BREAST CANCER ONLINE TOOLKIT

Tools

This section contains ASTHO templates and report examples from both state teams and ASTHO consultants. State teams can use these examples to present data findings and GIS maps from breast cancer disparities research efforts to both internal and external partners. Arizona’s redesigned year one data report is one example of how to clearly communicate data findings with stakeholders. 

State Data Reports

Year One Data Reports

In summer 2016, each state compiled data reports that provide thorough summaries of data findings, GIS maps, and stakeholders involved during the first year of the ASTHO Breast Cancer Learning Community. These reports are designed to be a comprehensive overview of year one findings that are easy to compile from information and maps that state teams have readily on hand.

Supplemental Data Reports

After compiling these data reports, states were encouraged to make updates to the formatting, maps, and/or data analyses of these data reports to suit their needs in communicating learning community findings and goals with new and existing stakeholders.

Using Data to Reduce Disparities in Breast Cancer Mortality in Arizona – In fall 2016, Arizona adapted their year one data report into a fully designed and organized report that they are better able to share with external partners in both print and electronic format.

Tennessee Shelby County GIS Maps – As a result of their year one data report, Tennessee recognized that efforts to reduce breast cancer disparities should center on Memphis and the surrounding area in Shelby County, where large differences in breast cancer mortality were observed between black and white women. Tennessee built off their year one data report to conduct statistical analyses and generate GIS maps specific to Shelby County and identify areas of need in even greater detail.

State Summaries – Innovation Row

ASTHO developed a poster describing key findings, lessons learned, and next steps for each demonstration state after initial state data collection activities. ASTHO also developed one-pagers in collaboration with state health department teams that explore key findings, lessons learned, and next steps for each state in greater detail. These materials were presented to ASTHO State Health Official members and other ASTHO partners on September 21, 2016, at the Innovation Row exposition convened during the 2016 ASTHO Annual Meeting in Minneapolis.

State Snapshots

ASTHO Breast Cancer Learning Community state teams and ASTHO staff are currently working on a series of State Snapshot documents, which provide a 3-4 page in-depth overview of the breast cancer burden, action steps taken, stakeholders involved, and key successes. These snapshot documents are useful in updating stakeholders about project successes, and describing actions taken to-date to new stakeholders. State Snapshots will be available in August 2017.

Examples from the University of South Carolina

ASTHO consultants have been highly involved in this project since its onset, providing demonstration states with technical assistance and expert advice to improve epidemiologic capacity, increase expertise in GIS mapping, and translate data findings into sustainable and evidence-based action.

Breast Cancer Statistics: The State of Breast Cancer in South Carolina – This white paper that describes the breast cancer burden in South Carolina and serves as a case study on how information and action plans can be presented to non-subject matter experts.

Disparities in Breast Cancer Incidence, Mortality, and Quality of Care Among African American and European American Women in South Carolina – This journal article, which explores racial disparities in breast cancer across the care continuum, is an example of how different data sources can be synthesized to create a comprehensive analysis of breast cancer disparities that includes data analysis and GIS mapping. This higher level format is more appropriate for academics, healthcare partners, and public health professionals.

Resources

The resources in this section can be used to collect analyze state- and local-level breast cancer data along the full continuum of care from screening to quality treatment. This section can also be used to establish and test benchmarks for treatment quality. The Tennessee team utilized state cancer registry and BRFSS data to map race-stratified mortality data which helped them identify Shelby County (where Memphis is located) as an area of focus.   

In order to get a good understanding of breast cancer in your state as well as where disparities may exist, there are many resources which can assist you. Below is a listing along with links as available of available sources of breast cancer and breast cancer related data. Most of these are publically available and free, although some (noted in their description) may have a cost associated with them.

The Resources section is organized into the following subsections:

GIS Mapping Tools and Examples

Esri – Esri is a Geographic Information Systems (GIS) software and analytics company that that has worked with learning community states to better analyze and display breast cancer data through mapping:

  • What is GIS? – Learn what GIS is and how it works and explore a showcase of GIS success stories across different industries. Dive deeper into different industries including Government, Education and Health to learn more.
  • Living Atlas of the World – The Living Atlas is a comprehensive collection of global geographic information from Esri and its partners. It contains valuable maps, data layers, tools, services, and apps for geographic analysis. Organized by theme, this content strengthens the diverse and significant work of the GIS community at-large to address global and regional challenges. Relevant features include healthcare access application and the CDC Social Vulnerability Index data layer.
  • Bridging the Breast Cancer Divide – This two-hour step-by-step online course coaches users on how to use ArcGIS software to map breast cancer data and sociodemographic data to identify racial disparities in breast cancer mortality.
  • Getting Started – Start to learn ArcGIS with a free trial or explore a variety of training options, videos or the Esri Newsroom.

