BREAST CANCER DISPARITIES ONLINE TOOLKIT

Burden of the Problem

Introduction

According to the 2012 Vital Signs Report, breast cancer death rates have been declining among U.S. women since 1990 because of early detection and advances in treatment; however, all racial groups have not benefited equally.

Vital Signs Image

Listen to the CDC Vital Signs – Defeating Breast Cancer Podcast.

This podcast is based on the November 2012 CDC Vital Signs report. Breast cancer is the second leading cause of cancer deaths among women in the United States. Better screening and treatment have contributed to a decline in breast cancer deaths; however, not all women have benefited equally from these improvements. Learn how we can all help reduce deaths from breast cancer.

CDC National Program of Cancer Registries Participating States

Forty-six states, the District of Columbia, Puerto Rico, the U.S. Pacific Island Jurisdictions, and the U.S. Virgin Islands receive funding through CDC’s National Program of Cancer Registries. Visit the National Program of Cancer Registries to find your local registry.

Your state cancer registry is a collection of detailed information about cancer diagnosis and treatments. The cancer registry is also an excellent data source to determine if the interventions implemented achieved the intended solution, so it is best to revisit the cancer registry regularly.

States should first outline questions that data can help them answer. Below are some examples to help determine what kind of search to perform:

  • Are screening rates different by zip code and/or age group?
  • Are there differences across the state for women diagnosed with breast cancer at a late stage?
  • Are more or fewer people getting breast cancer this year compared to last year?
  • What groups are most likely to be diagnosed with breast cancer by insurance type?

Consider these other questions to consider as you begin defining the burden of the problem and understanding present disparities.

State cancer registries are critical to:

  • addressing and understanding burden
  • addressing and understanding risk
  • targeting program focus
  • identifying disparate groups/high risk
  • investigating causes and excess cases

Stories can provide a comprehensive perspective. With Geographic Information Systems (GIS) Mapping, this mechanism adds to the story by providing an illustration of the distribution of services and travel times, etc., to tell the story through data how we’ve arrived at the challenges.

Bridging the Breast Cancer Divide Online Course Cover Image

View the Bridging the Breast Cancer Divide Online Course »

During year 1 of the ASTHO Breast Cancer Learning Community, each participating state focused on describing the burden of its problem by analyzing its local data. Through this process, states had a better lens for decision-making ahead of outlining its implementation strategies. It is important to use data to tell a story – paint of picture of the burden, availability of services, distance to services, etc. and overlay that information so that you can identify your "hotspots," or areas with the most need. Below are examples from each of the six participating states:

 

Below are example GIS maps. Click on each image to view a larger version.

CO Breast Cancer Screening Map      Map of Average Annual Age-Adjusted Female Breast Cancer Mortality Rates by County, WV, 2009-2013

Tennessee 2004-2013 Kriging Map              Active Mammography Facilities Map

Introduction

The ASTHO Breast Cancer Disparities Learning Community was born out of providing a response to the alarming trend that black women in the U.S. are approximately 40 percent more likely to die of breast cancer than white women. Through the learning community, we were able to look at state-level data contributing to this national trend in Arizona, Tennessee, and West Virginia. With a focus on improving epidemiologic capacity, states that participated in the learning community were better equipped to define their disparity and in position to take data-driven action with the input of key stakeholders.

 Map comparing white and black women breast cancer cases

Differences in Screening, Follow-up, and Treatment

Screening: Black women get mammograms as often as white women

Black and white women reported equal breast cancer screening in 2010 (mammograms every 2 years for women 50 to 74: 74% versus 73%). More black women are found to have breast cancer that has spread beyond the breast (45%) compared with white women (35%).

Follow-up: Black women get follow-up care later than white women

More black women experience follow-up times of over 60 days (20%) compared with white women (12%) after a mammogram that is not normal. Waiting longer for follow-up care may lead to cancers that spread beyond the breast and are harder to treat.

