Factors Associated With Rates of False-Positive and False-Negative Results From Digital Mammography Screening: An Analysis of Registry Data.

BACKGROUND: Women screened with digital mammography may receive false-positive and false-negative results and subsequent imaging and biopsies. How these outcomes vary by age, time since the last screening, and individual risk factors is unclear. OBJECTIVE: To determine factors associated with false-positive and false-negative digital mammography results, additional imaging, and biopsies among a general population of women screened for breast cancer. DESIGN: Analysis of registry data. SETTING: Participating facilities at 5 U.S. Breast Cancer Surveillance Consortium breast imaging registries with linkages to pathology databases and tumor registries. PATIENTS: 405,191 women aged 40 to 89 years screened with digital mammography between 2003 and 2011. A total of 2963 were diagnosed with invasive cancer or ductal carcinoma in situ within 12 months of screening. MEASUREMENTS: Rates of false-positive and false-negative results and recommendations for additional imaging and biopsies from a single screening round; comparisons by age, time since the last screening, and risk factors. RESULTS: Rates of false-positive results (121.2 per 1000 women [95% CI, 105.6 to 138.7]) and recommendations for additional imaging (124.9 per 1000 women [CI, 109.3 to 142.3]) were highest among women aged 40 to 49 years and decreased with increasing age. Rates of false-negative results (1.0 to 1.5 per 1000 women) and recommendations for biopsy (15.6 to 17.5 per 1000 women) did not differ greatly by age. Results did not differ by time since the last screening. False-positive rates were higher for women with risk factors, particularly family history of breast cancer; previous benign breast biopsy result; high breast density; and, for younger women, low body mass index. LIMITATIONS: Confounding by variation in patient-level characteristics and outcomes across registries and regions may have been present. Some factors, such as numbers of first- and second-degree relatives with breast cancer and diagnoses associated with previous benign biopsy results, were not examined. CONCLUSION: False-positive mammography results and additional imaging are common, particularly for younger women and those with risk factors, whereas biopsies occur less often. Rates of false-negative results are low. PRIMARY FUNDING SOURCE: Agency for Healthcare Research and Quality and National Cancer Institute.

Validation of a Medicare Claims-based Algorithm for Identifying Breast Cancers Detected at Screening Mammography.

BACKGROUND: The breast cancer detection rate is a benchmark measure of screening mammography quality, but its computation requires linkage of mammography interpretive performance information with cancer incidence data. A Medicare claims-based measure of detected breast cancers could simplify measurement of this benchmark and facilitate mammography quality assessment and research. OBJECTIVES: To validate a claims-based algorithm that can identify with high positive predictive value (PPV) incident breast cancers that were detected at screening mammography. RESEARCH DESIGN: Development of a claims-derived algorithm using classification and regression tree analyses within a random half-sample of Medicare screening mammography claims followed by validation of the algorithm in the remaining half-sample using clinical data on mammography results and cancer incidence from the Breast Cancer Surveillance Consortium (BCSC). SUBJECTS: Female fee-for-service Medicare enrollees aged 68 years and older who underwent screening mammography from 2001 to 2005 within BCSC registries in 4 states (CA, NC, NH, and VT), enabling linkage of claims and BCSC mammography data (N=233,044 mammograms obtained by 104,997 women). MEASURES: Sensitivity, specificity, and PPV of algorithmic identification of incident breast cancers that were detected by radiologists relative to a reference standard based on BCSC mammography and cancer incidence data. RESULTS: An algorithm based on subsequent codes for breast cancer diagnoses and treatments and follow-up mammography identified incident screen-detected breast cancers with 92.9% sensitivity [95% confidence interval (CI), 91.0%-94.8%], 99.9% specificity (95% CI, 99.9%-99.9%), and a PPV of 88.0% (95% CI, 85.7%-90.4%). CONCLUSIONS: A simple claims-based algorithm can accurately identify incident breast cancers detected at screening mammography among Medicare enrollees. The algorithm may enable mammography quality assessment using Medicare claims alone.

Distinguishing screening from diagnostic mammograms using Medicare claims data.