GIS and Public Health at CDC – There are a number of GIS resources available on the CDC website:

  • Chronic Disease GIS Exchange – CDC maintains this online forum of GIS resources, trainings, and maps for public health stakeholders of all levels of experience interested in using GIS in chronic disease prevention.
  • Online Public Health Maps This listing provides links to public health maps from CDC, other federal organizations, and other partners as well.
  • Geospatial Data Resources – This resources listing is organized into four topic areas: Public Health Resources, GIS Data, Social Determinants of Health Resources, and Environmental Health Data Resources. 
  • GIS Use in Public Health and Healthcare This external resource lists specific examples of interactive maps, atlases, and other tools developed by CDC covering a wide range of public health topics.

GIS and Spatial Health – This informational page from the University of North Carolina provides a brief overview of how GIS mapping and analysis can be used in public health, and describes a number of examples and case studies on the application of GIS in public health problem solving across North Carolina and other states.

Use of GIS Mapping as a Public Health Tool—From Cholera to Cancer – This journal article published by Musa et al. (2013) describes the applications of GIS in public health and health services, with in-depth discussions on the limitations and big data applications of GIS.

GIS & Mapping for Public Health: Mapping Websites & Applications – The University of California Berkeley page provides an exhaustive list of resources and GIS data websites relating to public health for the United States, California and other regions, and internationally.

Public Use Data Sets

CDC’s National Program of Cancer Registries (NPCR) Public Use Database – The NPCR public use database includes data on breast cancer incidence for 45 states, the District of Columbia and Puerto Rico providing information on 94.5% of the U.S. population. Datasets are available from 2001 onward (most current year available). The data are provided and analyzed using SEER*Stat software and requires users to complete a research data agreement.

United States Cancer Statistics (USCS) – Provides cancer incidence, mortality, and MIR data by year, state, metropolitan area, race, ethnicity, gender, and cancer site. Some data is restricted and requires a data request to be completed. More information is available on this USCS one-pager.

State Cancer Profiles – Provide state- and county-level cancer incidence, prevalence, and mortality rates for various cancer types (map or table format); mammography use in the past two years is also presented based on 2014 BRFSS data (state-level only).

NCI Small Area Estimates for Cancer-Related Measures – Mammography use with the past two years for women aged 40+ is presented at the county and HSA level based on BRFSS and NHIS data from 1997-1999 and 2000-2003 (more recent estimates, based on 2008-2010 BRFSS and NHIS data, are available in the NCI State Cancer Profiles website for mammography use in the past 2 years)

Health Information National Trends Surveys (HINTS)HINTS is an annual, nationally representative survey of American’s use of cancer-related information. The survey has been used to explore trends in mammography decision making and screening adherence, health information seeking, and cancer risk perception. Data is available at the state and national level.

National Health Interview Survey (NHIS)The National Health Interview Survey can be used to assess breast cancer screening utilization, and other health care seeking patterns and lifestyle choices among breast cancer survivors. The data is only available at the national level.

Behavioral Risk Factor Surveillance SurveyA telephone survey administered at the state level, this dataset has breast cancer screening specific questions including mammography use (ever and within the last year). Data can be combined to produce national estimates. County-level data can typically be obtained from each state’s department of health.

Medicare Current Beneficiary Survey (MCBS) – The MCBS can be used to examine mammogram screening (and reasons for not receiving mammography) among Medicare beneficiaries, and can examine other health care seeking behaviors (and its associated costs) among breast cancer survivors.

Medicare Expenditure Panel Survey (MEPS)MEPS can be used to examine breast cancer survivors’ health care seeking patterns, comorbidities, behaviors (e.g., smoking), and treatment costs. Data can also be used to describe variations in breast cancer screening and treatment related expenditures.

Uniform Data System (UDS) – All Federally Qualified Health Centers (FQHCs) across the nation report information to the Uniform Data System (UDS) maintained by the Health Resources and Services Administration. In addition to basic demographic and medical information of populations served by FQHCs, there are also several data elements specific to breast cancer screening including numbers of centers offering mammography services and numbers of mammograms performed. Additionally, many FQHCs engage in data share agreements for research and quality improvement purposes. Thus, it may be useful to contact FQHC administrators within your state to determine availability of this type of data. 

Healthy People 2020 – Healthy People 2020 sets goals and priorities as it relates to health outcomes and risk factors related to health outcomes. Its overall mission is to “attain high-quality, longer lives free of preventable disease, disability, injury, and premature death.” There are several indices related to breast cancer including breast cancer mortality and diagnosis of breast cancer at earlier stages. State-level data is available through their online data (DATA2020) tool. 

500 Cities ProjectThe 500 Cities project is a collaboration between CDC, the Robert Wood Johnson Foundation, and the CDC Foundation. The purpose of the 500 Cities Project is to provide city- and census tract-level small area estimates for chronic disease risk factors, health outcomes, and clinical preventive service use for the largest 500 cities in the United States. These small area estimates allow cities and local health departments to better understand the burden and geographic distribution of health-related variables in their jurisdictions, and assist them in planning public health interventions.

Chronic Disease Indicators – This set of chronic disease prevalence indicators, which include breast cancer mortality and mammography rates in women aged 50-74, can be searched by state and utilized to generate comparison reports. This tool was developed by CDC in partnership with the Council of State and Territorial Epidemiologists (CSTE), and the National Association of Chronic Disease Directors (NACDD).