Treatment: Black women have different treatment experiences than white women

Only 69 percent of black women start treatment within 30 days (compared with 83% of white women). Fewer black women receive the surgery, radiation, and hormone treatments they need compared to white women. Black women have 9 more deaths per 100 breast cancers diagnosed compared to white women.

The learning community states looked across screening, time to treatment and quality of treatment to measure the impact of health disparities. The process involved:

Step 1: Gathering demographics across the entire state, and then, by assessing certain criteria, scaling down to zero in on the priority populations.

  • Population by county
  • Acknowledge any sovereign land (e.g., tribal or reservation)
  • Incidence/mortality rates across state 

Step 2: Drafting a problem statement or hypothesis.

Step 3: Through a set of questions, expand data sets to help answer those questions and tell more of your story

  • Time since last mammogram by race/ethnicity, age group, etc.
  • Mammograms received over certain period of time by race/ethnicity, age group, etc.
  • Access state cancer registry data to look at things like:
         -  All female breast cancer cases by race/ethnicity, age group, etc.
         -  Median age of diagnosis by race/ethnicity, income level, insurance type, etc.
         -  All female breast cancer across race/ethnicity, etc. by days from diagnosis to first course of treatment. Analyze invasive female breast cancer across race/ethnicity, etc., by ER, PR, and HER2 combination results and county groups. 

Step 4: Expand your stakeholders in order to broaden the data sources included in your analysis to further define the burden of breast cancer and provide answers to the present disparities.

Step 5: Use your findings to open the lines of communication among influential leaders, policymakers, clinical providers and community groups serving individuals representing the priority population.

Finally, understand that analysis is an ongoing process without a concrete end date. As interventions and practices are implemented within the system of care or programs, it will be important to reanalyze your data to determine the efficacy of the interventions.

We captured some recommendations for measuring the influence of disparity on access to screening, time to schedule and complete a follow-up appointment after abnormal screening and the quality of treatment.

Screening and Health Disparities Slide Cover               Time to Treatment Slide Cover               Quality of Treatment Slide Cover

In addition, please see this brief video presentation in which Alicia Smith from ASTHO discusses how to address follow-up to quality treatment through coordinated measured approaches.

Where resources allowed, patient navigation proved to help improve outcomes in vulnerable populations by eliminating barriers to timely follow-up and the quality of treatment. Patient navigators have the ability to investigate risk factors associated with discrimination related to poverty and low economic status, education level, culture and language. Further, patient navigators serve as connectors linking community and clinical services and supporting patients with access and enrollment in programs designed to address such risk factors.

The George Washington Cancer Institute developed a toolkit to guide states in advancing patient navigation, Advancing the Field of Cancer Patient Navigation: A Toolkit for Comprehensive Cancer Control Professionals. Challenges with access to care are exacerbated by the influence of the social determinants of health and health disparities. This toolkit highlights best practices to properly train patient navigators, integrate patient navigation within systems change strategies and evaluate the use of patient navigators to reduce the burden of health disparities.

In addition, this video presentation from Maritza Arce-Larreta from the Utah Cancer Control Program discusses opportunities to integrate community health workers and patient navigators into state cancer control program initiatives.

Introduction

According to the CDC, conditions impacting the places where people live, learn, work and play affect a wide range of health risks and outcomes. Risk factors, such as poverty and education, often determine one’s ability to access healthy foods, live in safe neighborhoods and maintain healthy lifestyle behaviors. Through numerous research outlets, education remains a key predictor of health status.

The Data Set Directory of Social Determinants of Health at the Local Level, developed by the University of Michigan School of Public Health and funding from CDC, aims to respond to understand and address the socioeconomic contexts within which people work and play in order to improve their health and welfare. The directory contains an extensive list of existing data sets that can be used to address these determinants. The data sets are organized according to 12 dimensions, or broad categories, of the social environment. Each dimension is subdivided into various components.

