Wednesday, September 30, 2015

Esri Health Conference, 2015

Mark Carrozza, Dirctor of HealthLandscape, recently blogged about the idea that "Place Matters," especially when it comes to health and health care. It was fitting, then, that HealthLandscape had two presentations on the agenda at this year's Esri Health Conference, which was themed "Making Place Matter."

Our first presentation was an overview of two HealthLandscape tools - The Medicare Data Portal and Accountable Care Organization (ACO) Explorer. The aim of these tools is to help put the power of geographic visualization in the hands of researchers and policy makers. 

The Medicare Data Portal engages decision-makers and researchers with county and Hospital Referral Region (HRR) data from the Centers for Medicare & Medicaid (CMS) Geographic Variation database and the Chronic Conditions Warehouse. Users are able to visualize health outcome, cost, and demographic data for the Medicare population using maps, graphs, and trend charts. Users also have the ability to examine the relationship between two indicators (for example, Inpatient Costs and Diabetes) with side-by-side maps and a comparison tool that uses percentiles to visualize the relationship between variables. Users can choose from over 100 indicators across 6 categories, including Medicare Population data, Chronic Conditions, Utilization, Costs, Multiple Chronic Conditions, and Dartmouth Measures.

The ACO Explorer presents data for 211 Accountable Care Organizations, or ACOs. As part of the Affordable Care Act, new models of health care delivery have been developed, aimed at improving the quality of care while reducing costs. ACOs are being touted as potential solutions for the inefficiency and fragmentation of the U.S. healthcare system.  ACOs are made up of groups of doctors, hospitals, and other health care providers that coordinate care for Medicare beneficiaries. The tool allows users to visualize 33 quality metrics across five domains, which are compared against benchmarks set by CMS. Each point represents an accountable care organization. When you hover over or click on a specific site, flared rollover windows will appear that contain data about the quality measures included in each of the five domains, which will be colored red, yellow, or green based on their value respective to the thresholds. 

This set of tools can be accessed at For more detailed information, check out our previous blog post, or sign up for an upcoming webinar.

In addition to the more traditional paper sessions, the conference plenary session featured a round of Lightning Talks, where each presenter had a strict 5 minute window in which to present their ideas. Mark presented the HealthLandscape GeoEnrichment API, a HIPAA-compliant Data as a Service (DaaS) solution that appends multiple geographic identifiers and small-area community characteristics to individual data. This project involves integrating social determinants of health data into patient level data to yield a broader view of the environmental and social risks specific to each patient by indicating whether patient lives in the presence of factors such as poverty, healthy food sources, walkable streets and parks, social capital, and much more.  

We're very excited about all of the possible applications of this simple, but powerful, tool, and we look forward to sharing our ideas and plans in future blog posts.

Jené Grandmont
Senior Manager, Application Development and Data Services

Wednesday, September 9, 2015

UDS Mapper Update: New Data and Features!

The UDS Mapper is the premier tool built on the HealthLandscape platform.  Designed to visualize areas of potential need for new federally funded health centers, the UDS Mapper continues to be updated and grow each year.  This year is no exception.  On August 20th, we rolled out the newest version of the UDS Mapper with updated and new data, and improved functionality.

The UDS Mapper is now using data from 2014 showing where patients come from to receive services at health centers.  These health centers are funded by or affiliated with the Health Center Program of the Bureau of Primary Health Care, Health Resources and Services Administration.  Each organization completes a detailed report on the patients they see each year in the Uniform Data System (UDS).  Health Centers report on a calendar year basis and those data are cleaned and aggregated before being uploaded into the UDS Mapper.
In addition to having the newest health center data available, this year we are excited to be able to include information about patients based on their insurance status.  These data have only been reported by health centers for the past two years in the UDS Report.  Now UDS Mapper users can visualize where there are pockets of people by insurance status in communities, how well health centers are reaching them, where there are pockets of unmet need, and what changes have occurred over the past year. With these maps we can start to see if health centers are losing uninsured patients, gaining patients with insurance coverage, or gaining patients who remain uninsured having found no insurance coverage under Medicaid or in the Marketplaces.

