Background: Insurance may lengthen or inhibit time to follow-up after positive screening mammography. We assessed the association between insurance status and time to initial diagnostic follow-up after a positive screening mammogram.

Methods: Using 1995–2010 data from a North Carolina population-based registry of breast imaging and cancer outcomes, we identified women with a positive screening mammogram. We compared receipt of follow-up within 60 days of screening using logistic regression and evaluated time to follow-up initiation using Cox proportional hazards regression.

Results: Among 43,026 women included in the study, 73% were <65 years and 27% were 65+ years. Median time until initial diagnostic follow-up was similar by age group and insurance status. In the adjusted model for women <65, uninsured women experienced a longer time to initiation of diagnostic follow-up [HR, 0.47; 95% confidence interval (CI), 0.25–0.89] versus women with private insurance. There were increased odds of these uninsured women not meeting the Centers for Disease Control and Prevention guideline for follow-up within 60 days (OR, 1.59; 95% CI, 1.31–1.94). Among women ages 65+, women with private insurance experienced a faster time to follow-up (adjusted HR, 2.09; 95% CI, 1.27–3.44) than women with Medicare and private insurance. Approximately 10% of women had no follow-up by 365 days.

Conclusions: We found differences in time to initial diagnostic follow-up after a positive screening mammogram by insurance status and age group. Uninsured women younger than 65 years at a positive screening event had delayed follow-up.

Impact: Replication of these findings and examination of their clinical significance warrant additional investigation. Cancer Epidemiol Biomarkers Prev; 25(11); 1474–82. ©2016 AACR.

This article is featured in Highlights of This Issue, p. 1447

Screening mammography has been associated with as much as a 20% reduction in breast cancer mortality among women ages 40 to 74 years (1, 2), and mammography remains the preferred method for breast cancer screening in the United States (1). An estimated 54% to 60% of breast cancers are detected via screening mammography (3–5), highlighting its importance in breast cancer detection. Approximately 10% of screening mammograms require additional follow-up imaging and about 2% require a biopsy (6, 7). A dimension of screening that may impact breast cancer mortality is the receipt of appropriate and timely follow-up after a positive screening mammogram, especially if the follow-up delays necessary treatment. Breast cancer screening via mammography is only effective in reducing mortality if followed by timely diagnosis and treatment.

Currently, the only U.S. guideline regarding the length of time in which follow-up should occur after a positive screening mammogram comes from the Centers for Disease Control and Prevention (CDC). The CDC guidelines recommend women with a positive screening mammogram complete diagnostic work-up within 60 days of the initial positive screen (8, 9). Delayed (>60 days, based on the CDC guideline, as defined in the literature) follow-up after a positive screening mammogram may contribute to disparities in breast cancer outcomes and subsequently mortality since follow-up times of 3 to 6 months has been associated with larger tumor size at diagnosis and reduced survival (10–14).

Many factors may contribute to prolonged initiation of diagnostic follow-up after a positive screening mammogram result (15). Healthcare system factors known to influence receipt of appropriate diagnostic follow-up include adequate communication with health care professionals, physician referral, and facility type (16, 17). Prior studies have investigated patient factors such as race, education, and rural/urban residence that influence diagnostic follow-up time (18). However, few studies have examined the influence of insurance on diagnostic follow-up time. Insurance status refers to whether someone is uninsured or insured and among those with insurance designates the specific insurance provider.

Although the impact of insurance status as a determinant of breast cancer care (access to screening, stage at diagnosis, receipt of treatment) has been well-documented (19–24), the effect of insurance status on time to diagnostic follow-up initiation after a positive screening mammogram is not well understood. Associations may vary by insurance status and prior studies often include members of a single insurance status or combine multiple insurance groups. The primary objective of this study is to assess the association between insurance status and the time to initiation of diagnostic follow-up after a positive screening mammogram in a large, racially diverse population-based breast cancer screening population.

Data and study population

We used data from the Carolina Mammography Registry (CMR), an NIH-funded, population-based breast imaging registry in North Carolina. CMR is an active member of the Breast Cancer Surveillance Consortium (BCSC) (25) and collects data from women undergoing breast imaging at community radiology facilities, from radiologists performing the imaging examinations, and from pathology data collected by the breast imaging facilities. The CMR data include patient demographics, patient risk factors (such as breast density and family history of breast cancer), the type of imaging performed, the reason for the examination, and the radiologists' assessment and recommendation for follow-up. These data are linked with cancer outcomes from the North Carolina Central Cancer Registry (NC-CCR) and abstracted hospital pathology reports as well as with vital status data from the State Center for Health Statistics.

