Abstract
Introduction
Timely follow-up of abnormal tests is critical to the effectiveness of cancer screening, but may vary by screening test, healthcare system, and sociodemographic group.
Methods
Timely follow-up of abnormal mammogram and fecal occult blood testing or fecal immunochemical tests (FOBT/FIT) were compared by race/ethnicity using Population-Based Research Optimizing Screening through Personalized Regimens consortium data. Participants were women with an abnormal mammogram (aged 40–75 years) or FOBT/FIT (aged 50–75 years) in 2010–2012. Analyses were performed in 2015. Timely follow-up was defined as colonoscopy ≤3 months following positive FOBT/FIT, additional imaging or biopsy ≤3 months following Breast Imaging Reporting and Data System Category 0, 4, or 5 mammograms or ≤9 months following Category 3 mammograms. Logistic regression was used to model receipt of timely follow-up adjusting for study site, age, year, insurance, and income.
Results
Among 166,602 mammograms, 10.7% were abnormal; among 566,781 FOBT/FITs, 4.3% were abnormal. Nearly 96% of patients with abnormal mammograms received timely follow-up versus 68% with abnormal FOBT/FIT. There was greater variability in receipt of follow-up across healthcare systems for positive FOBT/FIT than for abnormal mammograms. For mammography, black women were less likely than whites to receive timely follow-up (91.8% vs 96.0%, OR=0.71, 95% CI=0.51, 0.97). For FOBT/FIT, Hispanics were more likely than whites to receive timely follow-up than whites (70.0% vs 67.6%, OR=1.12, 95% CI=1.04, 1.21).
Conclusions
Timely follow-up among women was more likely for abnormal mammograms than FOBT/FITs, with small variations in follow-up rates by race/ethnicity and larger variation across healthcare systems.
Introduction
Screening reduces mortality risk for breast and colorectal cancers.1–4 However, failure to receive appropriate follow-up after a positive result undermines the benefits of screening and may compound disparities.5, 6 Compared with whites, black and Hispanic women have lower likelihood of receiving follow-up for abnormal mammography.7–16 Little data exist on racial/ethnic disparities in time to follow-up of abnormal fecal occult blood testing or fecal immunochemical tests (FOBT/FIT).17 Comparisons across cancers may suggest processes that promote timely resolution of positive screening tests. However, no previous reports have simultaneously examined follow-up of abnormal breast and colorectal cancer screening tests by race/ethnicity. This study evaluated the receipt of timely follow-up of abnormal screening mammogram or FOBT/FIT18 and whether racial/ethnic differences in follow-up exist by screening type and healthcare system.
Methods
Data were obtained from the National Cancer Institute–funded Population-Based Research Optimizing Screening through Personalized Regiments (PROSPR) consortium (healthcaredelivery.cancer.gov/prospr/introduction.html).19 Breast cancer screening data came from Dartmouth Hitchcock Medical Center and Brigham and Women’s Hospital, University of Pennsylvania Health System, and Vermont Breast Cancer Surveillance System. FOBT/FIT data came from Kaiser Permanente, Northern (KPNC) and Southern California (KPSC), Group Health, and Parkland Hospital and Health System-University of Texas Southwestern Medical Center (PHHS-UTSW).20 Each study site’s IRB approved the study.
The study population included women with either abnormal mammograms (2011–2012) or positive FOBT/FIT (2010–2012) with race/ethnicity identified as non-Hispanic white, non-Hispanic black, Hispanic, or Asian/Pacific Islander. The mammography cohort included breast cancer–free women aged 40–75 years with mammograms classified as 0, 3, 4, or 5 on the Breast Imaging Reporting and Data System (BI-RADS)21 with no imaging within 3 months prior. The FOBT/FIT cohort was colorectal cancer–free women aged 50–75 years with a first positive FOBT/FIT after the cohort entry date with no prior colectomy, colonoscopy within 10 years, or sigmoidoscopy within 5 years.