Data Set Directory of Social Determinants of Health at the Local Level Cover Image
View Data Set Directory of Social Determinants of Health at the Local Level (PDF) »

Public health agencies represent the laboratories for change embedded within the communities they serve. Their roles as health providers, interpreters of conditions through data analysis, and natural conveners of stakeholders make them uniquely situated to incorporate interventions that effectively address health inequities. The CDC developed a brief document intended to help public health agencies insert social determinants of health practices within their portfolio.

Ten Essential Public Health Services and How They Can Include Addressing Social Determinants of Health Inequities Cover Image
View Ten Essential Public Health Services and How They Can Include Addressing Social Determinants of Health Inequities (PDF) »
 

Data Collection

Introduction

The collection and analysis of data from a variety of sources is a key step in understanding who is impacted by breast cancer disparities, and where those people are located. Telling a compelling and accurate story using data and GIS mapping galvanizes stakeholders to help collectively address identified disparities and promote health equity in the diagnosis and treatment of breast cancer. Data analysis is an essential step in the process of understanding which populations are impacted by breast cancer disparities along the continuum of care. States can reference their cancer registry, federal data, and other data sources to generate maps and communicate the greatest needs within their state to relevant stakeholders.

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.

Data analysis is an essential step in the process of understanding which populations are impacted by breast cancer disparities along the continuum of care, and where those disparities manifest themselves in geographic space. A good starting point is to compare available breast cancer data along the continuum of care against demographic data in as granular a manner as possible (e.g., county level, census tract level, zip code level, etc.) to understand how sociodemographic factors might be influencing the screening, diagnosis, treatment, and care of breast cancer, and where the most impacted populations are located.

A complete list of helpful data sources is available in the Public Resources Library located at the top of the toolkit. Each state should also make strong use of its state cancer registry to access the most up-to-date information on breast cancer prevalence, incidence, and mortality. Stakeholders such as community groups and healthcare payers and providers might also be able to make additional data available, further underscoring the importance of partnerships.

In their first year of participating in the learning community, each state has 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. You can use ASTHO’s data report template to create your own version of this report to communicate with stakeholders.

Introduction

There is a wide variety of stakeholders with an interest in better understanding and reducing breast cancer disparities, and these stakeholders can play a number of roles in collaboratively addressing breast cancer disparities. State health agencies have an important role to play in keeping stakeholders organized and engaged in collaborating to address breast cancer disparities and promote health equity.

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, healthcare, healthcare 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.

Apart from being potentially helpful sources of strong data (especially in the case of clinical partners and insurers), stakeholders will play a variety of roles in the planning and implementation of any activity that addresses breast cancer disparities. Community groups and the faith community may contribute knowledge about populations experiencing disparities and might also be strong allies in implementing a community level intervention. Clinical partners, including hospitals, FQHCs, and other screening sites, undoubtedly have an important role to play along the full continuum of care, such as in implementing new screening guidelines, instituting patient navigation programs, and establishing treatment quality benchmarks. Academic partners can provide assistance with research and data analysis.

State examples of key partnerships across different stakeholder groups include:

  • Arizona relied upon its state Well Woman contracted mammography providers to implement a new policy that makes mammograms available to women over 40 instead of over 50 after their initial data analysis uncovered a lower average age of diagnosis for minority women than for white women.
  • Tennessee has worked with members of the Memphis faith community and private service providers to address identified transportation barriers in Memphis to ensure low-income women are better able to attend treatment appointments.
  • West Virginia has maintained a strong partnership with the Charleston Area Medical Center (CAMC), which has taken initiative to implement a Project ECHO that assists rural physicians in providing breast cancer survivorship care in the primary care setting.

State health agencies have an important role to play in keeping stakeholders organized and engaged in collaborating to address breast cancer disparities and promote health equity. When presenting new data findings and brainstorming long term coordinated strategy every six to 12 months, in-person convenings hosted by the health agency have proven to be the most fruitful. Between those engagements, virtual or phone meetings to report progress on assigned action plan responsibilities can take place monthly, bimonthly, or quarterly to ensure ongoing collaboration.