This study includes data collected between 1995 and 2010 from women ages 40 and older undergoing screening mammography with non-missing insurance status and no personal history of breast cancer. At the time of the mammogram, the radiologist recorded whether the examination was a screening or diagnostic mammogram. A screening mammogram was defined using BCSC definitions (4, 26) and includes routine views of the breast among women without breast symptoms such as pain or lump. To be considered positive, the screening mammogram had to be assigned a Breast Imaging Reporting and Data System (BI-RADS) assessment of 0 (needs additional imaging), 4 (suspicious abnormality), 5 (highly suggestive of malignancy), or 3 (probably benign finding) coupled with the radiologist's recommendation for immediate follow-up (surgical consult, biopsy, or fine-needle aspiration) (26, 27). Among women with more than one positive screening mammogram in CMR, one positive screening exam was randomly selected. Women 65 years and older reporting no insurance were excluded from analyses due to small numbers (n = 24, <1% of the 65+ sample).

Exposure and outcome assessment

Insurance paying for the exam was self-reported by the women at the time of the screening mammogram and comprises the following categories: no insurance, Medicaid only, Medicare only, Medicare & Medicaid (usually referred to as “dual coverage”), Medicare & private, and private only. Initial diagnostic follow-up was defined as the first of subsequent breast imaging (such as diagnostic mammography, breast ultrasound, MRI) or breast biopsy following the positive screening mammogram. For each positive screening mammogram, we looked forward 1 year for subsequent imaging or biopsy and then ascertained the time until initial diagnostic follow-up as the number of days from the positive screening mammogram until the date of the first follow-up event, censoring at 365 days. A woman could have a follow-up time of zero days if the positive screening mammogram and the first diagnostic follow-up event were performed on the same day.

Covariates

Covariates of interest included demographic information as reported by the woman at the time of the mammogram using a standard patient questionnaire. These variables included: age (age at time of positive screening mammogram); race (black, white, Asian, Hispanic, American Indian, other); and education (less than high school diploma, high school graduate or equivalent, some college, college graduate).

An indicator of urban/rural patient residence was based on the zip code of the patient-provided address at the time of the positive screening mammogram. Breast density was reported at the time of the positive screening mammogram by the interpreting radiologist using BI-RADS breast density classifications of almost entirely fatty, scattered fibroglandular densities, heterogeneously dense, and extremely dense (28, 29). At the time of the screening mammogram, women self-reported family history of a first-degree relative with breast cancer and history of a breast biopsy. The facility at the time of screening mammography was categorized as Hospital, Radiology private office, Comprehensive cancer center, Hospital outpatient center, or Primary care. Primary care included OB/GYN office, mobile screening units, and multispecialty clinics. Guided by results from a systematic review of follow-up after positive screening mammography by Zapka and colleagues and a conceptual framework on cancer care delivery by Taplin and colleagues, we identified and selected covariates for inclusion in both the adjusted time-to-event models and the adjusted logistic regression models because these covariates represent potential confounders in the relationship between insurance status and time to follow-up after a positive screening mammogram (30, 31). In addition, previous studies identified the following covariates as risk factors for delays in follow-up after a positive screening mammography or for breast cancer: age, race (black non-Hispanic, white non-Hispanic, and other), education, breast density, history of breast biopsy, family history of breast cancer, and facility type (18, 31–34).

Statistical analysis

We described time to initial diagnostic follow-up for the study population by insurance status and age group at the time of the positive screening mammogram. Analyses were conducted separately for women younger than 65 years and for women 65 years and older at the time of the positive mammographic result because of the age-specific eligibility requirements of Medicare.

We calculated median time until initial diagnostic follow-up with interquartile range (IQR) and used the Kaplan–Meier estimator to construct time-to-event curves within strata of insurance using the first follow-up event as the endpoint (23). We confirmed the proportional hazards assumption by graphing the logs of the cumulative hazards. We then used the Cox proportional hazards regression model to estimate HRs and 95% confidence intervals (CI) to evaluate the association between insurance status and initial diagnostic follow-up after a positive screening mammogram. Women were administratively censored at 365 days after the positive screening mammogram if a follow-up event did not occur or at the time that the mammography facility at which they received their positive screening mammogram stopped reporting data to the CMR (if applicable), whichever came first.

We also used multivariable logistic regression to estimate ORs and 95% CIs for time to initial follow-up beyond 60 days based on the CDC guidelines. In both sets of models, the referent group for women younger than 65 years was private insurance alone. The referent group in the models for ages 65 and older was Medicare & private; among the older women, it was the most populous category for this age group. These models included women who did not receive follow-up within the study window. All P values were 2-sided and α <0.05 was considered statistically significant. Statistical analyses were performed using SAS v9.2 (SAS Institute). This ancillary study of CMR data was conducted with approval from the Institutional Review Board at The University of North Carolina at Chapel Hill.

In the study population, approximately 81% of women included in the study self-reported their race as non-Hispanic white and 12% reported non-Hispanic black (Table 1). The mean age for the study population was 57 years (SD, 12). The majority of women younger than 65 years of age reported having private insurance (89%) followed by Medicare plus private (18%). Although black women younger than 65 years represented 13% of the age group, they accounted for 16% of the uninsured in that age group. The majority (60%) of women 65 years and older reported Medicare & private insurance followed by Medicare only (22%).