BACKGROUND: Medicare claims data may be a fruitful data source for research or quality measurement in mammography. However, it is uncertain whether claims data can accurately distinguish screening from diagnostic mammograms, particularly when claims are not linked with cancer registry data. OBJECTIVES: To validate claims-based algorithms that can identify screening mammograms with high positive predictive value (PPV) in claims data with and without cancer registry linkage. RESEARCH DESIGN: Development of claims-derived algorithms using classification and regression tree analyses within a random half-sample of bilateral mammogram claims with validation in the remaining half-sample. SUBJECTS: Female fee-for-service Medicare enrollees aged 66 years and older, who underwent bilateral mammography from 1999 to 2005 within Breast Cancer Surveillance Consortium (BCSC) registries in 4 states (CA, NC, NH, and VT), enabling linkage of claims and BCSC mammography data (N=383,730 mammograms obtained from 146,346 women). MEASURES: Sensitivity, specificity, and PPV of algorithmic designation of a "screening" purpose of the mammogram using a BCSC-derived reference standard. RESULTS: In claims data without cancer registry linkage, a 3-step claims-derived algorithm identified screening mammograms with 97.1% sensitivity, 69.4% specificity, and a PPV of 94.9%. In claims that are linked to cancer registry data, a similar 3-step algorithm had higher sensitivity (99.7%), similar specificity (62.7%), and higher PPV (97.4%). CONCLUSIONS: Simple algorithms can identify Medicare claims for screening mammography with high predictive values in Medicare claims alone and in claims linked with cancer registry data.

Association of living alone and hospitalization among community-dwelling elders with and without dementia.

BACKGROUND: Older persons account for the majority of hospitalizations in the United States.1 Identifying risk factors for hospitalization among elders, especially potentially preventable hospitalization, may suggest opportunities to improve primary care. Certain factors-for example, living alone-may increase the risk for hospitalization, and their effect may be greater among persons with dementia and the old-old (aged 85+). OBJECTIVES: To determine the association of living alone and risk for hospitalization, and see if the observed effect is greater among persons with dementia or the old-old. DESIGN: Retrospective longitudinal cohort study. PARTICIPANTS: 2,636 participants in the Adult Changes in Thought (ACT) study, a longitudinal cohort study of dementia incidence. Participants were adults aged 65+ enrolled in an integrated health care system who completed biennial follow-up visits to assess for dementia and living situation. MAIN MEASURES: Hospitalization for all causes and for ambulatory care sensitive conditions (ACSCs) were identified using automated data. KEY RESULTS: At baseline, the mean age of participants was 75.5 years, 59 % were female and 36 % lived alone. Follow-up time averaged 8.4 years (SD 3.5), yielding 10,431 approximately 2-year periods for analysis. Living alone was positively associated with being aged 85+, female, and having lower reported social support and better physical function, and negatively associated with having dementia. In a regression model adjusted for age, sex, comorbidity burden, physical function and length of follow-up, living alone was not associated with all-cause (OR = 0.93; 95 % CI 0.84, 1.03) or ambulatory care sensitive condition (ACSC) hospitalization (OR = 0.88; 95 % CI 0.73, 1.07). Among participants aged 85+, living alone was associated with a lower risk for all-cause (OR = 0.76; 95 % CI 0.61, 0.94), but not ACSC hospitalization. Dementia did not modify any observed associations. CONCLUSION: Living alone in later life did not increase hospitalization risk, and in this population may be a marker of healthy aging in the old-old.

Association of incident dementia with hospitalizations.

CONTEXT: Dementia is associated with increased rates and often poorer outcomes of hospitalization, including worsening cognitive status. New evidence is needed to determine whether some admissions of persons with dementia might be potentially preventable. OBJECTIVE: To determine whether dementia onset is associated with higher rates of or different reasons for hospitalization, particularly for ambulatory care-sensitive conditions (ACSCs), for which proactive outpatient care might prevent the need for a hospital stay. DESIGN, SETTING, AND PARTICIPANTS: Retrospective analysis of hospitalizations among 3019 participants in Adult Changes in Thought (ACT), a longitudinal cohort study of adults aged 65 years or older enrolled in an integrated health care system. All participants had no dementia at baseline and those who had a dementia diagnosis during biennial screening contributed nondementia hospitalizations until diagnosis. Automated data were used to identify all hospitalizations of all participants from time of enrollment in ACT until death, disenrollment from the health plan, or end of follow-up, whichever came first. The study period spanned February 1, 1994, to December 31, 2007. MAIN OUTCOME MEASURES: Hospital admission rates for patients with and without dementia, for all causes, by type of admission, and for ACSCs. RESULTS: Four hundred ninety-four individuals eventually developed dementia and 427 (86%) of these persons were admitted at least once; 2525 remained free of dementia and 1478 (59%) of those were admitted at least once. The unadjusted all-cause admission rate in the dementia group was 419 admissions per 1000 person-years vs 200 admissions per 1000 person-years in the dementia-free group. After adjustment for age, sex, and other potential confounders, the ratio of admission rates for all-cause admissions was 1.41 (95% confidence interval [CI], 1.23-1.61; P < .001), while for ACSCs, the adjusted ratio of admission rates was 1.78 (95% CI, 1.38-2.31; P < .001). Adjusted admission rates classified by body system were significantly higher in the dementia group for most categories. Adjusted admission rates for all types of ACSCs, including bacterial pneumonia, congestive heart failure, dehydration, duodenal ulcer, and urinary tract infection, were significantly higher among those with dementia. CONCLUSION: Among our cohort aged 65 years or older, incident dementia was significantly associated with increased risk of hospitalization, including hospitalization for ACSCs.

