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.
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.
Authors: S A Feig; C J D'Orsi; R E Hendrick; V P Jackson; D B Kopans; B Monsees; E A Sickles; C B Stelling; M Zinninger; P Wilcox-Buchalla Journal: AJR Am J Roentgenol Date: 1998-07 Impact factor: 3.959
Authors: A M Leitch; G D Dodd; M Costanza; M Linver; P Pressman; L McGinnis; R A Smith Journal: CA Cancer J Clin Date: 1997 May-Jun Impact factor: 508.702
Authors: Laurence C Baker; Kathryn A Phillips; Jennifer S Haas; Su-Ying Liang; Dean Sonneborn Journal: Health Serv Res Date: 2004-12 Impact factor: 3.402
Authors: Ramzi G Salloum; Racquel E Kohler; Gail A Jensen; Stacey L Sheridan; William R Carpenter; Andrea K Biddle Journal: J Womens Health (Larchmt) Date: 2013-11-06 Impact factor: 2.681
Authors: Mandeep K Virk-Baker; Michelle Y Martin; Robert S Levine; Xin Wang; Tim R Nagy; Maria Pisu Journal: Cancer Causes Control Date: 2013-12 Impact factor: 2.506
Authors: Kathryn A Phillips; Jennifer S Haas; Su-Ying Liang; Laurence C Baker; Sherilyn Tye; Karla Kerlikowske; Julie Sakowski; Joanne Spetz Journal: Health Serv Res Date: 2004-02 Impact factor: 3.402
Authors: Daniella Meeker; Geoffrey F Joyce; Jesse Malkin; Steven M Teutsch; Anne C Haddix; Dana P Goldman Journal: Health Serv Res Date: 2010-10-28 Impact factor: 3.402
Authors: Su-Ying Liang; Kathryn A Phillips; Mika Nagamine; Uri Ladabaum; Jennifer S Haas Journal: Prev Chronic Dis Date: 2006-09-15 Impact factor: 2.830