Patient information, including race/ethnicity, age, screening exam date, the types and results of screening and follow-up exams, and insurance coverage status were obtained from electronic databases. Median household incomes at the ZIP code of residence were obtained by linking to 2010 U.S. Census data.
The outcome was timely follow-up, based on standard definitions used by the PROSPR consortium,18 defined as additional imaging or biopsy within 3 months of BI-RADS 0, 4, and 5 mammograms, or within 9 months for BI-RADS 3 mammograms and colonoscopy within 3 months of a positive FOBT/FIT.
The proportions of abnormal screening exams were compared by race/ethnicity and PROSPR sites, separately for breast and colorectal cancer screening. Multivariable logistic regression models were used to estimate the relative odds of timely follow-up by race/ethnicity, adjusted for age, test year, and study site. Expanded models also adjusted for insurance and ZIP code income. The Vermont site lacked insurance data so it was excluded from the expanded models.
Results
Among 166,602 screening mammograms, 17,746 (10.7%) were abnormal, with a similar fraction abnormal across racial/ethnic groups (p=0.84) (Table 1). Among 566,781 screening FOBT/FITs, 24,424 (4.3%) were positive, with a range from 3.9% for Asian/Pacific Islanders to 4.8% for blacks (p<0.001).
Table 1.
Characteristics of Women With Preventive Screening in the PROSPR Consortium
| Breast | Colorectal | |||||
|---|---|---|---|---|---|---|
|
| ||||||
| Total screened population | Abnormal screening result | Percent abnormal within category | Total screened population | Abnormal screening result | Percent abnormal within category | |
|
| ||||||
| N (Column %) | N (Column %) | Row % | N (Column %) | N (Column %) | Row % | |
| Total | 166,602 (100) | 17,746 (100) | 10.7 | 566,781 (100) | 24,424 (100) | 4.3 |
|
| ||||||
| Age, year | ||||||
| 40–44 | 20,018 (12.0) | 3,279 (18.5) | 16.4 | |||
| 45–49 | 24,948 (15.0) | 3,435 (19.4) | 13.8 | |||
| 50–54 | 29,754 (17.9) | 3,229 (18.2) | 10.9 | 187,367 (33.1) | 6,843 (28.0) | 3.7 |
| 55–59 | 29,296 (17.6) | 2,589 (14.6) | 8.8 | 129,209 (22.8) | 4,998 (20.5) | 3.9 |
| 60–64 | 26,966 (16.2) | 2,246 (12.7) | 8.3 | 112,615 (19.9) | 4,905 (20.1) | 4.4 |
| 65–69 | 20,487 (12.3) | 1,732 (9.8) | 8.5 | 78,244(13.8) | 4,013 (16.4) | 5.1 |
| 70–75 | 15,133 (9.1) | 1,236 (7.0) | 8.2 | 59,346 (10.5) | 3,665 (15.0) | 6.2 |
| Race/ethnicity | ||||||
| N.H. white | 146,503 (87.9) | 15,568 (87.7) | 10.6 | 305,758 (53.9) | 13,360 (54.7) | 4.4 |
| N.H. black | 9,841 (5.9) | 1,069 (6.0) | 10.9 | 51,230 (9.0) | 2,452 (10.0) | 4.8 |
| Hispanic | 7,502 (4.5) | 811 (4.6) | 10.8 | 126,545 (22.3) | 5,338 (21.9) | 4.2 |