Identification of abnormal screening mammogram interpretation using Medicare claims data.

OBJECTIVE: To develop and validate Medicare claims-based approaches for identifying abnormal screening mammography interpretation. DATA SOURCES: Mammography data and linked Medicare claims for 387,709 mammograms performed from 1999 to 2005 within the Breast Cancer Surveillance Consortium (BCSC). STUDY DESIGN: Split-sample validation of algorithms based on claims for breast imaging or biopsy following screening mammography. DATA EXTRACTION METHODS: Medicare claims and BCSC mammography data were pooled at a central Statistical Coordinating Center. PRINCIPAL FINDINGS: Presence of claims for subsequent imaging or biopsy had sensitivity of 74.9 percent (95 percent confidence interval [CI], 74.1-75.6) and specificity of 99.4 percent (95 percent CI, 99.4-99.5). A classification and regression tree improved sensitivity to 82.5 percent (95 percent CI, 81.9-83.2) but decreased specificity (96.6 percent, 95 percent CI, 96.6-96.8). CONCLUSIONS: Medicare claims may be a feasible data source for research or quality improvement efforts addressing high rates of abnormal screening mammography.

Upgrade of high-risk breast lesions detected on mammography in the Breast Cancer Surveillance Consortium.

BACKGROUND: Upgrade rates of high-risk breast lesions after screening mammography were examined. METHODS: The Breast Cancer Surveillance Consortium registry was used to identify all Breast Imaging Reporting and Data System category 4 assessments followed by needle biopsies with high-risk lesions. Follow-up was performed for all women. RESULTS: High-risk lesions were found in 957 needle biopsies, with excision documented in 53%. Most (n = 685) were atypical ductal hyperplasia (ADH), 173 were lobular neoplasia, and 99 were papillary lesions. Upgrade to cancer varied with type of lesion (18% in ADH, 10% in lobular neoplasia, and 2% in papillary lesions). In premenopausal women with ADH, upgrade was associated with family history. Cancers associated with ADH were mostly (82%) ductal carcinoma in situ, and those associated with lobular neoplasia were mostly (56%) invasive. During a further 2 years of follow-up, cancer was documented in 1% of women with follow-up surgery and in 3% with no surgery. CONCLUSIONS: Despite low rates of surgery, low rates of cancer were documented during follow-up. Benign papillary lesions diagnosed on Breast Imaging Reporting and Data System category 4 mammograms among asymptomatic women do not justify surgical excision.

External validation of Medicare claims codes for digital mammography and computer-aided detection.

BACKGROUND: While Medicare claims are a potential resource for clinical mammography research or quality monitoring, the validity of key data elements remains uncertain. Claims codes for digital mammography and computer-aided detection (CAD), for example, have not been validated against a credible external reference standard. METHODS: We matched Medicare mammography claims for women who received bilateral mammograms from 2003 to 2006 to corresponding mammography data from the Breast Cancer Surveillance Consortium (BCSC) registries in four U.S. states (N = 253,727 mammograms received by 120,709 women). We assessed the accuracy of the claims-based classifications of bilateral mammograms as either digital versus film and CAD versus non-CAD relative to a reference standard derived from BCSC data. RESULTS: Claims data correctly classified the large majority of film and digital mammograms (97.2% and 97.3%, respectively), yielding excellent agreement beyond chance (κ = 0.90). Claims data correctly classified the large majority of CAD mammograms (96.6%) but a lower percentage of non-CAD mammograms (86.7%). Agreement beyond chance remained high for CAD classification (κ = 0.83). From 2003 to 2006, the predictive values of claims-based digital and CAD classifications increased as the sample prevalences of each technology increased. CONCLUSION: Medicare claims data can accurately distinguish film and digital bilateral mammograms and mammograms conducted with and without CAD. IMPACT: The validity of Medicare claims data regarding film versus digital mammography and CAD suggests that these data elements can be useful in research and quality improvement.