Table 1.

Demographic distribution of women ages 40 years and older receiving a positive screening mammogram between 1995–2010 by insurance status stratifying by women younger than 65 years and women 65 years and older

Insurance status
AllNo insuranceaMedicaid onlyMedicare onlyMedicare & MedicaidMedicare & privatePrivate only
n (%)n (%)n (%)n (%)n (%)n (%)n (%)
Age <65 y 
 Total 31,194 916 (3) 934 (3) 634 (2) 475 (1) 592 (2) 27,643 (89) 
Race/Ethnicity 
 Black, non-Hispanic 3,916 (13) 144 (16) 374 (40) 165 (26) 178 (37) 108 (18) 2,947 (11) 
 White, non-Hispanic 24,969 (80) 665 (73) 458 (49) 423 (67) 269 (57) 444 (75) 22,710 (82) 
 Other 859 (3) 82 (9) 40 (4) b b 15 (3) 703 (3) 
 Unknown 1,450 (5) 25 (3) 62 (7) b b 25 (4) 1,283 (5) 
Age, y 
 40–44 7,307 (23) 212 (23) 276 (30) 64 (10) 62 (13) 35 (6) 6,658 (24) 
 45–49 7,040 (22) 220 (24) 204 (22) 98 (15) 97 (20) 72 (12) 6,349 (23) 
 50–54 6,648 (21) 184 (20) 184 (20) 121 (19) 105 (22) 109 (18) 5,945 (22) 
 55–59 5,590 (18) 144 (16) 159 (17) 165 (26) 109 (23) 162 (27) 4,851 (18) 
 60–64 4,609 (15) 156 (17) 111 (12) 186 (29) 102 (21) 214 (36) 3,840 (14) 
Education 
 <High school 1,580 (5) 140 (15) 227 (24) 107 (17) 141 (30) 59 (10) 906 (3) 
 High school/GED 6,692 (21) 295 (32) 273 (29) 204 (32) 142 (30) 183 (31) 5,595 (20) 
 Some college 7,286 (23) 206 (22) 167 (18) 130 (21) 64 (13) 140 (24) 6,579 (24) 
 College graduate 8,372 (27) 103 (11) 59 (6) 48 (8) 25 (5) 103 (17) 8,034 (29) 
 Unknown 7,264 (23) 172 (19) 208 (22) 145 (23) 103 (22) 107 (18) 6,529 (24) 
Age 65+ y 
 Total 11,832 — 192 (2) 2,617 (22) 753 (6) 7,087 (60) 1,183 (10) 
Race/Ethnicity 
 Black, non-Hispanic 1,226 (10) — 46 (24) 363 (14) 285 (38) 422 (6) 110 (9) 
 White, non-Hispanic 9,883 (83) — 132 (69) 2,115 (81) 408 (54) 6,245 (88) 983 (83) 
 Other 134 (1) — b 27 (1) b 71 (1) 19 (2) 
 Unknown 589 (5) — b 112 (4) b 349 (5) 71 (6) 
Age, y 
 65–69 4,342 (37) — 80 (42) 920 (35) 222 (29) 2,354 (33) 766 (65) 
 70–74 3,320 (28) — 49 (26) 753 (29) 204 (27) 2,086 (29) 228 (19) 
 75+ 4,170 (35) — 63 (33) 944 (36) 327 (43) 2,647 (37) 189 (16) 
Education 
 <High school 1,632 (14) — 62 (32) 457 (17) 297 (39) 705 (10) 111 (9) 
 High school/GED 3,767 (32) — 58 (30) 892 (34) 195 (26) 2,277 (32) 345 (29) 
 Some college 2,291 (19) — 20 (10) 403 (15) 65 (9) 1,564 (22) 239 (20) 