Introduction

GIS mapping has a key role to play in plotting data by geographic area to identify breast cancer disparities along the continuum of care in geographic space. Hotspot analysis, the calculation of risk scores, and plotting access to services by transportation time are just some of the possible uses of GIS mapping to aid in data-driven decisionmaking.

GIS mapping allows for breast cancer screening, prevalence, and mortality data to be examined geographically to pinpoint priority areas. Hotspot analysis, such as this Tennessee example performed on breast cancer mortality rate at the county level, can identify areas that are better or worse off than surrounding communities to a statistically significant degree.

Map of Breast Cancer Mortality Rate by County, 2004-2013 Hot Spot Analysis

Additionally, sociodemographic disparities in these key statistical measures can be analyzed across geographic space through GIS mapping. This can help identify the “who” and the “where” of specific populations that stand to benefit the most from specifically tailored interventions. After deciding to focus on Memphis and the surrounding Shelby County area, Tennessee calculated a risk score incorporating factors prioritized by their stakeholder group – breast cancer incidence, breast cancer mortality, insurance rate, and poverty rate.

Breast Cancer Risk Map

GIS mapping has the unique ability to shed light on how access to different breast cancer services might differ across space or differ by sociodemographic groups. One simple way to do this is to overlay a map displaying key breast cancer data (e.g., screening rates or mortality rates) with the locations of key healthcare providers (e.g., FQHCs, all screening or treatment facilities, and/or Commission on Cancer accredited hospitals). Helpful state examples of this are below:

Map of Average Annual Age-Adjusted Female Breast Cancer Mortality Rates by County, WV, 2009-2013

 Mammography and BCCP Providers Map

Additionally, GIS mapping can allow for the calculation and display of transportation time to the different screening and/or treatment providers listed above. This can be done statewide or on a more granular level once a priority area is identified.

Active Mammography Facilities Map

Commission on Cancer Approved Hospitals With 30-Minute Drive Time Area

Esri and CDC have both been key partners throughout the learning community in helping to build state capacity in the area of GIS mapping. Helpful resources from both organizations are shared below – see the Public Resources Library for more GIS mapping resources and see the Templates and Tools page for more state examples.

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. 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:

GIS and Public Health at CDC

There are a number of GIS resources available on the CDC website:

Quality Improvement Model (PDSA)

Introduction

An inter-related framework for systems in a state that support breast cancer screening, follow-up and treatment is illustrated below. This aims to contextualize the roles of a diverse range of state and local-level partners involved in each state’s project, as well as the different settings and partners within a community that are involved in creating systems of care for breast cancer identification and control.

System Framework Breast Cancer Support Illustration

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 to incorporating the PDSA model.

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?

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 ASTHO Templates and Tools section of this toolkit. The strategies should include roles for each stakeholder and should be identified after considering the resources and assets available, such as data to inform decision making and note individuals in the target population.

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.

Introduction

ASTHO’s evidence-based Breast Cancer Learning Community Change Package, informed by an extensive journal literature review and the action plan proposals of learning community public health agencies, 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.

Additional references to assess the implications of other interventions can be explored within the following resources:

ASTHO conducted a literature review to explore the answers to questions to help guide data analysis decisions and to inform the selection of intervention and avoid unintended consequences.

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 Non-white 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


1. https://www.ncbi.nlm.nih.gov/pubmed/28033538
2. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5181819/
3. http://onlinelibrary.wiley.com/doi/10.1002/cncr.10933/full
4. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2774639/
5. http://eds.a.ebscohost.com.proxygw.wrlc.org/eds/pdfviewer/pdfviewer?sid=73ea8453-ee93-46ae-b83a-bc1fca4f2545%40sessionmgr4010&vid=2&hid=4210
6. https://www.ncbi.nlm.nih.gov/pubmed/15009798
7. https://www.sciencedirect.com/science/article/abs/pii/S1353829210000870
8. http://www.sciencedirect.com/science/article/pii/S1353829210000870
9. https://www.ncbi.nlm.nih.gov/pubmed/16618951
10. http://www.jacr.org/article/S1546-1440(16)30722-0/fulltext

ASTHO conducted a literature review to explore the answers to questions to help guide data analysis decisions and to inform the selection of intervention and avoid unintended consequences.