| Asian/PI | 2,756 (1.7) | 298 (1.7) | 10.8 | 83,248 (14.7) | 3,274 (13.4) | 3.9 |
| Study site | ||||||
| D-BWH | 50,225 (30.2) | 4,917 (27.7) | 9.8 | |||
| UPenn | 16,233 (9.7) | 1,649 (9.3) | 10.2 | |||
| VT | 100,144 (60.1) | 11,180 (63.0) | 11.2 | |||
| GH | 22,343 (3.9) | 956 (3.9) | 4.3 | |||
| KPNC | 272,133 (48.0) | 11,080 (45.4) | 4.1 | |||
| KPSC | 260,667 (46.0) | 11,942 (48.9) | 4.6 | |||
| PHHS-UTSW | 11,638 (2.1) | 446 (1.8) | 3.8 | |||
| Year of positive test | ||||||
| 2010 | 295,355 (52.1) | 11,474 (47.0) | 3.9 | |||
| 2011 | 72,754 (43.7) | 7,937 (44.7) | 10.9 | 161,894 (28.6) | 7,609 (31.2) | 4.7 |
|
| ||||||
| 2012 | 93,848 (56.3) | 9,809 (55.3) | 10.5 | 109,532 (19.3) | 5,341 (21.9) | 4.9 |
| Insurance type | ||||||
| Medicare | 14,432 (21.9) | 1,175 (18.0) | 8.1 | 154,706 (27.3) | 8,645 (35.4) | 5.6 |
| Medicaid | 4,101 (6.2) | 480 (7.4) | 11.7 | 14,421 (2.5) | 977 (4.0) | 6.8 |
| Commercial/private | 39,890 (60.6) | 4,038 (62.0) | 10.1 | 387,339 (68.3) | 14,422 (59.0) | 3.7 |
| Other | 6,505 (9.9) | 691 (10.6) | 10.6 | 1,171 (0.2) | 46 (0.2) | 3.9 |
| Uninsured | 1,011 (1.5) | 124 (1.9) | 12.3 | 8,962 (1.6) | 329 (1.3) | 3.7 |
| Unknown | 519 (0.8) | 58 (0.9) | 11.2 | 182 (0.0) | 5 (0.0) | 2.7 |
| Not collected | 100,144 | 11,180 | 11.2 | |||
| ZIP code median income | ||||||
| Q1 | 39,070 (23.5) | 4,188 (23.6) | 10.7 | 130,887 (23.1) | 6,053 (24.8) | 4.6 |
| Q2 | 39,261 (23.6) | 4,497 (25.3) | 11.5 | 142,283 (25.1) | 6,558 (27.0) | 4.6 |
| Q3 | 39,882 (23.9) | 4,225 (23.8) | 10.6 | 143,835 (25.4) | 6,063 (24.8) | 4.2 |
| Q4 | 38,049 (22.8) | 3,785 (21.3) | 10.0 | 144,580 (25.5) | 5,485 (22.5) | 3.8 |
| Unknown | 10,340 (6.2) | 1,051 (5.9) | 10.2 | 5,196 (0.9) | 235 (1.0) | 4.5 |
DBWH, Geisel School of Medicine at Dartmouth and Brigham and Women’s Hospital; GH, Group Health Research Institute; KPNC, Kaiser Permanente Northern California; KPSC, Kaiser Permanente Southern California; N.H., Non-Hispanic; PHHS-UTSW, Parkland Health and Hospital System - University of Texas Southwestern; PI, Pacific Islander; PROSPR, Population-based Research Optimizing Screening through Personalized Regimens; UPenn, University of Pennsylvania; VT, University of Vermont
Receipt of timely follow-up was higher and less variable across study sites for abnormal mammograms (Table 2, 92.9%–96.7%) than for positive FOBT/FITs (39.8%–71.3%). In general, the proportion with timely follow-up was fairly similar by race; however, small differences were statistically significant. Blacks were less likely than whites to receive timely follow-up of mammography at all study sites (p<0.001). Timely follow-up by race/ethnicity was more variable across healthcare systems for FOBT/FIT.
Table 2.
