Place matters to personal and population health. We can help you understand YOUR data and local, regional, and national measures of health, economics, and demographics.


HealthLandscape is dedicated not only to data democratization and visualization, but also to research related to health, health care, and social determinants of health. We are actively:

  • Researching how our social circumstances affect our health and access to health care;
  • Applying geospatial and statistical techniques to help answer questions about disparities in health outcomes; and
  • Creating new visualization methods.

Our Geospatial Research Briefs highlight these interests. These short papers cover a variety of topics that are intended to demonstrate the power of geospatial analysis and tools for better understanding important issues related to health care. The research briefs emphasize the use of publicly accessible datasets, as well as data visualization and mapping tools, while focusing on the key areas of health disparities, population health, primary care, and value-based payment models.

Measuring Behavioral Health Need and Treatment Capacity

June 2022 - Michael Topmiller, PhD, Jennifer Rankin, PhD, Jessica McCann, MA, Morgan Walker, MS, Jene Grandmont, MA, & Mark Carrozza, MA

HealthLandscape developed an Integrated Behavioral Health (IBH) data visualization and mapping tool to compare behavioral health need and behavioral health assets. Targeting geographic areas for increasing access to IBH requires measures related to both behavioral health need and behavioral health care capacity. Several national behavioral health data sources include measures for both need and capacity (e.g., the National Survey of Drug Use and Health [NSDUH]), though few have data at a geography appropriate for exploring capacity relative to need and developing interventions. This brief discusses the rationale for the measures and geographies (i.e., NSDUH sub-state regions) included in the HealthLandscape IBH data visualization.

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Identifying Health Center Behavioral Health "Bright Spots"

June 2022 - Michael Topmiller, PhD, Jennifer Rankin, PhD, Jessica McCann, MA, Jene Grandmont, MA, Morgan Walker, MS, & Mark Carrozza, MA

Health centers provide health care services to the nation’s most vulnerable populations, including behavioral health care. Given health centers’ experience providing integrative behavioral health (IBH) and the evidence that IBH models increase access to care and improve outcomes, it is important to identify successful models within health centers that can be replicated to improve care. This study describes an approach for identifying high-performing (bright spot) Health Resources and Services Administration (HRSA)-supported health centers for in-depth study of IBH models. We also compare the geographic, organizational, and patient characteristics of bright spots with low-performing health centers (cold spots).

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Co-Location of Primary Care and Behavioral Health Clinicians

June 2022 - Mark Carrozza, MA, Michael Topmiller, PhD, Jessica McCann, MA, Jene Grandmont, MA, Morgan Walker, MS, & Jennifer Rankin, PhD

In this research, we create a proxy for the availability of integrated behavioral health (IBH) by using a workforce co-location methodology to explore the geospatial distribution of primary care practices and behavioral health providers. We explore the distribution of these practices relative to primary care and mental health care Health Professional Shortage Areas (HPSAs), Medically Underserved Areas/Populations (MUA/Ps), and urban/rural designation. This brief outlines the above, as well as an innovative methodology, the IBH potential score, which explores the distribution of likely-integrated behavioral health locations.

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Measuring IBH Potential: Weighting for "Probable" and "Possible" Collaborations

May 2022 - Mark Carrozza, MA, Jennifer Rankin, PhD, Michael Topmiller, PhD, Jessica McCann, MA, Jene Grandmont, MA, & Morgan Walker, MS

Determining whether a primary care setting employs an Integrated Behavioral Health (IBH) approach usually requires staff interviews, surveys, or detailed data on referrals and collaborations. These measures might be available in some electronic health records or health information exchanges but are not currently accessible to researchers and other stakeholders for the vast majority of practices throughout the country. There is a need for an IBH potential measure that provides insights into the potential capacity of primary care practice locations to do IBH. This brief describes the development of an IBH Potential Score that attempts to fill that knowledge gap.

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Targeting High-Need, High Minority Geographies: Improving Access to Behavioral Health Care

May 2022 - Michael Topmiller, PhD, Mark Carrozza, MA, Jennifer Rankin, PhD, Jessica McCann, MA, Jene Grandmont, MA, & Morgan Walker, MS

Preliminary analyses suggest that regions with high levels of poor mental health and larger minority populations have less access to mental health services. This is consistent with literature on disparities in mental health access for minority populations who also have less access to substance use treatment services. Minority populations are also less likely to have health insurance, face higher barriers to accessing primary health care services, and have fewer behavioral health professionals practicing in close proximity to primary care providers in their neighborhoods. This research identifies priority areas for addressing racial disparities in access to behavioral health care. 

