Person:

Haas, Jennifer

Breast cancer screening holds a prominent place in public health, health care delivery, policy, and women's health care decisions. Several factors are driving shifts in how population-based breast cancer screening is approached, including advanced imaging technologies, health system performance measures, health care reform, concern for "overdiagnosis," and improved understanding of risk. Maximizing benefits while minimizing the harms of screening requires moving from a "1-size-fits-all" guideline paradigm to more personalized strategies. A refined conceptual model for breast cancer screening is needed to align women's risks and preferences with screening regimens. A conceptual model of personalized breast cancer screening is presented herein that emphasizes key domains and transitions throughout the screening process, as well as multilevel perspectives. The key domains of screening awareness, detection, diagnosis, and treatment and survivorship are conceptualized to function at the level of the patient, provider, facility, health care system, and population/policy arena. Personalized breast cancer screening can be assessed across these domains with both process and outcome measures. Identifying, evaluating, and monitoring process measures in screening is a focus of a National Cancer Institute initiative entitled PROSPR (Population-based Research Optimizing Screening through Personalized Regimens), which will provide generalizable evidence for a risk-based model of breast cancer screening, The model presented builds on prior breast cancer screening models and may serve to identify new measures to optimize benefits-to-harms tradeoffs in population-based screening, which is a timely goal in the era of health care reform.

The breast imaging modalities of mammography, ultrasound, and MRI are widely used for screening, diagnosis, treatment, and surveillance of breast cancer. Geographic access to breast imaging services in various modalities is not known at a national level overall or for population subgroups. METHODS: A retrospective study of 2004-2008 Medicare claims data was conducted to identify ZIP codes in which breast imaging occurred, and data were mapped. Estimated travel times were made for each modality for 215,798 census block groups in the contiguous United States. Using Census 2010 data, travel times were characterized by sociodemographic factors for 92,788,909 women aged ≥30 years, overall, and by subgroups of age, race/ethnicity, rurality, education, and median income. RESULTS: Overall, 85% of women had travel times of ≤20 minutes to nearest mammography or ultrasound services, and 70% had travel times of ≤20 minutes for MRI with little variation by age. Native American women had median travel times 2-3 times longer for all 3 modalities, compared to women of other racial/ethnic groups. For rural women, median travel times to breast imaging services were 4-8-fold longer than they were for urban women. Black and Asian women had the shortest median travel times to services for all 3 modalities. CONCLUSIONS: Travel times to mammography and ultrasound breast imaging facilities are short for most women, but for breast MRI, travel times are notably longer. Native American and rural women are disadvantaged in geographic access based on travel times to breast imaging services. This work informs potential interventions to reduce inequities in access and utilization.

RATIONALE AND OBJECTIVES: To determine the relationship between screening mammography facility characteristics and on-site availability of advanced breast imaging services required for supplemental screening and the diagnostic evaluation of abnormal screening findings. MATERIALS AND METHODS: We analyzed data from all active imaging facilities across six regional registries of the National Cancer Institute-funded Breast Cancer Surveillance Consortium offering screening mammography in calendar years 2011-2012 (n = 105). We used generalized estimating equations regression models to identify associations between facility characteristics (eg, academic affiliation, practice type) and availability of on-site advanced breast imaging (eg, ultrasound [US], magnetic resonance imaging [MRI]) and image-guided biopsy services. RESULTS: Breast MRI was not available at any nonradiology or breast imaging-only facilities. A combination of breast US, breast MRI, and imaging-guided breast biopsy services was available at 76.0% of multispecialty breast centers compared to 22.2% of full diagnostic radiology practices (P = .0047) and 75.0% of facilities with academic affiliations compared to 29.0% of those without academic affiliations (P = .04). Both supplemental screening breast US and screening breast MRI were available at 28.0% of multispecialty breast centers compared to 4.7% of full diagnostic radiology practices (P < .01) and 25.0% of academic facilities compared to 8.5% of nonacademic facilities (P = .02). CONCLUSIONS: Screening facility characteristics are strongly associated with the availability of on-site advanced breast imaging and image-guided biopsy service. Therefore, the type of imaging facility a woman attends for screening may have important implications on her timely access to supplemental screening and diagnostic breast imaging services.

Current shifts toward patient-centered healthcare and accountable payment options point to the more personalized production of better health, not just healthcare, as a next organizational paradigm. Transformation to a system geared toward promoting health requires us to think broadly about what it means to engage patients meaningfully, to give them a voice in their health and care, and to capture more of their varied experience and attitudes beyond the provider visit. The collection and use of patient-reported outcome data into electronic health records represents an important step forward for the transition to a more patient-centered health system. We set out an agenda for better understanding how and when patient-reported outcomes may improve patient health and care experience.