Timely Follow-up of Abnormal Screening Tests by Screening Type and Race/Ethnicitya
| Breast | Colorectal | ||||||||
|---|---|---|---|---|---|---|---|---|---|
|
| |||||||||
| Race/Ethnicity | Total N(%) | D-BWH N(%) | UPenn N(%) | VT N(%) | Total N(%) | GH N(%) | KPNC N(%) | KPSC N(%) | PHHS-UTSW N(%) |
| All races | 16,953 (95.6) | 4,567 (92.9) | 1,575 (95.5) | 10,811 (96.7) | 15,447 (67.9) | 463 (55.7) | 6,919 (66.2) | 7,942 (71.3) | 153 (39.8) |
| N.H. white | 14,931 (96.0) | 3,574 (93.2) | 927 (97.5) | 10,430 (96.8) | 8,483 (67.6) | 343 (56.0) | 4,275 (66.4) | 3,840 (70.7) | 25 (44.6) |
| N.H. black | 981 (91.8) | 370 (90.9) | 564 (92.5) | 47 (90.4) | 1,478 (64.5) | 24 (53.3) | 557 (65.1) | 831 (68.5) | 66 (37.5) |
| Hispanic | 762 (94.0) | 510 (92.9) | 31 (93.9) | 221 (96.5) | 3,457 (70.0) | 25 (56.8) | 984 (66.0) | 2,391 (73.1) | 57 (43.2) |
| Asian/PI | 279 (93.6) | 113 (89.7) | 53 (96.4) | 113 (96.6) | 2,059 (67.9) | 71 (55.0) | 1,103 (66.6) | 880 (71.8) | 5 (25.0) |
Percentages are derived from the number completing timely follow-up (shown) divided by the number of women with abnormal screening test results among women with sufficient follow-up time within each study site and racial/ethnic group (not shown).
D-BWH, Geisel School of Medicine at Dartmouth and Brigham and Women’s Hospital; GH, Group Health Research Institute; KPNC, Kaiser Permanente Northern California; KPSC, Kaiser Permanente Southern California; N.H., Non-Hispanic; PHHS-UTSW, Parkland Health and Hospital System - University of Texas Southwestern; PI, Pacific Islander; UPenn, University of Pennsylvania; VT, University of Vermont
Overall, black women were less likely than white women to receive timely follow-up of abnormal mammograms (Table 3), though differences were attenuated after adjusting for insurance and income (OR=0.71, 95% CI=0.51, 0.97). For FOBT/FIT, compared with whites, blacks had similar a rate of timely follow-up whereas Hispanics were more likely to have timely follow-up (AOR=1.12, 95% CI=1.04, 1.21) after adjusting for study site, age, year of test, insurance, and income. Analyses stratified by study site are displayed in Appendix Table 1. There were no significant interactions between study site and race/ethnicity. Sensitivity analyses using 6 months instead of 3 months as the definition of timely follow-up produced similar results (Appendix Table 2).
Table 3.
Logistic Regression of Timely Follow-up of Abnormal Screening Tests by Screening Type and Race/Ethnicity
| Race/Ethnicity | OR (95% CI) | ||||
|---|---|---|---|---|---|
| Breast a | Breast b | Breast c | Colorectal a | Colorectal c | |
|
| |||||
| N total | N=17,739 | N=6,564 | N=6,447 | n=22,805 | n=22,598 |
| N.H. white | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) | 1.00 (ref) |
| N.H. black | 0.53 (0.41–0.69) | 0.55 (0.42–0.72) | 0.71 (0.51–0.97) | 0.90 (0.82,0.99) | 1.00 (0.90,1.10) |
| Hispanic | 0.90 (0.66–1.22) | 0.90 (0.64–1.27) | 1.26 (0.87–1.84) | 1.05 (0.98,1.14) | 1.12 (1.04,1.21) |
| Asian/PI | 0.71 (0.44–1.15) | 0.66 (0.38–1.14) | 0.67 (0.38–1.15) | 1.00 (0.92,1.09) | 0.98 (0.90,1.07) |
Logistic regression model adjusted for study site, age, year of test. (All sites)
Logistic regression model adjusted for study site, age, year of test. (VT excluded).