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.1 One study in Illinois found an inverse relationship between access to primary care and late stage diagnosis risk.2 Data suggests that with increasing visits to the physician, breast cancer outcomes are improved and late-stage diagnoses are reduced.1 Additionally, research has indicated that poorer geographic access to primary care is linked to late diagnosis.3 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.4 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.5,6 One study analyzed the effect of density and often found a positive correlation between percent of women screened and the number of mammography facilities per 10,000 women at the state level.7

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.8 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.3 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 Mississippi study showed no statistically significant connection between breast cancer outcomes and the availability or access to mammography facilities.9

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.4 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.4,10

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.11 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.11

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.12 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.12 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.13 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.4


1. http://www.annfammed.org/content/10/5/401.full
2. https://www.tandfonline.com/doi/full/10.1080/00330120701724087?scroll=top&needAccess=true&
3. https://www.ncbi.nlm.nih.gov/pubmed/20630792
4. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4933961/
5. https://www.ncbi.nlm.nih.gov/pubmed/22037904
6. https://www.ncbi.nlm.nih.gov/pubmed/20195174
7. https://www.ncbi.nlm.nih.gov/pubmed/15772962
8. https://www.ncbi.nlm.nih.gov/pubmed/26223824
9. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3959918/
10. https://www.ncbi.nlm.nih.gov/pubmed/22952626
11. https://www.ncbi.nlm.nih.gov/pubmed/21553117
12. https://academic.oup.com/jnci/article/93/17/1344/2519497
13. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3475100/

ASTHO conducted a literature review to explore the answers to questions to help guide data analysis decisions and to inform the selection of intervention and avoid unintended consequences.

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.1 Furthermore, geographic variation of treatment has a significant impact on treatment type, treatment intensity and cost of care.2,3

There is also geographic variation in the magnitude of racial disparities in breast cancer treatment across the United States.3 For instance, black patients in areas of the northeastern and southern United States show the lowest rates of radiation therapy.4 Poor spatial accessibility to health care services, especially for women who rely on public transportation, prevent optimal treatment for women with breast cancer.5

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.6 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.7 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.8,9,10,11 Additionally, studies show mixed results for whether black women are more likely to receive mastectomies compared to white women.12,13,14 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.15

The literature has shown mixed results regarding the relationship between timely breast cancer treatment and survival.16,17,18,19,20,21 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.22 African American women experience more diagnosis and treatment delays when compared to women of other racial/ethnic subgroups.23,24,25,26,27 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.8 Madubata and colleagues (2016) found that black women had higher odds of radiation delay than their white counterparts.13


1. https://www.ncbi.nlm.nih.gov/pubmed/23909950
2. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4164811/
3. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3596448/
4. https://www.ncbi.nlm.nih.gov/pubmed/20014181
5. https://www.ncbi.nlm.nih.gov/pubmed/23726213
6. https://www.ncbi.nlm.nih.gov/pubmed/20939011
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Introduction

Public health policy has been revered as an element in communities contributing to profound and sustainable impact on a community’s health status. The participating states used their data to determine which formal laws, rules and regulations (“Big P” policies) to use to educate their elected officials. Organizational guidelines and internal agency decisions/agreements (“Little p” policies) served as the most common form of policies enacted during and beyond the learning community. 

Refer to this policy planning tool for public health agency conveners to assess readiness to advance evidence-based policy interventions. 

The participating states explored telehealth and telemedicine models to connect specialty and primary care physicians to address complex patient conditions to inform policy, protocols, and treatment decision monitoring.

For example, Project ECHO is an ongoing guided learning model that focuses on the public health workforce’s capacity to provide the highest quality care and reduce health disparities. This model is characterized by hub-and-spoke information-sharing networks that are led by expert teams using virtual platforms to host clinics for providers. Telehealth platforms are assisting health care systems and private practices to create pathways for improved understanding, incorporation of evidence-based practice and proper alignment with national quality standards.