Small Area Health Insurance Estimates (SAHIE) – This U.S. Census Bureau tool produces statistically modelled estimates of health insurance coverage rates for all U.S. counties and states. This data can be stratified by income level and other demographic indicators such as sex and race/ethnicity.

Proprietary/Limited Use Data Sets

These resources may not be accessible by all visitors. Additionally there may be costs associated with the use of these resources. 

CDC's National Breast and Cervical Cancer Early Detection Program – The National Breast and Cervical Cancer Early Detection Program provides free breast cancer screening and mammography follow-up to low-income, uninsured, and underserved women. Data is collected on all mammograms performed on participants in the program including screening mammography, diagnostic services, and breast cancer diagnoses.  National and state estimates are available at this website. Typically, state health departments, as recipients of the national grantee program, have individual and county level data.

Center of Medicaid Services (CMS) Data Navigator – Medicare and Medicaid are federally-administered health insurance plans provided to all Americans age 65 and up (Medicare) or income eligible individuals (Medicaid). Medicare administrative data is available at significant cost from CMS. Medicaid, which is administered at a state-level, can often be obtained at lower cost from state-based organizations (usually the Department of Health and Human Services). CMS provides an online data tool which allows the user to query Medicare and Medicaid sources without actually providing individual-level data. Billable services such as mammography, diagnostic services, and treatment services could be queried in the dataset.

State Employee Health Plan – Many states offer a unified health insurance plan to all state workers which would include all public schools, state government offices, and public academic institutions. Similar to Medicare and Medicaid, administrative data utilized from these type of sources could be used to examine mammography, diagnostic services, and treatment services provided.

National Cancer Database (NCDB) (NCDB) The National Cancer Database includes cancer registry data from COC-accredited facilities in the U.S. The database includes more than 70% of all newly diagnosed cancer cases in the U.S. COC-accredited facilities can use the online tools available from the NCDB to analyze their own institutional data and compare their program against benchmarks for similar programs in the region, state, or nationwide. Applications are accepted for HIPAA-compliant participant user files by researchers not affiliated with a COC-accredited program during a limited time period each year. Per NCBD requirements, patients and facilities are de-identified.

Breast Cancer Surveillance Consortium (BCSM)The Breast Cancer Surveillance Consortium includes six active (and two inactive) mammography registry sites across the U.S. The BCSM is not currently accepting data request proposals, but may in the future.

Truven Health MarketScan Research Databases This all-payer clinical database includes over 230 million de-identified patients and can be used to examine inpatient and outpatient treatment patterns, lab results, dental care, primary care usage, and more.

Healthcare Cost and Utilization Project (HCUP) – The Healthcare Cost and Utilization Project is a group of healthcare databases and online query tools developed and maintained by the Agency for Healthcare Research and Quality (AHRQ). The databases contain inpatient, outpatient, and emergency department discharge records across all payer types (data availability varies by state and year). The online query tool can also provide statistics on inpatient, outpatient, or emergency department services related to breast cancer at the county level.

Surveillance, Epidemiology and End Results (SEER)-Medicare Linked Database – The SEER-Medicare linked databases link cancer registry data from the Surveillance, Epidemiology and End Results (SEER) program with claims data for Medicare beneficiaries in the U.S. The data can be used to conduct a variety of epidemiologic, economic, and health services research projects for breast cancer related outcomes. 

State Cancer Registries – States collect demographic and clinical data for all diagnosed cancer cases residing in each state. Requests for individual-level data are typically required to go through IRB review and a formal data request from the data owner (costs may apply). Aggregate statistics for the state and/or counties may not require an extensive application or IRB review. For a list of available variables, please see the most recent North American Association of Central Cancer Registries (NAACCR) data dictionary.

Quality Improvement Programs and Accountability Measures

Commission on Cancer (CoC) of the American College of Surgeons (ACOS) – The CoC is a nationally-recognized accreditation program offered through ACOS. To apply for CoC accreditation, explore the tools and resources offered on the ACOS website. See Knutson et al. (2014), Kneisl and Jackson (2011), and Bilimoria et al. (2009) for more information on the impacts that CoC accreditation has on cancer outcomes.

FDA Mammography Quality Standards Act & Program (MQSA) – U.S. mammography clinics must be accredited and certified annually by the FDA (or FDA-approved agency). National standards are described in detail on the FDA MQSA website.

National Cancer Institute (NCI) Designation – NCI-designated cancer centers and comprehensive cancer centers are awarded designation based on achievement in transdisciplinary basic science, clinical and population-based cancer research. NCI offers major funding to NCI-designated cancer center programs to assist with faculty recruitment, administrative support, core services (e.g., biostatistical support, lab processing, etc.), clinical trials, and research innovation. See Merkow et al. (2014) for more information on the impacts of NCI designation.

American College of Radiology (ACR) ACR maintains accreditation requirements and processes for a number of breast cancer diagnostic and treatment procedures, including mammography, breast ultrasound, and stereotactic breast biopsy.