 College graduate 1,579 (13) — 17 (9) 267 (10) 25 (3) 1,106 (16) 164 (14) 
 Unknown 2,563 (22) — 35 (18) 598 (23) 171 (23) 1,435 (20) 324 (27) 
Insurance status
AllNo insuranceaMedicaid onlyMedicare onlyMedicare & MedicaidMedicare & privatePrivate only
n (%)n (%)n (%)n (%)n (%)n (%)n (%)
Age <65 y 
 Total 31,194 916 (3) 934 (3) 634 (2) 475 (1) 592 (2) 27,643 (89) 
Race/Ethnicity 
 Black, non-Hispanic 3,916 (13) 144 (16) 374 (40) 165 (26) 178 (37) 108 (18) 2,947 (11) 
 White, non-Hispanic 24,969 (80) 665 (73) 458 (49) 423 (67) 269 (57) 444 (75) 22,710 (82) 
 Other 859 (3) 82 (9) 40 (4) b b 15 (3) 703 (3) 
 Unknown 1,450 (5) 25 (3) 62 (7) b b 25 (4) 1,283 (5) 
Age, y 
 40–44 7,307 (23) 212 (23) 276 (30) 64 (10) 62 (13) 35 (6) 6,658 (24) 
 45–49 7,040 (22) 220 (24) 204 (22) 98 (15) 97 (20) 72 (12) 6,349 (23) 
 50–54 6,648 (21) 184 (20) 184 (20) 121 (19) 105 (22) 109 (18) 5,945 (22) 
 55–59 5,590 (18) 144 (16) 159 (17) 165 (26) 109 (23) 162 (27) 4,851 (18) 
 60–64 4,609 (15) 156 (17) 111 (12) 186 (29) 102 (21) 214 (36) 3,840 (14) 
Education 
 <High school 1,580 (5) 140 (15) 227 (24) 107 (17) 141 (30) 59 (10) 906 (3) 
 High school/GED 6,692 (21) 295 (32) 273 (29) 204 (32) 142 (30) 183 (31) 5,595 (20) 
 Some college 7,286 (23) 206 (22) 167 (18) 130 (21) 64 (13) 140 (24) 6,579 (24) 
 College graduate 8,372 (27) 103 (11) 59 (6) 48 (8) 25 (5) 103 (17) 8,034 (29) 
 Unknown 7,264 (23) 172 (19) 208 (22) 145 (23) 103 (22) 107 (18) 6,529 (24) 
Age 65+ y 
 Total 11,832 — 192 (2) 2,617 (22) 753 (6) 7,087 (60) 1,183 (10) 
Race/Ethnicity 
 Black, non-Hispanic 1,226 (10) — 46 (24) 363 (14) 285 (38) 422 (6) 110 (9) 
 White, non-Hispanic 9,883 (83) — 132 (69) 2,115 (81) 408 (54) 6,245 (88) 983 (83) 
 Other 134 (1) — b 27 (1) b 71 (1) 19 (2) 
 Unknown 589 (5) — b 112 (4) b 349 (5) 71 (6) 
Age, y 
 65–69 4,342 (37) — 80 (42) 920 (35) 222 (29) 2,354 (33) 766 (65) 
 70–74 3,320 (28) — 49 (26) 753 (29) 204 (27) 2,086 (29) 228 (19) 
 75+ 4,170 (35) — 63 (33) 944 (36) 327 (43) 2,647 (37) 189 (16) 
Education 
 <High school 1,632 (14) — 62 (32) 457 (17) 297 (39) 705 (10) 111 (9) 
 High school/GED 3,767 (32) — 58 (30) 892 (34) 195 (26) 2,277 (32) 345 (29) 
 Some college 2,291 (19) — 20 (10) 403 (15) 65 (9) 1,564 (22) 239 (20) 
 College graduate 1,579 (13) — 17 (9) 267 (10) 25 (3) 1,106 (16) 164 (14) 
 Unknown 2,563 (22) — 35 (18) 598 (23) 171 (23) 1,435 (20) 324 (27) 