According to an article in the American Journal of Law and Medicine, healthcare reform that aims to eliminate health disparities in rural and other disadvantaged areas has an opportunity to consider using technology to increase access to healthcare services, but must integrate telemedicine within a comprehensive approach rather than as a standalone service.

The West Virginia team partnered with researchers at the Charleston Area Medical Center to start a Project ECHO tele-mentoring program with rural physicians to improve primary care for breast cancer survivors in areas with poor healthcare access.  

Telehealth Example

Implementation

Introduction

States can use several resources for evidence-based interventions to address the disparities that data analysis and needs assessment reveal, but should ensure that they have been proven 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 interventions. 

Additionally, the Community Preventive Services Task Force releases evidence-based recommendations on public interventions that reduce disease burdens and improve well being via the Community Guide. The Community Guide provides an objective process for convening partners in multiple sectors and prioritizing problems and solutions together during implementation planning. It also contains a wealth of evidence-based recommendations specific to cancer prevention and control (including for breast cancer).

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.

The State Health Assessment Guidance and Resources document includes four modules covering important components of the state health assessment process:

  1. Identifying and engaging system stakeholders.
  2. Collecting and analyzing health status data.
  3. Collecting and analyzing stakeholder and community input data.
  4. Summarizing, presenting, and communicating findings.

Community Health Needs Assessment (CHNA) and implementation strategies are newly required of tax-exempt hospitals as a result of the Patient Protection and Affordable Care Act. These assessments and strategies create an important opportunity to improve the health of communities. They ensure that hospitals have the information they need to provide community benefits that meet the needs of their communities. They also provide an opportunity to improve coordination of hospital community benefits with other efforts to improve community health. By statute, the CHNAs must take into account input from “persons who represent the broad interests of the community served by the hospital facility, including those with special knowledge of or expertise in public health.”

Since the passage of IRS and Public Health Accreditation Board requirements for community-based health assessments in 2011, state and federal agencies have sought ways of encouraging collaboration between local public health departments and rural hospitals. ASTHO explored a framework and regulatory background to inform how and why rural communities approach community-based health needs assessments. Further, ASTHO detailed the opportunities and barriers that local public health departments and rural hospitals face in their attempts to work collaboratively on projects. By scanning models from across the country, ASTHO highlighted areas of education and collaboration, funding, and data sharing as opportunities for increased collaboration. The environmental scan provided several recommendations for how state offices of rural health and state health officials can work collaboratively to encourage local public health departments and rural hospitals to complete joint community-based health needs assessments.  View Community-Based Health Needs Assessment Activities: Opportunities for Collaboration Between Public Health Departments and Rural Hospitals to learn more »

In 2014, the Internal Revenue Service published final rules for the Affordable Care Act’s community health needs assessment (CHNA) requirement. The IRS allows charitable hospitals to rely on both the 2012 and 2013 proposed rules until the hospital’s first tax year after December 29, 2015. The final rules address various regulatory issues, including definitional changes, health needs assessments under expanded regulations, implementation strategies, financial assistance policies, and preemption. ASTHO detailed the IRS final rule issuing a State Health Policy brief. 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. Below are case studies detailing healthcare and state health agency collaboration practices around community health needs assessments:

Introduction

To address disparities, the learning community states strengthened their ability to mobilize data resources by diversifying their menu of involved stakeholders. A truly broad stakeholder group should include representation from a wide range of sectors, including public health, healthcare, healthcare financing, health information technology, and quality improvement. Visit the Key Stakeholders section for a full list of partners to consider including in your statewide breast cancer prevention and control efforts.

