Tracy Onega1,2,3, Tor D Tosteson1,2,3, Julie Weiss1, Jennifer S Haas4,5,6, Martha Goodrich7,8, Roberta DiFlorio9, Charles Brackett10, Cheryl Clark4, Kimberly Harris4, Anna N A Tosteson2,3. 1. Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA. 2. Norris Cotton Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA. 3. The Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA. 4. Division of General Internal Medicine and Primary Care, Brigham and Women's Hospital, Boston, MA, USA. 5. Harvard Medical School, Boston, MA, USA. 6. Harvard T.H. Chan School of Public Health, Boston, MA, USA. 7. Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA. martha.e.goodrich@Dartmouth.edu. 8. Norris Cotton Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA. martha.e.goodrich@Dartmouth.edu. 9. Department of Radiology, Dartmouth-Hitchcock Medical Center, Lebanon, NH, USA. 10. Department of General Internal Medicine, Dartmouth-Hitchcock Medical Center, Lebanon, NH, USA.
Abstract
BACKGROUND: Use of breast cancer screening is influenced by factors associated with patients, primary care providers, practices, and health systems. OBJECTIVE: We examined the relative effects of these nested levels on four breast cancer screening metrics. DESIGN: A web-based survey was completed at 15 primary care practices within two health systems representing 306 primary care providers (PCPs) serving 46,944 women with a primary care visit between 1/2011-9/2014. Analyses occurred between 1/2017 and 5/2017. MAIN MEASURES: Across four nested levels (patient, PCP, primary care practice, and health system), frequency distributions and adjusted rates of primary care practice characteristics and survey results for four breast screening metrics (percent screened overall, and percent screened age 40-49, 50-74, and 75+) were reported. We used hierarchical multi-level mixed and random effects analysis to assess the relative influences of PCP, primary care practice, and health system on the breast screening metrics. KEY RESULTS: Overall, the proportion of women undergoing breast cancer screening was 73.1% (73.4% for ages 40-49, 76.5% for 50-74, and 51.1% for 75+). Patient ethnicity and number of primary care visits were strongly associated with screening rates. After adjusting for woman-level factors, 24% of the overall variation among PCPs was attributable to the primary care practice level, 35% to the health system level, and 41% to the residual variation among PCPs within practice. No specific provider-level characteristics were found to be statistically significant determinants of screening rates. CONCLUSIONS: After accounting for woman-level characteristics, the remaining variation in breast cancer screening was largely due to provider and health system variation.
BACKGROUND: Use of breast cancer screening is influenced by factors associated with patients, primary care providers, practices, and health systems. OBJECTIVE: We examined the relative effects of these nested levels on four breast cancer screening metrics. DESIGN: A web-based survey was completed at 15 primary care practices within two health systems representing 306 primary care providers (PCPs) serving 46,944 women with a primary care visit between 1/2011-9/2014. Analyses occurred between 1/2017 and 5/2017. MAIN MEASURES: Across four nested levels (patient, PCP, primary care practice, and health system), frequency distributions and adjusted rates of primary care practice characteristics and survey results for four breast screening metrics (percent screened overall, and percent screened age 40-49, 50-74, and 75+) were reported. We used hierarchical multi-level mixed and random effects analysis to assess the relative influences of PCP, primary care practice, and health system on the breast screening metrics. KEY RESULTS: Overall, the proportion of women undergoing breast cancer screening was 73.1% (73.4% for ages 40-49, 76.5% for 50-74, and 51.1% for 75+). Patient ethnicity and number of primary care visits were strongly associated with screening rates. After adjusting for woman-level factors, 24% of the overall variation among PCPs was attributable to the primary care practice level, 35% to the health system level, and 41% to the residual variation among PCPs within practice. No specific provider-level characteristics were found to be statistically significant determinants of screening rates. CONCLUSIONS: After accounting for woman-level characteristics, the remaining variation in breast cancer screening was largely due to provider and health system variation.
Entities:
Keywords:
breast cancer screening; primary care practice breast screening
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