aWomen reporting no insurance 65 years and older were removed from the models due to small sample size (n = 24).

bCell counts < 11 have been suppressed.

For the study cohort, the median time until initial diagnostic follow-up after a positive screening mammogram was 12 days (IQR, 7–22 days). Women younger than 65 years with no insurance experienced a median follow-up of 16 days (IQR, 8–37 days) compared to women with private insurance, who had a median of 12 days (IQR, 7–21 days; Table 2). Among women 65 years and older, those with Medicare & Medicaid experienced a median follow-up of 14 days (IQR, 8–29 days), whereas women with private insurance experienced a median of 12 days (IQR, 7–21 days). The Kaplan–Meier survivor curves, stratified by insurance status for women younger than 65 years of age (Fig. 1) and those 65 years and older (Fig. 2), show differences by insurance status in initial follow-up time were observed for the 365-day study period (P < 0.01).

Table 2.

Median and mean time to initial diagnostic follow-up in days, proportion with follow-up greater than 60 days, and proportion with no follow-up for women ages 40 years and older receiving a positive screening mammogram between 1995–2010 by insurance status, stratified at 65 years of age

Insurance statusMedian (IQR)aMean (SD)Percentage with follow-up > 60 dPercentage with no follow-up within 365 d
All 12 (7–22) 43 (116) 11.9 10.1 
Age <65 y 
 No insurance 16 (8–37) 62 (166) 17.5 13.8 
 Medicaid only 14 (7–27) 47 (121) 12.9 8.5 
 Medicare only 15 (8–28) 53 (159) 15.5 9.6 
 Medicare & Medicaid 14 (8–29) 60 (220) 14.0 9.5 
 Medicare & private 13 (7–24) 42 (80) 13.0 8.2 
 Private only 12 (7–21) 40 (108) 11.0 10.9 
 All, <65 12 (7–22) 41 (114) 11.4 10.8 
Age 65+ y 
 Medicare only 13 (7–26) 54 (135) 14.5 8.8 
 Medicare & Medicaid 14 (8–29) 55 (142) 15.9 8.8 
 Medicare & private 12 (7–21) 44 (118) 12.5 7.7 
 Private only 12 (7–21) 40 (87) 11.5 10.6 
 All, 65+ 13 (7–22) 46 (121) 13.2 8.3 
Insurance statusMedian (IQR)aMean (SD)Percentage with follow-up > 60 dPercentage with no follow-up within 365 d
All 12 (7–22) 43 (116) 11.9 10.1 
Age <65 y 
 No insurance 16 (8–37) 62 (166) 17.5 13.8 
 Medicaid only 14 (7–27) 47 (121) 12.9 8.5 
 Medicare only 15 (8–28) 53 (159) 15.5 9.6 
 Medicare & Medicaid 14 (8–29) 60 (220) 14.0 9.5 
 Medicare & private 13 (7–24) 42 (80) 13.0 8.2 
 Private only 12 (7–21) 40 (108) 11.0 10.9 
 All, <65 12 (7–22) 41 (114) 11.4 10.8 
Age 65+ y 
 Medicare only 13 (7–26) 54 (135) 14.5 8.8 
 Medicare & Medicaid 14 (8–29) 55 (142) 15.9 8.8 
 Medicare & private 12 (7–21) 44 (118) 12.5 7.7 
 Private only 12 (7–21) 40 (87) 11.5 10.6 
 All, 65+ 13 (7–22) 46 (121) 13.2 8.3 

aIQR reported as a range; from the 25th percentile to the 75th percentile.

Figure 1.

Comparison of the Kaplan–Meier estimates of the time-to-event curve stratified by insurance status for women less than 65 years old receiving a positive screening mammogram between 1995–2010. Tick marks represent observations in time as each woman experiences the follow-up event.

Figure 1.

Comparison of the Kaplan–Meier estimates of the time-to-event curve stratified by insurance status for women less than 65 years old receiving a positive screening mammogram between 1995–2010. Tick marks represent observations in time as each woman experiences the follow-up event.

Close modal
Figure 2.

Comparison of the Kaplan–Meier estimates of the time-to-event curve stratified by insurance status for women 65 years and older receiving a positive screening mammogram between 1995–2010. Tick marks represent observations in time as each woman experiences the follow-up event.

Figure 2.

Comparison of the Kaplan–Meier estimates of the time-to-event curve stratified by insurance status for women 65 years and older receiving a positive screening mammogram between 1995–2010. Tick marks represent observations in time as each woman experiences the follow-up event.

Close modal

In the time-to-event analysis, approximately 10% of women had no follow-up in the study period (365 days) after their positive screening mammogram (Table 2). While the proportions of women who did and who did not receive follow-up during the study period differed statistically by race, age, education level, and breast density (P < 0.0001), the differences in proportions were small (Supplementary Table S1). Among women who received no follow-up during the study period, there were slight differences in ever receiving follow-up by age group. Women 65 years and older were more likely to receive follow-up within the study period of 365 days than women younger than 65 years (8% vs. 11% with no follow-up within 365 days, respectively).

In the adjusted time-to-event model for women younger than 65 years, when compared with women with private insurance, uninsured women experienced a longer time to initial diagnostic follow-up with HR of 0.47 (95% CI, 0.25–0.89; Table 3). Among women younger than 65 years, we did not observe statistically significant differences between private insurance only (the referent group) and the following insurance groups: Medicaid only, Medicare only, Medicare & Medicaid, and Medicare & private, although all but Medicare & private had HRs less than 1.0. In the adjusted model, among women 65 years and older, when compared with those with Medicare plus private insurance, women with private insurance experienced a faster time to initiation of follow-up with HR of 2.09 (95% CI, 1.27–3.44). Among women 65 years and older, we did not observe statistically significant differences between Medicare & private insurance (the referent group) and the following insurance groups: Medicare, and Medicare & Medicaid. In the model including all other covariates, among women 65 years and older with an assessment of BI-RADS, 5 experienced a faster time to initial diagnostic follow-up when compared with women with an assessment of BI-RADS 0 in the same age category (HR, 1.62; 95% CI, 1.09–2.42). We did not observe statistically significant differences for BI-RADS assessment among women younger than 65 years.

Table 3.