National Quality Forum – The National Quality Forum is a useful not-for-profit and independent foundation that works to set national standards for care for the purposes of quality assessment and control. There are several metrics related to breast cancer screening and treatment which can be accessed. In particular, the ‘NQF Work’ link on their website allows you to search for breast cancer specific quality measures.

National Consortium of Breast Centers (NCBC) – The National Consortium of Breast Centers has program to help centers collect and report on a variety of national quality measures such as: 1) time between screening mammogram and diagnostic mammogram, 2) time between diagnostic mammogram and needle/core biopsy, and 3) time between needle biopsy and initial breast cancer surgery. The program costs $600 annually, and allows centers to see comparisons to other NQMBC programs’ quality scores. They also have a program to certify patient navigators

National Accreditation Program for Breast Centers (NAPBC) – The National Accreditation Program for Breast Cancers, administered by the American College of Surgeons, sets quality assurance and improvement standards for U.S. breast centers and maintains the National Breast Disease Database. Breast centers can apply for accreditation ($2,500/annually) and learn more at the NAPBC website. See Winchester (2011) and Winchester (2016) for additional information on NAPBC accreditation and its impact on cancer care.

Patterns of Care/Quality of Care Studies – The National Cancer Institute (NCI) is congressionally mandated to study quality of cancer care in the U.S. Using POC data, hundreds of studies have been published describing variations in guideline-concordant cancer treatment, dissemination of evidence-based strategies into community practice, and determinants of treatment quality. A search tool on NCI’s website allows you to identify relevant articles to breast cancer treatment.

Healthcare Effectiveness Data and Information Set (HEDIS) – HEDIS is an annually updated set of healthcare performance measures – including breast cancer screening for Medicare, Medicaid, and private providers – that collects data from a wide variety of healthcare providers. This tool is used extensively by health plans to measure healthcare performance.

Recommendations for Translating Data to Action

This section can help states translate data findings into the implementation of evidence-based initiatives to reduce breast cancer disparities. For example, the West Virginia team has partnered with researchers at the Charleston Area Medical Center to start a Project ECHO telementoring program with rural physicians to improve primary care for breast cancer survivors in areas with poor healthcare access.  

Evidence-Based Interventions

There are several resources for evidenced-based interventions which could be used to address disparities found upon your data analysis and needs assessment. An important principle for your decision-making process is ensuring that the approach which you want to use has proven to be effective in the scientific literature. The Cancer Control PLANET from the National Cancer Institute is an excellent resource which can help with the planning and implementation of evidence-based programs. Below are several resources which provide useful descriptions of cancer-related interventions:

Community Guide (HHS) – The Community Preventive Services Task Force releases evidence-based recommendations on public interventions that reduce disease burdens and improve wellbeing. These recommendations are referred to as the Community Guide. This page contains evidence-based recommendations specific to cancer prevention and control, including recommendations on breast cancer.

 

Research-tested Intervention Programs (NCI) – NCI’s research-tested intervention programs (RTIPs) list contains a database of 180 searchable evidence-based cancer interventions, which can be indexed based on cancer site (including breast cancer), by sociodemographic group, and other factors as well.

Breast Cancer Learning Community Change Package – This evidence-based change package, informed by the journal literature and the action plan proposals of ASTHO learning community states, systematically lists different strategies that can be implemented based on a state’s identified disparities. Strategies are organized into two categories along the cancer care continuum – follow-up between diagnosis and treatment, and treatment quality.

Increasing Population-based Breast and Cervical Cancer Screenings (CDC) – This comprehensive action guide was developed to assist Comprehensive Cancer Control (CCC) grantees implement and expand efforts that increase population-based cancer screening through the adoption of evidence-based strategies and collaboration with key partners. 

Comprehensive Cancer Control Branch Program Evaluation Toolkit (CDC) – This toolkit is designed to help CCC grantees plan and implement evaluations of their grant-funded cancer control programs.

Training and Education Resources (GW Cancer Center) – GW Cancer Center offers a wide variety of relevant resources and trainings for healthcare professionals, including a patient navigation roadmap, a comprehensive patient navigation toolkit, and an e-learning series on survivorship care. 

Patient Values Initiative (CancerCare) – Reports on patient decisionmaking and oncologist decisionmaking at the point of care provide insights on integrating patient treatment choices as part of evidence-based cancer care.

Plan, Do, Study, Act Cycle Strategy

Applying evidence-based interventions to real-world settings can occur using a quality improvement approach. Quality improvement models such as the Institute for Healthcare Improvement’s Breakthrough Series are designed to guide teams of stakeholders through a process to identify and test evidence-based strategies and determine the best approaches to bring to scale. While this QI model was developed for health care settings, ASTHO has adapted it to apply to statewide systems that support better coordination and integration between public health, health care, and community-based services and resources. The following outlines the steps in ASTHO’s approach.

Step 1: Develop an Aim Statement.