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Influenza Immunization Rates as Planning Tool for COVID-19 Vaccination

January 2021 - Michael Topmiller, PhD & Mark Carrozza, MA

Annual vaccination rates for influenza and pneumonia vary significantly across the U.S., with some areas having much higher rates than others. Further, a lack of public health infrastructure and barriers related to social determinants of health limit the capacity of some areas to effectively vaccinate their populations. Stakeholders need to identify areas that may have higher rates of COVID-19 vaccine-hesitancy or refusal, areas that may lack capacity for large-scale vaccine distribution, and areas that have the most at-risk populations for COVID-19 hospitalizations and mortality. The purpose of this research is to explore the geographic variation of flu vaccine deficits across the U.S. and identify priority areas within each state for expanding COVID-19 vaccination efforts, with Virginia and Florida as examples.

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Distribution of Multigenerational Households by Race and Ethnicity, and Implications for COVID-19 Planning

August 2020 - Mark Carrozza, MA

While social determinants such as institutional racism, access to care, and wealth play a part in the differences in death rates, this brief focuses on geospatial and racial differences in multigenerational households. Households with multiple generations are particularly susceptible to intra-household COVID-19 spread. Difficulty in maintaining proper distancing for suspected or confirmed cases puts members of these households at a higher risk of becoming seriously ill or dying as a result of COVID-19.

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Where are Areas of Greatest Need of New Health Centers? A Spatial Empirical Bayes Approach

July 2017 - Michael Topmiller, PhD & Jennifer Rankin, PhD

Geospatial methods can also be integrated with Bayesian approaches to account for spatial variation and variance instability in regards to population. This brief illustrates the use of a spatial empirical Bayes approach to identify high-need areas based on low-income populations not served by the federally-funded Health Center Program (HCP).

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Exploring Competition and Proximity: A Comparison of Basic Methods

October 2016 - Jené Grandmont, MA

When planning for the expansion of services and determining areas of need, estimating people’s ability to reach health care services is an important issue. In order to accurately identify the areas in need of additional health care providers, while avoiding service area overlap, it is necessary to understand the practical accessibility of other nearby providers. While there is a wealth of literature exploring definitions and measures of potential access (Apparicio et al, 2008, Topmiller, 2013), this brief illustrates the importance of local context in choosing the right measure by exploring the relationship between potential health care access and utilization.

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Where are “bright spots” for appropriate Diabetes preventive care?

July 2016 - Michael Topmiller, PhD

Research has shown that higher rates of appropriate Diabetes preventive care can lead to better health outcomes, fewer hospitalizations, and lower spending (Gray et al., 2012; Kralewski et al., 2013). Our previous work has demonstrated that geographic variation exists for Medicare spending, hospitalizations, and preventive care, while also identifying priority regions for improving care (Topmiller, 2016). However, little is known about the strategies that lead to higher rates of preventive care and why rates vary so much across geographic regions. Finding the “bright spots,” regions with higher than expected rates of appropriate Diabetes preventive care, can assist researchers and policy makers in identifying successful strategies for producing higher rates. This brief utilizes a two-step geospatial approach for identifying regions that are appropriate Diabetes preventive care “bright spots.”

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Where are “hot spots” of Medicare spending and preventable hospitalizations and “cold spots” for preventive care?

May 2016 - Michael Topmiller

Many healthcare reform efforts are underway that are working towards achieving the triple aim of better care, better health, and lower costs. However, questions still remain about how reforms take into account the significant geographic variation of healthcare spending and utilization. Recognizing the importance of geography, researchers have developed hot-spot and cold-spot approaches for targeting healthcare super-utilizers and high need communities, offering potential models for identifying priority regions where policymakers can target scarce resources. Hot-spotting and cold-spotting has also been used in the field of geospatial analysis, where hot spots are defined as clusters of high values and cold spots as clusters of low values. Thus, we could think of clusters of counties with low rates of preventive care as cold spots. This brief details an approach for identifying priority geographic regions for improving preventive care.

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Do Regions with More Preventive Care Have Lower Spending and Fewer Hospitalizations?

March 2016 - Michael Topmiller, PhD

Complications from Diabetes are a major cause of hospitalizations and high Medicare spending, with about 27% of Medicare beneficiaries diagnosed with the disease (CMS, 2013). Appropriate Diabetes preventive care such as annual hemoglobin A1C tests, blood lipids LDL‐C tests, and eye exams have been shown to reduce complications with Diabetes and improve quality of life (Gray et al., 2012). Despite the evidence for positive outcomes associated with more preventive care, few studies have explored the relationship between Diabetes preventive care, utilization, and spending.
This brief explores the relationship of appropriate Diabetes preventive care to preventable hospitalization rates and Medicare spending per enrollee (age‐sex‐race adjusted).

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