Unadjusted and adjusted HR estimates and 95% CIs of the association between insurance status and time to initial diagnostic follow-up after a positive screening mammogram for women younger than 65 years and women 65 years and older between 1995–2010

UnadjustedAdjustedb
Insurance statusHR (95% CI)PaHR (95% CI)Pa
Age <65 y 
 No insurance 0.59 (0.33–1.06) 0.08 0.47 (0.25–0.89) 0.02 
 Medicaid only 0.75 (0.44–1.28) 0.28 0.81 (0.46–1.42) 0.46 
 Medicare only 0.86 (0.44–1.67) 0.65 0.95 (0.47–1.91) 0.88 
 Medicare & Medicaid 0.63 (0.32–1.24) 0.18 0.50 (0.24–1.02) 0.06 
 Medicare & private 2.16 (1.07–4.38) 0.03 1.81 (0.86–3.83) 0.12 
 Private only (referent) 1.00 (—) — 1.00 (—) — 
Age 65+ y 
 Medicare only 0.89 (0.66–1.20) 0.44 0.97 (0.70–1.34) 0.83 
 Medicare & Medicaid 0.79 (0.49–1.27) 0.33 0.99 (0.57–1.74) 0.99 
 Medicare & private (referent) 1.00 (—) — 1.00 (—) — 
 Private only 1.92 (1.22–3.03) 0.005 2.09 (1.27–3.44) <0.01 
UnadjustedAdjustedb
Insurance statusHR (95% CI)PaHR (95% CI)Pa
Age <65 y 
 No insurance 0.59 (0.33–1.06) 0.08 0.47 (0.25–0.89) 0.02 
 Medicaid only 0.75 (0.44–1.28) 0.28 0.81 (0.46–1.42) 0.46 
 Medicare only 0.86 (0.44–1.67) 0.65 0.95 (0.47–1.91) 0.88 
 Medicare & Medicaid 0.63 (0.32–1.24) 0.18 0.50 (0.24–1.02) 0.06 
 Medicare & private 2.16 (1.07–4.38) 0.03 1.81 (0.86–3.83) 0.12 
 Private only (referent) 1.00 (—) — 1.00 (—) — 
Age 65+ y 
 Medicare only 0.89 (0.66–1.20) 0.44 0.97 (0.70–1.34) 0.83 
 Medicare & Medicaid 0.79 (0.49–1.27) 0.33 0.99 (0.57–1.74) 0.99 
 Medicare & private (referent) 1.00 (—) — 1.00 (—) — 
 Private only 1.92 (1.22–3.03) 0.005 2.09 (1.27–3.44) <0.01 

aAll P values are 2-sided, and α < 0.05 was considered statistically significant.

bThe adjusted model includes race, education, breast density, categorical age, history of breast biopsy, family history of breast cancer, and facility type.

In the logistic regression analysis, about 12% of all women in the study did not receive initial diagnostic follow-up within 60 days of their positive screening mammogram as recommended by CDC guidelines. This 12% includes women who received follow-up beyond 60 days and those who do not receive follow-up within 365 days (Table 2). Among women younger than 65 years, nearly 18% of women without insurance received initial diagnostic follow-up after 60 days compared with 11% of women with private insurance. Women 65 years and older were slightly more likely than younger women to have follow-up greater than 60 days (13%). Among women 65 years and older, women reporting Medicare & Medicaid were slightly more likely to receive initial follow-up after 60 days.

In the adjusted logistic regression model for women younger than 65 years, when compared with women with private insurance, uninsured women had increased odds of delay (OR, 1.59; 95% CI, 1.31–1.94; Table 4). No other insurance groups among women younger than 65 years indicated significant odds of delay. Among women 65 years and older, we did not observe statistically significant differences between Medicare & private insurance (the referent group) and the other insurance groups in adjusted models. We did not find modification of the insurance–delay relationship by educational status for either age group.

Table 4.

Unadjusted and adjusted OR estimates and 95% CIs of the association between insurance status and time to initial diagnostic follow-up of more than 60 days after a positive screening mammogram for women younger than 65 years and women 65 years and older between 1995–2010

UnadjustedAdjustedb
Insurance statusOR (95% CI)PaOR (95% CI)Pa
Age <65 y 
 No insurance 1.61 (1.38–1.89) <0.0001 1.59 (1.31–1.94) <0.0001 
 Medicaid only 0.97 (0.82–1.14) 0.70 1.00 (0.82–1.21) 0.96 
 Medicare only 1.19 (0.98–1.43) 0.08 1.21 (0.97–1.52) 0.09 
 Medicare & Medicaid 1.09 (0.88–1.36) 0.43 1.09 (0.85–1.42) 0.49 
 Medicare & private 0.95 (0.77–1.17) 0.62 1.10 (0.87–1.40) 0.43 
 Private only (referent) 1.00 (—) — 1.00 (—) — 
Age 65+ y 
 Medicare only 1.21 (1.08–1.35) 0.001 1.14 (0.99–1.30) 0.06 
 Medicare & Medicaid 1.29 (1.08–1.56) 0.006 0.96 (0.76–1.20) 0.73 
 Medicare & private (referent) 1.00 (—) — 1.00 (—) — 
 Private only 1.12 (0.96–1.31) 0.16 1.14 (0.95–1.36) 0.16 
UnadjustedAdjustedb
Insurance statusOR (95% CI)PaOR (95% CI)Pa
Age <65 y 
 No insurance 1.61 (1.38–1.89) <0.0001 1.59 (1.31–1.94) <0.0001 
 Medicaid only 0.97 (0.82–1.14) 0.70 1.00 (0.82–1.21) 0.96 
 Medicare only 1.19 (0.98–1.43) 0.08 1.21 (0.97–1.52) 0.09 
 Medicare & Medicaid 1.09 (0.88–1.36) 0.43 1.09 (0.85–1.42) 0.49 
 Medicare & private 0.95 (0.77–1.17) 0.62 1.10 (0.87–1.40) 0.43 
 Private only (referent) 1.00 (—) — 1.00 (—) — 
Age 65+ y 
 Medicare only 1.21 (1.08–1.35) 0.001 1.14 (0.99–1.30) 0.06 
 Medicare & Medicaid 1.29 (1.08–1.56) 0.006 0.96 (0.76–1.20) 0.73 
 Medicare & private (referent) 1.00 (—) — 1.00 (—) — 
 Private only 1.12 (0.96–1.31) 0.16 1.14 (0.95–1.36) 0.16 

