preventive measures. Addiction. 1993;88:913–921.[Medline]

18. Donaldson C, Mapp T, Ryan M, Curtin K. Estimating the economic benefits of avoiding food-borne risk: is ‘willingness to pay’ feasible? Epidemiol Infect. 1996;116:285–294.[Medline]

19. Donaldson C, Shackley P, Abdalla M, Miedzybrodzka Z. Willingness to pay for antenatal carrier screening for cystic fibrosis. Health Econ. 1995;4:439–452.[ISI][Medline]

20. US Census Bureau. DP-1 profile of general demographic characteristics: 2000. Available at: http://factfinder.census.gov/servlet/BasicFactsTable?_lang=en&_vt_name=DEC_2000_SF1_U_DP1&_geo_id=04000US53. Accessed November 13, 2002.




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