An Aim Statement defines the team’s collective vision and goals, and answers the question “What are we trying to accomplish?” The Aim Statement should be as specific as possible, and include the following information:

  • What are we trying to improve?
  • By when will we improve it?
  • By how much will it improve?
  • For whom will it improve?
  • What are the likely key strategies we will use to achieve our goal/purpose?

Step 2: Identify strategies to test to achieve Aim.

After defining the Aim Statement, teams should identify evidence-based strategies they wish to test to achieve the Aim. Many resources to help identify appropriate evidence-based strategies exist—see the Tools section of this toolkit. The strategies should include roles for each stakeholder, and should be identified considering the resources and assets available, such as data to inform decision making and identify individuals in the target population.

Step 3: Develop and implement rapid tests of change.

The Plan-Do-Study-Act (PDSA) Cycle, developed by the Deming Institute, guides teams through a continuous series of steps to conduct small, rapid “tests of change” that inform continuous improvement of a process or initiative. Within the context of breast cancer screening, follow-up, and treatment quality, PDSA cycles can help teams quickly identify the best protocols for helping patients quickly gain access to care after a breast cancer diagnosis, establish optimal data-sharing systems between public health and clinical providers, and standardize the treatment guidelines physicians use for their patients. Good PDSA cycles are specific, coordinated, rapid, and adapt and grow over time to impact more and more patients with each cycle. Teams can plan an initial PDSA cycle by asking the following questions:

  1. What system change or strategy are we testing?
  2. How big is our test (how many people will we test)?
  3. When will the test of change take place?

Once the plan has been developed, teams should determine how they will measure the outcomes of their test by asking the following questions:

  1. What indicator(s) can we use to measure the outcomes of this activity?
  2. What kind of data will we collect? Who will collect it? Who will analyze it?
  3. How will we know if we have succeeded in progressing toward our aim statement using the selected activity(ies)? What will be the short/medium-term results of this activity?

Teams then implement and measure the outcomes of their test. After the test has been implemented, they should study the results of the test by analyzing the data they collected and asking what worked and what didn’t work. Based on the findings of this process, teams may choose one of three options for advancing to a second test:

  1. Adopt the first test unchanged and expand it to more individuals;
  2. Adapt the test and try it again on a small group of individuals;
  3. Abandon the test completely and try something new.

ASTHO has extensive experience guiding cross-sector statewide teams through this quality improvement process. States interested in learning more can contact Josh Berry at ASTHO.

Success Stories

ASTHO Breast Cancer Learning Community state teams and ASTHO staff are currently working on a series of State Snapshot documents, which provide a 3-4 page in-depth overview of the breast cancer burden, action steps taken, stakeholders involved, and key successes. These snapshot documents are useful in updating stakeholders about project successes, and describing actions taken to-date to new stakeholders. State Snapshots will be available in August 2017.

If you have a success story to share about using evidence-based methods, GIS mapping, or other information in this online toolkit to identify and/or reduce breast cancer disparities, ASTHO wants to hear about it. Please reach to Josh Berry with any successes so that your work can be highlighted on this online toolkit and through other ASTHO communications as a state success story.

Needs Assessment

This section can help state health agencies build a coalition to identify and address breast cancer disparities. The resources provided in this section can assist teams in performing their own needs assessment, and bringing the right stakeholders on board. 

 Community Needs and Assets Assessment

States and communities have a range of opportunities to assess and identify priority health topics to guide resource allocation decisions and monitor change over time. One opportunity is leveraging the community health needs assessment (CHNA) process, which is required for tax-exempt hospitals to conduct under the Affordable Care Act at least once every three years. ASTHO’s Community Health Needs Assessment webpage provides more information and guidance around CHNAs, includes case studies of how state health agencies are successfully supporting implementation of CHNAs, and links to additional resources.

Capture_Needs Assessment

States and communities have a range of opportunities to assess and identify priority health topics to guide resource allocation decisions and monitor change over time. One opportunity is leveraging the community health needs assessment (CHNA) process, which is required for tax-exempt hospitals to conduct under the Affordable Care Act at least once every three years. ASTHO’s Community Health Needs Assessment webpage provides more information and guidance around CHNAs, includes case studies of how state health agencies are successfully supporting implementation of CHNAs, and links to additional resources.

In the context of breast cancer screening and outcomes, states can conduct assessments of existing statewide systems that support breast cancer screening, follow up, and treatment. ASTHO has developed a needs assessment process for state health agencies to survey stakeholder perceptions of capacity and opportunities to strengthen systems related to data, infrastructure, partnerships, communication, and evidence-based practice. States interested in learning more about this process can contact ASTHO.

Additional CHNA examples and resources can be found on the Susan G. Komen Community Profile Reports webpage.

Stakeholder Identification

The most effective initiatives engage a broad range of stakeholders at the state, local, and community levels. A truly broad stakeholder group should include representation from a wide range of sectors, including public health, health care, health care financing, health information technology (health IT), and quality improvement.