aAll P values are 2-sided, and α < 0.05 was considered statistically significant.

bThe adjusted model includes race, education, breast density, categorical age, history of breast biopsy, family history of breast cancer, and facility type.

We examined insurance as a predictor of time to initial diagnostic follow-up in a large population-based mammography registry and found that among women younger than 65 years, women without insurance experienced a longer time to initial diagnostic follow-up compared to women with private insurance. It is important to note that the difference in days to initiation between the insurance groups is small and may not represent a clinically significant difference. Among women ages 65 and older, women with private only insurance experienced a faster time to initial diagnostic follow-up compared with women with Medicare and private insurance. These women may be more economically advantaged with increased access to care. In the multivariable logistic regression models, uninsured women younger than 65 years of age were 1.59 times more likely to experience a delay when compared with the privately insured in the same age group. There were no observed statistically significant associations between insurance status and delay among women 65 years of age and older.

Few population-based studies have examined the impact of insurance status and time until initial diagnostic follow-up after a positive screening mammogram. A study of time between initial consult and diagnosis reports HR estimates of 4 levels of insurance and the uninsured, but includes women with symptoms (35). Other studies focused on homogenous populations including, for example, only Medicaid beneficiaries (18, 36, 37). In many studies of breast cancer outcomes, Medicaid enrollment is a predictor of poor health outcomes (20, 35, 38, 39). In this study, we did not find that Medicaid insurance was associated with a longer time to initial diagnostic follow-up after a positive screening mammogram, regardless of age group.

Other studies combined insurance groups, specifically Medicare and Medicaid to create a public or government category and compared this to all others included in the study (33, 40–43). Similarly, another study grouped Medicaid and those without insurance (44), which may mask benefits in time to follow-up experienced by those with Medicaid. This may lead to less informative conclusions because eligibility requirements for government-sponsored insurance programs such as Medicare and Medicaid are largely based on specific guidelines for age, income status, and disability status (45, 46). In addition, the insurance categories may represent populations with varying barriers for seeking care such as disability or comorbidities. An urban hospital-based study found that women with private insurance reached resolution of their positive mammogram faster than those with government insurance, a combination of people with Medicare and Medicaid (47). A recent study of women enrolled in a patient navigation program assessing the impact of barriers to care after a positive screen, one of which was insurance, reported that women with an insurance barrier experienced a longer time to diagnostic follow-up after a positive screening mammogram (HR, 0.85; 95% CI, 0.74–0.97; ref. 48). Another study comparing those with no insurance to those with only hospitalization insurance found that insurance was not associated with completing diagnostic follow-up (49). While these studies provided helpful information regarding a broad effect of insurance on resolution of a positive mammogram, they do not provide information on how resolution of a positive screening mammogram may vary by specific categories of insurance.

Median follow-up times to initial diagnostic follow-up in the current study were similar to prior studies (40, 50, 51). Specifically, a study of women attending an urban academic medical center in a federally designated medically underserved area reported a median follow-up time (defined as days between the positive mammogram and additional imaging) of 14 days (40). However, this study did not investigate differences by insurance status. Other studies report median time to complete follow-up between 20 and 50 days (32, 33, 49, 52).

In the current time-to-event analysis, 10% of women had no initial diagnostic follow-up within 365 days of their positive screening mammogram. It is challenging to compare our results regarding no follow-up with other studies as many studies fail to describe women with no follow-up after a positive screening mammogram (32, 53, 54) or exclude these women from the analysis (55). It may be the case that women who never receive follow-up are different than those who are delayed but do eventually receive follow-up.