Additional data that are available for health centers include whether they have received certification as a Patient-Centered Medical Home, whether they have implemented an Electronic Health Record at all sites and all providers are using it, and health center costs.

Jennifer L. Rankin, PhD
Senior Manager, Research and Product Services

For more information or to just begin using the UDS Mapper, please visit and plan on attending one of our free webinars!

Learn more about HealthLandscape with our online Webinars and Training

Wednesday, September 2, 2015

Hospitals Located in Distressed Counties in Appalachia Disproportionally Affected by Readmission Penalties

The Hospital Readmissions ReductionProgram (HRRP) requires hospitals to pay penalties if Medicare readmissions for common diagnosis are too high.  Despite increasing evidence that readmissions are more a result of social factors largely outside the control of hospitals, readmission rates and penalties are not risk-adjusted for socio-economic factors.  Not surprising given the socio-economics of the region, safety-net hospitals in the Appalachian region have higher readmissions and are more likely to receive higher penalties, with hospitals located in the most distressed counties of the region having the highest rates and most severe penalties.  These results highlight the importance of risk-adjusting for socio-economic factors for under-resourced regions and provide insights into the potential impacts of payment reform on safety-net clinics.
In an effort to control Medicare costs, the Hospital Readmissions Reduction Program was created as part of the Affordable Care Act.  The program requires hospitals to pay penalties if readmissions for common diagnosis such as Acute Myocardial Infarction, Heart Failure, Pneumonia, COPD, and Hip/Knee Replacement are too high. The HRRP has been levying fines on hospitals since the 2013 fiscal year, with maximum fines increasing from a 1% reduction in base Medicare Inpatient claims payment (in 2013) to a 3% maximum reduction in 2015. For fiscal years 2015 and 2016, close to 4 in 5 hospitals in the U.S. were fined for excess readmissions, though the majority received fines of less than 1%.
The first few years of data from the HRRP have shown that safety-net hospitals are more likely to receive higher penalties, with data indicating that factors affecting readmissions are largely outside the control of hospitals (Gu et al., 2014).  This is particularly troublesome for the Appalachian region, which has higher rates of poverty, less education, and worse health outcomes when compared to the United States as a whole (Appalachian Regional Commission, 2015).  A recent Kaiser Health News report noted that four hospitals have received the maximum readmission penalty all four years of the program, with three of these hospitals located in the Appalachia region (Kaiser Health News, 2015).  For the fiscal year 2016, about one-third of the 38 hospitals receiving the maximum penalty were located in Appalachia.  

Hospital Readmission (FY 2015) & Dual-Eligible Status (County)

# Hospitals (%)
% Dual Eligible (County)
% Readmission Rate (Hospital)
All (Appalachia)
No - Penalty
48 (10.1%)
Yes - Penalty
427 (89.9%)
Penalty >= 1%
108 (22.7%)
Penalty >= 2%
32 (6.7%)
Penalty = 3%
17 (3.6%)
 Source: CMS Final Rule MRRP, 2015; CMS Geographic Variation PUF, 2013; Appalachia Data Portal

Using a combination of web-based mapping and data visualization tools, we examined whether hospitals in Appalachia are more adversely affected by the HRRP than hospitals outside the region.  The table above shows the relationship between hospital readmissions (at the hospital level) and dual-eligible for Medicaid population (at the county-level).  Overall, almost 90% of hospitals in Appalachia were penalized for excess readmissions in 2015 (compared to about 80% for the U.S.), with more than 20% receiving fines of 1% or greater.  Moreover, hospitals with high readmission rates were located in counties with higher percentages of dual eligibles, with the largest fines levied against those hospitals located in counties with dual eligible populations of greater than 30%. The image below displays the difference in the percent of dual eligibles for the county in which the hospitals are located by whether the hospitals received a 2% fine or greater.