Key stakeholders to consider including fall into a number of different categories:

  • State policy makers and leaders
  • State health agency
  • State Medicaid agency and Medicaid managed care plans (MCOs)
  • Private health plans and health insurance companies
  • Accountable care organizations (ACOs)
  • Health systems, hospitals, primary care physicians, and specialists
  • Community health center networks
  • State physician associations
  • State quality improvement organizations
  • Regional or state health information exchanges, health center controlled networks, and other health IT partners
  • Advocacy organizations (for example, Susan G. Komen Foundation state affiliates)
  • Local health departments
  • Federally Qualified Health Centers (FQHCs), community health clinics, and cancer clinics
  • Individual physicians and other non-physician cancer providers
  • Social service providers
  • Community health workers
  • Patient navigators, care coordinators, and case managers
  • Public health nurses
  • Community-based organizations
  • Comprehensive cancer control plans
  • State GIS clearing house
  • Academic institutions and researchers
  • Religious institutions and leaders

Additional recommendations can be found in CDC’s list of potential partners for comprehensive cancer control coalitions.


Approaches to Measuring Breast Cancer Disparities

This literature review explores questions that learning community states have researched to help identify breast cancer disparities through data analysis. This information can help states identify sociodemographic populations and geographic areas of focus.

 

There is much research published in the peer-reviewed literature that contributes to our understanding of why racial/ethnic and socioeconomic disparities in breast cancer screening and outcomes exist. This literature can help states formulate research questions and data analysis approaches to better understand breast cancer disparities in one’s area. This toolkit section is organized as a literature review that explores different questions that learning community states have found useful in doing their own research and data analyses. A reference list is also included.

To what extent do geographic disparities exist in breast cancer screening?

Although mammography rates have become more or less equal among black and white women, screening rates vary greatly by geographic location.1 Consistently, low adherence to mammography screening guidelines were observed in areas of New Mexico, Wyoming, Mississippi, Oklahoma, and Indiana. However, increases in adherence were observed in southern Appalachia including northern Alabama and Georgia.2 One study identified an increased need for screening adherence and access in the southern Black Belt region (Virginia, North Carolina, South Carolina, Georgia, Florida, Alabama, Mississippi, Louisiana, Texas, Arkansas, and Tennessee).3

Mammography use varied geographically, and the magnitude of geographic disparities differed by race and age. Additionally, findings showed variation between states on county level screening rates.4 The majority of states exhibit the standard disparities reported national statistics, whereas others show no disparities at all and some studies even find reverse disparities in states such as Michigan and New Jersey.5 Nonwhite women showed the lowest levels of screening compared with all other groups. Women aged 40 to 49 also had lower screening rates when compared with other age groups.4

What populations underutilize breast cancer screening?

Although screening rates have been increasing, racial/ethnic minorities in the United States are underutilizing preventive health services.6 Racial/ethnic minorities and those with low socioeconomic status report low screening rates, with the lowest mammogram rates reported among uninsured women.6, 7 Underutilization of breast cancer screening services is an ongoing issue, particularly for African American women. Compared to non-Hispanic white women, black women are less likely to be screened for breast cancer. 8 In addition, a recent study found that 34 percent of African American women received insufficient breast cancer screening prior to their diagnosis.9

Hispanic women screen less frequently than black and white women.10 The most significant barriers reported by previous studies include language barriers, not having a usual source of care, and lack of health insurance.10 These racial disparities in mammogram utilization prominently exist among women aged 40 to 65 years old, and women aged 65 and older.10

To what extent do geographic disparities exist in breast cancer treatment?

One study in Georgia found that patients who live in small rural areas have increased chances of receiving surgery and decreased chance of receiving radiotherapy as well as decreased mortality risk.11 Furthermore, geographic variation of treatment has a significant impact on treatment type, treatment intensity and cost of care.12, 13

There is also geographic variation in the magnitude of racial disparities in breast cancer treatment across the United States.13 For instance, black patients in areas of the northeastern and southern United States show the lowest rates of radiation therapy.14 Poor spatial accessibility to health care services, especially for women who rely on public transportation, prevent optimal treatment for women with breast cancer.15

What populations receive less than optimal breast cancer treatment?

Generally, minority populations receive poorer quality breast cancer treatment than white women. Racial disparities in breast cancer treatment were evident in several studies despite adjusting for insurance and socioeconomic status.16 There are clear racial differences between treatment and outcomes. African American women diagnosed with breast cancer have overall lower incidences than white women, but experience higher mortality rates, possibly due to a delay in diagnosis and treatment which can negatively impact patient outcomes.17 Multiple studies found that black and Hispanic women fail to receive definitive local therapy, chemotherapy and radiotherapy for curable breast cancers as often as White women.18, 19, 20, 21 Additionally, studies show mixed results for whether black women are more likely to receive mastectomies compared to white women.22, 23, 24 Conversely, one study in Alabama found that there was no difference in quality of care received by Medicare beneficiaries based on race, but a significant difference was observed based on socioeconomic status.25  

The literature has shown mixed results regarding the relationship between timely breast cancer treatment and survival.26, 27, 28, 29, 30, 31 Risk factors for treatment delay include older age, the nature of the breast symptom, patients’ negative attitudes towards their general practitioner, and fears about cancer treatment.32 African American women experience more diagnosis and treatment delays when compared to women of other racial/ethnic subgroups.33,34,35,36,37 Relative to white women, black women are four to five times more likely to experience treatment delays longer than 60 days, and are significantly less likely to receive cancer-directed surgery, radiation therapy after lumpectomy, and hormonal therapy for hormone receptor-positive tumors, after controlling for tumor characteristics.18 Madubata and colleagues (2016) found that black women had higher odds of radiation delay than their white counterparts.23

What is the association between primary care provider availability and breast cancer screening or late-stage diagnosis rates?