Logistic regression model adjusted for study site, age, year of test, income (ZIP code median), and insurance (VT excluded from mammography analysis)
N.H., Non-Hispanic; PI, Pacific Islander
Discussion
There were different patterns of timely follow-up of positive screening test by race/ethnicity for mammography and FIT/FOBT. Mammography follow-up rates were high for all racial/ethnic groups. Black women were less likely than whites to receive timely follow-up of abnormal mammograms but the absolute percentage difference in follow-up between whites and blacks was relatively small. By contrast, timely follow-up of positive FOBT/FIT was lower than abnormal mammography and racial/ethnic differences were not significant. Positive FOBT/FIT follow-up rates were more variable across healthcare systems, consistent with prior reports that 40%–85% of positive FOBT/FIT results receive follow-up within 1 year.22–28 These patterns may be the result of differences in policies, the screening process, and practices and procedures across the cancers and healthcare systems as well as differences in the populations served.
The Mammography Quality Standards Act requires providers to notify patients with abnormal results in a timely manner, which likely explains the consistent and high observed follow-up rates.29 No such mandates are in place for positive FOBT/FIT results. Higher rates of timely follow-up of abnormal FOBT/FIT were observed at KPNC/KPSC, which have more aggressive follow-up procedures than other systems.20 KPNC, KPSC, and Group Health all have systemwide procedures to track adherence to follow-up of positive FOBT/FIT, but PHHS-UTSW does not have a system-level program in place. At PHHS-UTSW, physicians are notified of positive results and patients’ failure to attend scheduled colonoscopy. The lack of a system-level follow-up program likely explains the observed greater variation in follow-up across racial/ethnic groups at PHHS-UTSW than at the other healthcare systems in this study.
Differential access to care and income may explain differences in mammography follow-up, because racial differences in follow-up were attenuated after adjustment for insurance and income. Although the Affordable Care Act mandates coverage without co-payments for U.S. Preventive Services Task Force–recommended screening tests, coverage and out-of-pocket costs for follow-up testing can vary widely across health insurance plans.30 The majority of the FOBT/FIT cohort was from insured populations of KPNC, KPSC, and Group Health, which may account for the minimal overall racial/ethnic differences. By contrast, there is more diversity in insurance coverage among the mammography screening sites, with a greater proportion of Medicaid recipients.
Limitations
A limitation of this study is the potential for incomplete capture of received care and prior screening at outside institutions, although some sites included data from claims. The authors were unable to disentangle the contributions of geographic differences in characteristics from other factors, which may require pragmatic trials of the mandates and organized process of care for diverse populations.
Conclusions
This study showed high rates of follow-up of abnormal mammograms irrespective of race/ethnicity and small racial differences across healthcare systems. By contrast, follow-up rates of positive FOBT/FIT were lower and more variable across healthcare systems with minimal differences by race/ethnicity. Legal mandates targeted at national patient safety goals, or in their absence, coordinated organized programs with multilevel interventions, may improve follow-up of abnormal tests.31, 32 Future studies could assess how specific patient-, provider-, and system-level follow-up methods affect variation in timely follow-up by race/ethnicity.
Supplementary Material
Acknowledgments
The authors thank the participating Population-Based Research Optimizing Screening through Personalized Regimens (PROSPR) Research Centers for the data they have provided for this study. A list of the PROSPR investigators and contributing research staff are provided at: healthcaredelivery.cancer.gov/prospr/.
The authors thank Isabel Scarinci for her comments on the manuscript.
This work was funded by the NIH/National Cancer Institute PROSPR program, grant numbers: Kaiser Foundation Research Institute U54CA163262, Group Health Research Institute U54CA163261, Parkland UT Southwestern U54CA163308, University of Pennsylvania U54CA163313, University of Vermont U54CA163303, Geisel School of Medicine at Dartmouth and Brigham and Women’s Hospital U54CA163307, University of New Mexico U54CA164336, Fred Hutchinson Cancer Research Center U01CA163304.
