Address correspondence to Kathryn Phillips, Ph.D., 3333 California St., Suite 420, Box 936, University of California, San Francisco, San Francisco, CA 94143. At the time of this study, Sherilyn Tye, Ph.D., was a Research Associate, School of Pharmacy, University of California, San Francisco. Kathryn A. Phillips, Ph.D., is an Associate Professor, Health Services Research and Health Economics, School of Pharmacy and Institute of Health Policy Studies, University of California, San Francisco. Su-Ying Liang, Ph.D., is an Assistant Research Health Economist, Department of Clinical Pharmacy, University of California, San Francisco. Jennifer S. Haas, M.D., M.S.P.H., is an Associate Professor of Medicine, Division of General Internal Medicine, Brigham and Women's Hospital, Boston.
Moving beyond the Typologies of Managed Care: The Example of Health Plan Predictors of Screening Mammography
Article first published online: 6 JAN 2004
Health Services Research
Volume 39, Issue 1, pages 179–206, February 2004
How to Cite
Tye, S., Phillips, K. A., Liang, S.-Y. and Haas, J. S. (2004), Moving beyond the Typologies of Managed Care: The Example of Health Plan Predictors of Screening Mammography. Health Services Research, 39: 179–206. doi: 10.1111/j.1475-6773.2004.00221.x
This work was supported by funding from the National Cancer Institute (R01 CA81130). Partial support was also provided by the Agency for Healthcare Research and Quality (PO1 HS10771 and PO1 HS10856) and the Russell M. Grossman Endowment.
- Issue published online: 6 JAN 2004
- Article first published online: 6 JAN 2004
- Health plans;
- mammography screening;
- managed care;
Objectives. To develop a framework of factors to characterize health plans, to identify how plan characteristics were measured in a national survey, and to apply our findings to an analysis of the predictors of screening mammography.
Data Source. The primary data were from the 1996 Medical Expenditure Panel Survey.
Study Design. Women ages 40+, with private insurance, and no history of breast cancer were included in the study (N=2,909). We used multivariate logistic regression to estimate mammography utilization in the past two years relative to health plan and demographic factors. Health plan measures included whether there is a defined provider network, whether coverage is restricted to a network, use of gatekeepers, level of cost containment, copayment and deductible amounts, coinsurance rate, and breadth of benefit coverage.
Principal Findings. We found no significant difference in reported mammography utilization using a dichotomous comparison of individuals enrolled in managed care versus indemnity plans. However, women in health plans with a defined provider network were more likely to report having received a mammogram in the past two years than those without networks (adjusted OR=1.21, 95 percent CI=1.07–1.36), and women in gatekeeper plans were more likely to report receiving mammography than those without gatekeepers (adjusted OR=1.18, 95 percent CI=1.03–1.36). Restricted out-of-network coverage, use of cost containment, enrollee cost sharing, and breadth of benefit coverage did not appear to affect mammography use.
Conclusions. It is important to examine the effect of individual health plan components on the utilization of health care, rather than use the traditional broader categorizations of managed versus nonmanaged care or simple health plan typologies.