In the current study, nearly 12% of women did not receive initial diagnostic follow-up within 60 days after a positive screening mammogram. A study of CDC's National Breast and Cervical Cancer Early Detection screening program found that 20% of women did not receive any diagnostic follow-up within 60 days of a positive screening mammogram (37). Other studies of complete diagnostic follow-up after a positive screening mammogram report similar results: 20% to 40% of women receive diagnostic follow-up more than 60 days after a positive screening mammogram or fail to receive diagnostic follow-up entirely (36, 37, 52, 56, 57). These estimates are slightly higher than those reported in our study and may be explained by differences in study populations, as these studies were conducted in hospitals or academic medical centers and our population represents women screened in community practices. Although there are no national or population-based estimates for the proportion of positive screening mammograms that do not receive diagnostic follow-up with which to compare, our study falls within the reported range (9%–50%) from other studies (30, 31, 57, 58).

It is uncertain if the differences of a few days, as illustrated by the median differences, in initial follow-up after a positive screening mammogram by insurance status represent variation of clinical significance. Medians may mask extreme differences in follow-up. We also provide results in terms of the dichotomous outcome of having received follow-up within 60 days, as recommended by the CDC. By presenting estimates from both sets of models by insurance type, we give more information about differences in delay. Recognizing potential delays experienced at follow-up and diagnosis may be important when considering the breast cancer care continuum and potential delays experienced at other points of care coordination such as treatment. As previously shown, delays in diagnosis may be indicative of delays in treatment (34).

The strengths of our study include the use of prospectively collected data, a diverse population, and large sample size. Moreover, the CMR data are longitudinal providing the opportunity to follow individual women receiving screening mammograms and subsequent breast imaging and biopsy. Prior studies were often limited by small sample sizes or focused on one insurance status and did not allow for examination by more insurance categories while also including the uninsured. In addition, previous studies frequently relied on administrative databases designed for billing purposes rather than research and thus lack crucial information on the mammogram result. Exclusive use of patient questionnaires or medical records may lack complete dates of services to ensure sufficient documentation of time until diagnostic follow-up. In contrast, the CMR data contain detailed information on breast imaging procedures performed including the date of procedure as well as the radiologists' interpretation of the mammogram.

Our study also has several limitations. Insurance status from the CMR is self-reported and may not be completely accurate. We are unable to confirm the payer for each imaging and biopsy received during the study period. However, other studies found that self-report of insurance payer can be fairly accurate for both mammography (59) and non-mammography settings (60, 61). It is also possible that some follow-up visits were not captured in the CMR if a woman received her diagnostic follow-up care outside of the CMR catchment area. There may be bias due to unmeasured confounding. Some factors that may influence healthcare outcomes are not collected by CMR such as income, co-morbidities, access to transportation, social support, etc. It is possible that these factors may impact the patient's screening behaviors such as the ability to undergo diagnostic procedures or the frequency with which they interact with the healthcare system and could explain the differences in follow-up observed in this study (62). Furthermore, patient-reported outcomes after a positive screening mammogram such as anxiety, fear, stress, satisfaction with care received at the time of the screening mammogram, and quality of life have been shown to impact delays in follow-up and while beyond the scope of our analyses should be considered in future work (16, 38, 43, 48, 58). Finally, we were unable to assess the potential interaction between insurance status and known factors associated with diagnostic delay (such as race and education) due to small numbers but this remains another important area of future work.

In summary, to maximize the benefits of screening mammography, it is important that women receive appropriate and timely follow-up after a positive screening mammogram, especially if the follow-up delays necessary treatment. In addition, it is important to understand how insurance impacts follow-up after a positive screening mammogram. We found differences in time to initial diagnostic follow-up after a positive screening mammogram by insurance status as well as by age group. Our findings that 8% to 14% of women with a positive screening mammogram do not receive follow-up within 365 days is concerning, as this may have a significant clinical impact on time to diagnosis and receipt of treatment. Future research on the variation in the proportion of women with no follow-up at 365 days by insurance status should be undertaken to further understand how to target groups experiencing longer time to follow-up.

No potential conflicts of interest were disclosed.

Conception and design: D.D. Durham, W.R. Robinson, S.B. Wheeler, K.E. Reeder-Hayes, J.M. Bowling, A.F. Olshan, L.M. Henderson

Development of methodology: D.D. Durham, S.S. Lee, S.B. Wheeler, K.E. Reeder-Hayes, J.M. Bowling, A.F. Olshan, L.M. Henderson

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): L.M. Henderson

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): D.D. Durham, W.R. Robinson, S.B. Wheeler, K.E. Reeder-Hayes, J.M. Bowling, A.F. Olshan, L.M. Henderson

Writing, review, and/or revision of the manuscript: D.D. Durham, W.R. Robinson, S.S. Lee, S.B. Wheeler, K.E. Reeder-Hayes, A.F. Olshan, L.M. Henderson

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): A.F. Olshan, L.M. Henderson

Study supervision: J.M. Bowling, L.M. Henderson

The study was supported by grants F31CA180755 (NCI NIH) to D.D. Durham, K01CA172717 (NCI NIH) to W.R. Robinson, and 5U01CA070040-15 (NCI NIH) and P01CA154292 (NCI NIH) to L.M. Henderson.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

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