Source: CMS Final Rule MRRP, 2015; CMS Geographic Variation PUF, 2013; Appalachia Readmissions Explorer

There are also clear geographic patterns within Appalachia.  Hospitals with fines of greater than 2% are concentrated in central Appalachian, which is the most distressed region in Appalachia, with high rates of poverty and unemployment, and low rates of education.  Further, half of all the hospitals located in Appalachia that received fines of 3% in 2015 were located in distressed counties.

Appalachian Regional Commission, County Economic Status FY2016 (Distressed Counties in Red)

Source: Appalachia Data Portal & Readmissions Explorer

The Hospital Readmissions Reduction Program (HRRP) has been criticized for not risk-adjusting for the socio-economic circumstances of the populations that they serve, despite increasing evidence of readmissions being driven by factors largely outside the control of hospitals.  While there has been some movement towards risk-adjusting for socio-economic factors (the National Quality Forum has begun a two-year pilot studying the potential for risk-adjustment of socio-economic factors and the U.S. Senate has introduced a bill to incorporate socio-economic factors), changes to the penalties do not seem imminent.  Policy-makers need to consider risk-adjusting for social determinants of health and geographic variation for hospital readmissions, while also applying lessons learned when moving towards value-based payments for physicians and the detrimental impact that not risk-adjusting may have on safety-net clinics.

HealthLandscape Web-Based Data Visualization Tools

We used a combination of web-based mapping and data visualization tools, including the Appalachia Readmissions Explorer and the Appalachia Data Portal.  The Appalachia Readmissions Explorer is an interactive mapping tool that allows users to quickly compare readmissions for hospitals in the Appalachian Region.  Hospitals are colored red, yellow, or green – based on whether hospitals have readmissions worse, no different, or better than national average for all-cause readmissions and for the individual diagnosis of Heart Failure, Heart Attack (AMI), Pneumonia, COPD, Stroke, and Hip/Knee Replacements.  Mortality data have also been added which allows users to explore readmissions and mortality rates.  Users can also filter by whether a hospital was fined for excess readmissions in 2015, the percent amount of fine, and by whether a hospital received a penalty as part of the Hospital Value-Based Purchasing (HVBP) Program.  In addition, users can use the Stats tool to perform statistical analyses to explore relationships between hospital readmissions and mortality rates and population health indicators for the county in which the hospital is located. 

The Appalachia Data Portal is an online tool for exploring demographic, education, income, and health disparities for the 420 counties in the Appalachian region. The data included in the Appalachia Data Portal come from a variety of sources, including the American Community Survey, the Appalachian Regional Commission, the Robert Wood Johnson County Health Rankings, and the Centers for Medicare & Medicaid. The tool allows users to visualize economic, demographic, and other types of data for the Appalachian region using maps, graphs, and trend charts.  Users also have the ability to examine the relationship between two indicators (for example, Diabetes and Poverty) with side-by-side maps and a comparison tool that uses percentiles to visualize the relationship between variables.  The Appalachia Data Portal provides multiple methods for exploring population indicator disparities throughout the Appalachian region, and is a helpful tool for identifying health disparities and bright spots within the region.

Michael Topmiller
Health GIS Research Specialist 

To access the Appalachia Data Portal and Appalachia Readmissions Explorer, please visit

More information about the data sources are available at:
Medicare Hospital Readmissions Reduction Program:

Appalachia Regional Commission County Economic Status:

Appalachia Data Portal & Appalachia Readmissions Explorer
Appalachian Regional Commission (ARC), 2015.  County Economic Status Reports.
CMS Final Rule Medicare Readmissions Reduction Program (MRRP), 2015

CMS Geographic Variation Public Use File (PUF), 2013

Gu, Qian, Lane Koenig, Jennifer Faerberg, Caroline Rossi Steinberg, Christopher Vaz, and Mary P. Wheatley. 2014. The Medicare Hospital Readmissions Reduction Program: Potential Unintended Consequences for Hospitals Serving Vulnerable Populations. Health Services Research, 49(3): 818-833.
Kaiser Health News – “Half of Nation’s Hospitals Fail Again to Escape Medicare’s Readmission Penalties”