There is a strong association between primary care provider availability and breast cancer screening and late stage diagnosis rates. 38 One study in Illinois found an inverse relationship between access to primary care and late stage diagnosis risk.39 Data suggests that with increasing visits to the physician, breast cancer outcomes are improved and late-stage diagnoses are reduced.38 Additionally, research has indicated that poorer geographic access to primary care is linked to late diagnosis.7 Accessible and available primary medical care is an important factor in achieving better outcomes for patients with a diagnosis of breast cancer.

Does geographic access to mammography affect breast cancer screening or late-stage diagnosis rates?

A systematic review found mixed results for the relationship between geographic access to mammography and breast cancer screening utilization.40 When examining the impact of mammography capacity on screening uptake, one study compared seven states and determined that women in counties with inadequate capacity were more likely to have longer wait times for screening and were less likely to have a mammogram.41, 42 One study analyzed the effect of density often found a positive correlation between percent of women screened and the number of mammography facilities per 10,000 women at the state level.43

Cancer stage at diagnosis has a substantial impact on treatment received, recovery, and survival. In a cross-sectional retrospective study examining the impact of spatial access to healthcare services on late detection of female breast cancer diagnosis in Missouri, it was revealed that geographical differences exist between metro and suburban/rural areas in terms of access, distance traveled to the nearest healthcare facility, and stage at breast cancer diagnosis. The findings from this study support the hypothesis that women living in areas with limited access to mammography facilities are more likely to be diagnosed with late-stage breast cancer.44 Similarly, a study which took place in metropolitan Detroit suggests that living in areas with poorer mammography access can significantly increase the risk of late diagnosis of breast cancer.7 In contrast, Henry et al. (2013) did not find a significant relationship between late stage diagnosis of breast cancer and geographic access to mammography in a large 10-state study. Additionally, one study done in Mississippi, there was no significance between breast cancer outcomes and the availability or access to mammography facilities.45

The majority of analyses using distance and travel time measures found no statistically significant results between geographic access and mammography use or late-stage at diagnosis, whereas the majority of results from capacity and density found statistically significant associations.40 Distance and travel time alone may not be sufficient measures of geographic access to care. Having more standardized and granular representations of geographic access to care will improve the ability to make valid inferences about these relationships.40, 46

Does geographic access to breast cancer treatment (surgery, radiation therapy or chemotherapy) affect adherence to breast cancer treatment or quality of care received?

While travel time to screening mammography has been broadly characterized, distance or travel time to breast cancer treatment has been less well studied. In a study investigating the association between the influence of travel time to the nearest radiology facility and breast cancer treatment found that travel time appears to influence the type of primary therapy received among women with breast cancer in that women with travel times greater than 30 minutes were more likely to have a mastectomy compared to women with travel times less than 10 minutes.47 These findings suggest that without adequate access to radiology facilities, women are likely to prefer services such as mastectomies, which would be considered low frequency services.47

A cohort study examining the relationship between distance and breast cancer treatment received found a significant decrease in the likelihood of undergoing breast-conserving surgery among women living greater than 15 miles from a hospital with radiotherapy facilities.48 Among women who underwent breast-conserving surgery, a lower probability of undergoing radiotherapy was observed specifically to those who live greater than 40 miles from a hospital with radiotherapy facilities.48   Because radiotherapy is recommended for women who undergo breast-conserving study as primary therapy, Nattinger et al. (2001) cited the lower use of radiotherapy among breast-conserving surgery patients living greater than 40 miles from a hospital with a radiotherapy facility as a cause for concern in the issue of appropriateness of care. Additionally, patients who live far from a reference care center are less likely to be referred to specialized surgeons that may practice farther away, and receive less assistance with overall disease management.49 Due to limitations in studies performed, such as the potential accuracy and wide variability in measures, it is difficult to draw conclusions regarding the effect of geographic access to treatment on quality of care.40

 