Dr. Conant is a consultant and lecturer for Hologic, Inc. and a consultant for Siemen’s Healthcare. No other financial disclosures were reported by the authors of this paper.
Footnotes
Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
References
- 1.Screening for colorectal cancer: U.S. Preventive Services Task Force recommendation statement. Ann Intern Med. 2008;149(9):627–637. doi: 10.7326/0003-4819-149-9-200811040-00243. http://dx.doi.org/10.7326/0003-4819-149-9-200811040-00243. [DOI] [PubMed] [Google Scholar]
- 2.Screening for breast cancer: U.S. Preventive Services Task Force recommendation statement. Ann Intern Med. 2009;151(10):716–726. doi: 10.7326/0003-4819-151-10-200911170-00008. http://dx.doi.org/10.7326/0003-4819-151-10-200911170-00008. [DOI] [PubMed] [Google Scholar]
- 3.Levin B, Lieberman DA, McFarland B, et al. Screening and surveillance for the early detection of colorectal cancer and adenomatous polyps, 2008: a joint guideline from the American Cancer Society, the US Multi-Society Task Force on Colorectal Cancer, and the American College of Radiology. CA Cancer J Clin. 2008;58(3):130–160. doi: 10.3322/CA.2007.0018. http://dx.doi.org/10.3322/CA.2007.0018. [DOI] [PubMed] [Google Scholar]
- 4.Smith RA, Manassaram-Baptiste D, Brooks D, et al. Cancer screening in the United States, 2015: a review of current American cancer society guidelines and current issues in cancer screening. CA Cancer J Clin. 2015;65(1):30–54. doi: 10.3322/caac.21261. http://dx.doi.org/10.3322/caac.21261. [DOI] [PubMed] [Google Scholar]
- 5.Yabroff KR, Washington KS, Leader A, Neilson E, Mandelblatt J. Is the promise of cancer-screening programs being compromised? Quality of follow-up care after abnormal screening results. Med Care Res Rev. 2003;60(3):294–331. doi: 10.1177/1077558703254698. http://dx.doi.org/10.1177/1077558703254698. [DOI] [PubMed] [Google Scholar]
- 6.Zapka J, Taplin SH, Price RA, Cranos C, Yabroff R. Factors in quality care--the case of follow-up to abnormal cancer screening tests--problems in the steps and interfaces of care. J Natl Cancer Inst Monogr. 2010;2010(40):58–71. doi: 10.1093/jncimonographs/lgq009. http://dx.doi.org/10.1093/jncimonographs/lgq009. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Wujcik D, Shyr Y, Li M, et al. Delay in diagnostic testing after abnormal mammography in low-income women. Oncol Nurs Forum. 2009;36(6):709–715. doi: 10.1188/09.ONF.709-715. http://dx.doi.org/10.1188/09.ONF.709-715. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Jones BA, Dailey A, Calvocoressi L, et al. Inadequate follow-up of abnormal screening mammograms: findings from the race differences in screening mammography process study (United States) Cancer Causes Control. 2005;16(7):809–821. doi: 10.1007/s10552-005-2905-7. http://dx.doi.org/10.1007/s10552-005-2905-7. [DOI] [PubMed] [Google Scholar]
- 9.Gorin SS, Heck JE, Cheng B, Smith SJ. Delays in breast cancer diagnosis and treatment by racial/ethnic group. Arch Intern Med. 2006;166(20):2244–2252. doi: 10.1001/archinte.166.20.2244. http://dx.doi.org/10.1001/archinte.166.20.2244. [DOI] [PubMed] [Google Scholar]