Partnerships with stakeholders across the continuum of breast cancer care and beyond public health, such as housing, transportation, and education, allow for a multidisciplinary approach that addresses the social determinants of health and can better inform public health policy and program development. Additionally, by expanding data sources during data collection and analysis, public health agencies help decisionmakers establish statewide policy and funding priorities for chronic conditions. The most effective initiatives engage a broad range of stakeholders at the state, local, and community levels. Key stakeholders should be represented across different categories:

HEALTHCARE

  • Accountable care organizations
  • Health systems
  • Hospitals
  • Primary care physicians
  • Specialists
  • Individual physicians and other non-physician cancer providers

STATE AND LOCAL GOVERNMENT

  • State policymakers and leaders
  • State health agency
  • State Medicaid agency and Medicaid managed care plans
  • Local health departments
  • Federally Qualified Health Centers, community health clinics, and cancer clinics
  • Public health nurses
  • Comprehensive Cancer Control Program

ACADEMIA

  • State geographic information system clearing house
  • Academic institutions and researchers

INFORMATICS AND IT

  • Regional or state health information exchanges
  • health center-controlled networks
  • health IT partners

COMMUNITY, COALITIONS AND ASSOCIATIONS

  • Private health plans and health insurance companies
  • Community health center networks
  • State physician associations
  • State quality improvement organizations
  • Advocacy organizations (for example, Susan G. Komen Foundation state affiliates)
  • Social service providers
  • Community health workers
  • Patient navigators
  • Care coordinators
  • Case managers
  • Community-based organizations
  • Religious institutions and leaders
  • Comprehensive Cancer Control Coalition

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

Coming soon!

Introduction

ASTHO sought to answer three questions through this evaluation of the Breast Cancer Disparities Learning Community: 

  1. Does participation in the ASTHO Breast Cancer Disparities Learning Community provide participating state teams with the information, resources, and expert advice they need to better identify and address breast cancer disparities in their states?
  2. Is the ASTHO Breast Cancer Disparities Online Toolkit perceived as a user-friendly, informative and effective resource that helps increase the capacity of health department teams?
  3. Did state involvement in the learning community result in increased identification of disparities and implementation of effective interventions?
To learn more about the evaluation and findings, view the ASTHO Breast Cancer Disparities Learning Community Evaluation Year 3 Review (PDF).

Leaders set the tone and those who advocate for and prioritize health equity through strategic partnerships with other governmental agencies help to establish a strong infrastructure for health equity, operational alignment, and the ability to secure the appropriate resources needed to support continuous evaluation and sustainable strategic implementation.

Workforce development consists of identifying activities, resources, and systems that increase the capacity of public health professionals to carry out public health functions and ensure optimum organization of human capacity. ASTHO’s State Public Health Employee Worker Shortage: A Civil Service Recruitment and Retention Crisis report concluded that the combination of a rapidly aging public health workforce, employee retirement rates as high as 45 percent over the next five years, current vacancy rates as high as 20 percent in some states, and turnover rates of up to 14 percent in parts of the country all add up to a public health employee shortage crisis in a majority of the states. Since public health agencies' primary resource is people, it was important for the learning community states to outline workforce development needs as part of their sustainability plans, as a shortage in a capable workforce will further strain a system meant to address disparities.

The Comprehensive Cancer Control (CCC) Branch Program Evaluation Toolkit helps grantees plan and implement evaluations of their National Comprehensive Cancer Control Program (NCCCP)-funded programs. The five-section toolkit provides general guidance on evaluation principles and techniques, as well as practical templates and tools. View the NCCCP CCC Branch Program Evaluation Toolkit webpage for more information.

Public health agencies are laboratories for change with the expertise to improve health equity for all. Through ASTHO’s Breast Cancer Disparities Learning Community, six public health agencies and their community and clinical statewide partners implemented comprehensive, cross-sector systems change interventions to reduce the burden of breast cancer mortality in their communities. This toolkit provides a coordinated guide of events to operationalize best practice interventions by mobilizing data resources more effectively to address disparities in breast cancer mortality. The toolkit is structured around a set of phases that public health agencies and community and clinical stakeholders can apply to increase their capacity for effective data collection and analysiscoordinated stakeholder engagement, and sustainable implementation and evaluation. To begin, select any one of the four phases above. For more information about this toolkit, visit the About page.