References

    1.   Steil et al., 2016  

    2.   Feng et al., 2016  

    3.   Coughlin et al., 2002  

    4.   Schneider et al., 2009  

    5.   Mobley et al., 2012

    6.   Peek and Han, 2004

    7.   Dai, 2010

    8.   Henry et al., 2013

    9.   Smith-Bindman et al., 2006

    10.   Ahmed et al., 2016

    11.   Markossian et al., 2014

    12.   Eberth, 2014

    13.   Feinstein et al., 2013

    14.   Smith et al., 2010

    15.   Pepins, 2013

    16.   Freedman, 2010

    17.   DeSantis et. al, 2013

    18.   Carey et al., 2013

    19.   Sail et al., 2012

    20.   Dookeran et al., 2015

    21.   Freedman et al., 2012

    22.   Akinyemiju, 2015  

    23.   Mudubata et al., 2016

    24.   Grimmer, 2015

    25.   White et al, 2014

    26.   Webber et al., 2014

    27.   Nurgalieva et al., 2013

    28.   Smith et al, 2013

    29.   Eastman et al., 2013

    30.   Sanchez et al., 2007

    31.   Lohrisch et al., 2006

    32.   Bish et. al 2004

    33.   Gorin et al., 2006

    34.   Sheppard et al., 2015

    35.   George et al., 2015

    36.   Williams et al., 2010

    37.   Bustami, 2014

    38.   Roetzheim et al., 2012

    39.   Wang et al., 2006

    40.   Khan-Gates et al., 2016

    41.   Elkin et al. 2012

    42.   Elkin et al. 2010

    43.   Marchick and Henson, 2005

    44.   Williams et al. 2015

    45.   Nichols et al., 2014

    46.   Lian et al., 2012

    47.   Onega et al. 2011

    48.   Nattinger et al. 2001

    49.   Gentil et al., 2012

About the ASTHO Breast Cancer Learning Community

About this Online Toolkit

The purpose of the ASTHO Breast Cancer Online Toolkit is to provide resources on identifying, measuring, and addressing breast cancer disparities, and to detail lessons learned from ASTHO’s Breast Cancer Learning Community. The information in this toolkit is designed to provide state and local health departments, as well as other breast cancer stakeholders such as cancer registries, healthcare providers, and healthcare payers, with a comprehensive roadmap on how to work towards health equity by reducing disparities in breast cancer mortality.

The toolkit is organized into the following sections:

  • About: This page describes the purpose of the ASTHO Breast Cancer Learning Community and this toolkit.
  • Needs Assessment: This page provides information on community needs and assets assessments.
  • Resources: This page provides a list of resources regarding breast cancer disparities data. Most of these resources are publically available
  • Approaches to Measuring Breast Cancer Disparities: This section is presented in the form of a literature review and combines data from several research articles concerning geographic disparities associated with breast cancer.
  • Recommendations for Translating Data to Action: This page provides guidance for evidence-based interventions, success stories and application to real world scenarios
  • Tools: ASTHO templates and state data report examples are available in this section.

 Learning Community Background

Black women in the U.S. are approximately 40% more likely to die of breast cancer than white women. ASTHO received funding from the CDC in fall of 2015 to form a learning community with state health department teams from Arizona, Tennessee, and West Virginia to improve epidemiologic capacity to identify breast cancer disparities, and position states to take data-driven action with the input of key stakeholders. The purpose of the ASTHO Breast Cancer Learning Community is to strengthen the ability of state public health departments to mobilize data resources more effectively to address disparities in breast cancer mortality.

State Map 

In the first year of this learning community, ASTHO convened a series of in-person and virtual meetings with national experts and a variety of state stakeholders to obtain and analyze state-specific data using GIS mapping techniques. National experts involved in this project include CDC researchers from the Division of Cancer Prevention and Control, representatives from hospital systems, research institutions, and national foundations, and state-level breast cancer stakeholders include healthcare providers, community groups, and public and private healthcare payers. States focused their data analysis and mapping efforts in three CDC-recommended cancer continuum areas: screening, follow up after abnormal screening result, and treatment quality. At the conclusion of the first year of this project, states presented data reports before a national partner audience resulting in customized feedback on data analysis and expanded intervention considerations.

In the second year of this learning community, states are continuing collaboration with the above national experts and state-level stakeholders through in-person and virtual meetings to not only analyze additional data, but to draft and execute action plans that translate data findings and stakeholder recommendations into interventions that reduce sociodemographic disparities in breast cancer screening, follow up after abnormal screening result, and treatment quality. States are also working to create, refine, and enhance collaboration between health systems, public health payers, and community partners to create a “systems of care” network spanning clinical, community, and public health settings that identify individuals with breast cancer.

Requests for additional information on the ASTHO Breast Cancer Learning Community can be sent to Josh Berry.

Partnerships

CDC – The Breast Cancer Disparities Learning Community is made possible by the funding and support of the CDC Division for Cancer Prevention and Control (DCPC). DCPC staff have been involved in every facet of the learning community, providing ASTHO and demonstration states alike with research, expert advice, and technical assistance during in-person and virtual convenings of the learning community to ensure that demonstration states and their stakeholders utilize the most up to date research, analytic approaches, and interventions in their work.

   

ESRI – ESRI has been a key partner whose work has ensured that states have the software and technical knowledge needed to identify disparities geographically by translating data into maps that facilitate data-driven decision making. ESRI has helped ensure that all demonstration states have up to date GIS software licenses, and have regularly provided states with technical assistance on GIS and epidemiologic analysis, such as through their Bridging the Breast Cancer Divide online course.

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