- 10.Perez-Stable EJ, Afable-Munsuz A, Kaplan CP, et al. Factors influencing time to diagnosis after abnormal mammography in diverse women. J Womens Health (Larchmt) 2013;22(2):159–166. doi: 10.1089/jwh.2012.3646. http://dx.doi.org/10.1089/jwh.2012.3646. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Warner ET, Tamimi RM, Hughes ME, et al. Time to diagnosis and breast cancer stage by race/ethnicity. Breast Cancer Res Treat. 2012;136(3):813–821. doi: 10.1007/s10549-012-2304-1. http://dx.doi.org/10.1007/s10549-012-2304-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Wujcik D, Fair AM. Barriers to diagnostic resolution after abnormal mammography: a review of the literature. Cancer Nurs. 2008;31(5):E16–30. doi: 10.1097/01.NCC.0000305764.96732.45. http://dx.doi.org/10.1097/01.NCC.0000305764.96732.45. [DOI] [PubMed] [Google Scholar]
- 13.Ramirez AG, Perez-Stable EJ, Talavera GA, et al. Time to definitive diagnosis of breast cancer in Latina and non-Hispanic white women: the six cities study. Springerplus. 2013;2(1):84. doi: 10.1186/2193-1801-2-84. http://dx.doi.org/10.1186/2193-1801-2-84. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Battaglia TA, Santana MC, Bak S, et al. Predictors of timely follow-up after abnormal cancer screening among women seeking care at urban community health centers. Cancer. 2010;116(4):913–921. doi: 10.1002/cncr.24851. http://dx.doi.org/10.1002/cncr.24851. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Mojica CM, Bastani R, Ponce NA, Boscardin WJ. Latinas with abnormal breast findings: patient predictors of timely diagnostic resolution. J Womens Health (Larchmt) 2007;16(10):1468–1477. doi: 10.1089/jwh.2006.0324. http://dx.doi.org/10.1089/jwh.2006.0324. [DOI] [PubMed] [Google Scholar]
- 16.Kaplan CP, Crane LA, Stewart S, Juarez-Reyes M. Factors affecting follow-up among low-income women with breast abnormalities. J Womens Health (Larchmt) 2004;13(2):195–206. doi: 10.1089/154099904322966182. http://dx.doi.org/10.1089/154099904322966182. [DOI] [PubMed] [Google Scholar]
- 17.Partin MR, Gravely A, Gellad ZF, et al. Factors Associated With Missed and Cancelled Colonoscopy Appointments at Veterans Health Administration Facilities. Clin Gastroenterol Hepatol. 2016;14(2):259–267. doi: 10.1016/j.cgh.2015.07.051. http://dx.doi.org/10.1016/j.cgh.2015.07.051. [DOI] [PubMed] [Google Scholar]
- 18.Tosteson AN, Beaber EF, Tiro J, et al. Variation in Screening Abnormality Rates and Follow-Up of Breast, Cervical and Colorectal Cancer Screening within the PROSPR Consortium. J Gen Intern Med. doi: 10.1007/s11606-015-3552-7. In press. Online December 9, 2015. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Beaber EF, Kim JJ, Schapira MM, et al. Unifying screening processes within the PROSPR consortium: a conceptual model for breast, cervical, and colorectal cancer screening. J Natl Cancer Inst. 2015;107(6):djv120. doi: 10.1093/jnci/djv120. http://dx.doi.org/10.1093/jnci/djv120. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Tiro JA, Kamineni A, Levin TR, et al. The colorectal cancer screening process in community settings: a conceptual model for the population-based research optimizing screening through personalized regimens consortium. Cancer Epidemiol Biomarkers Prev. 2014;23(7):1147–1158. doi: 10.1158/1055-9965.EPI-13-1217. http://dx.doi.org/10.1158/1055-9965.EPI-13-1217. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.American College of Radiology. Breast imaging reporting and data system (BI-RADS) 4. Reston, VA: American College of Radiology; 2003. [Google Scholar]
- 22.Miglioretti DL, Rutter CM, Bradford SC, et al. Improvement in the diagnostic evaluation of a positive fecal occult blood test in an integrated health care organization. Med Care. 2008;46(9 Suppl 1):S91–96. doi: 10.1097/MLR.0b013e31817946c8. http://dx.doi.org/10.1097/MLR.0b013e31817946c8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Green BB, Anderson ML, Wang CY, et al. Results of nurse navigator follow-up after positive colorectal cancer screening test: a randomized trial. J Am Board Fam Med. 2014;27(6):789–795. doi: 10.3122/jabfm.2014.06.140125. http://dx.doi.org/10.3122/jabfm.2014.06.140125. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Fisher DA, Jeffreys A, Coffman CJ, Fasanella K. Barriers to full colon evaluation for a positive fecal occult blood test. Cancer Epidemiol Biomarkers Prev. 2006;15(6):1232–1235. doi: 10.1158/1055-9965.EPI-05-0916. http://dx.doi.org/10.1158/1055-9965.EPI-05-0916. [DOI] [PubMed] [Google Scholar]
- 25.Etzioni DA, Yano EM, Rubenstein LV, et al. Measuring the quality of colorectal cancer screening: the importance of follow-up. Dis Colon Rectum. 2006;49(7):1002–1010. doi: 10.1007/s10350-006-0533-2. http://dx.doi.org/10.1007/s10350-006-0533-2. [DOI] [PubMed] [Google Scholar]
- 26.Garman KS, Jeffreys A, Coffman C, Fisher DA. Colorectal cancer screening, comorbidity, and follow-up in elderly patients. Am J Med Sci. 2006;332(4):159–163. doi: 10.1097/00000441-200610000-00001. http://dx.doi.org/10.1097/00000441-200610000-00001. [DOI] [PubMed] [Google Scholar]
- 27.Partin MR, Burgess DJ, Burgess JF, Jr, et al. Organizational predictors of colonoscopy follow-up for positive fecal occult blood test results: an observational study. Cancer Epidemiol Biomarkers Prev. 2015;24(2):422–434. doi: 10.1158/1055-9965.EPI-14-1170. http://dx.doi.org/10.1158/1055-9965.EPI-14-1170. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Partin MR, Powell AA, Nugent S, Ordin DL. Colorectal cancer diagnosis improvement project evaluation demonstrates the importance of using multiple measures to track progress toward timeliness goals. J Healthc Qual. 2013;35(3):41–48. doi: 10.1111/j.1945-1474.2011.00188.x. http://dx.doi.org/10.1111/j.1945-1474.2011.00188.x. [DOI] [PubMed] [Google Scholar]
- 29.Linver MN, Osuch JR, Brenner RJ, Smith RA. The mammography audit: a primer for the mammography quality standards act (MQSA) Am J Roentgenol. 1995;165(1):19–25. doi: 10.2214/ajr.165.1.7785586. http://dx.doi.org/10.2214/ajr.165.1.7785586. [DOI] [PubMed] [Google Scholar]
- 30.Green BB, Coronado GD, Devoe JE, Allison J. Navigating the murky waters of colorectal cancer screening and health reform. Am J Public Health. 2014;104(6):982–986. doi: 10.2105/AJPH.2014.301877. http://dx.doi.org/10.2105/AJPH.2014.301877. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Doubeni CA. The impact of colorectal cancer screening on the U.S. population: is it time to celebrate? Cancer. 2014;120(18):2810–2813. doi: 10.1002/cncr.28789. http://dx.doi.org/10.1002/cncr.28789. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Levin TR, Jamieson L, Burley DA, Reyes J, Oehrli M, Caldwell C. Organized colorectal cancer screening in integrated health care systems. Epidemiol Rev. 2011;33(1):101–110. doi: 10.1093/epirev/mxr007. http://dx.doi.org/10.1093/epirev/mxr007. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.