Polis Center Works

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SAVI Public Health Needs Assessment: Final Report and Recommendations
(The Polis Center, IUPUI, 2007-07) Comer, Karen F; Kandris, Sharon; Colbert, Jay; Devadasan, Neil; Bodenhamer, David J
This report summaries the 2007 assessment of current and projected health sector uses of the SAVI Community Information System (SAVI) and recommends SAVI enhancements to meet the information needs of decision makers, practitioners, and researchers. Based on focus groups and key informant interviews, it was discovered that local decisionmakers and practitioners in Central Indiana currently used SAVI, or would like to use SAVI, to assess the relative spatial demand and supply of health and human services, select sites for new health and human service facilities, assess patient access to health and human service facilities, select locations for services and programs, and track characteristics of facility catchment areas. Health practitioners and public health professionals were interested in using geospatially-enabled indicators for more effective planning and interventions, including to track public health outcomes, understand the socio-economic and physical environment of individual patients and communities, locate target populations for existing and potential health programs and services, support grant applications, and inform the public about environmental risk factors and disease prevalence in their communities. Clinical translational and public health researchers are using, or would like to use, geospatially-enabled measures for the study of social and environmental determinants of health, health disparities, environmental exposure and health risk, predictors of health knowledge, ecological models of health behavior, health service access, quality, and cost, and efficacy of health interventions. Detailed recommendations are provided for both short- and long-term enhancements to SAVI based on the existing and potential SAVI users and uses identified via this study and toward assisting the local health sector improve health knowledge and ultimately the health and wellbeing of Central Indiana communities.
SAVI Data Catalog
(The Polis Center at IUPUI, 2011-04) Derr, Michelle; Colbert, Jay; Nalla, Goutami; Comer, Karen F.
The SAVI Community Information System (SAVI) is the nation’s largest spatially-enabled system of its type, providing local organizations, researchers, and involved citizens with the detailed, geographically precise information needed to make well-informed decisions. This data catalog describes the wealth of free data provided by SAVI, including data about the social, physical, and economic conditions of Central Indiana communities from counties to neighborhoods and census tracts, as well as information on thousands of non-profit and community-based organizations and programs. SAVI exists as a Web-based, interactive system that allows users to create custom maps, graphs, charts, and data profiles of over 2,000 Central Indiana communities.
Spatial Integration of Community Data with Clinical Data in Support of Community Health Research and Practice
(Office of the Vice Chancellor for Research, 2011-04-08) Frederickson Comer, Karen; Wiehe, Sarah E.; Wilson, Jeffrey S.; Dixon, Brian E.; Grannis, Shaun
This poster will describe the recent integration of one of the nation’s largest health information exchanges, the Indiana Network for Patient Care developed by the Regenstrief Institute, with one of the nation’s most comprehensive community information system, the SAVI CIS developed by The Polis Center at IUPUI. Integrating community data that quantifies the social and physical environment with clinical data has great potential for supporting and advancing community health research and practice. Multi-sector collaboration on the development and evaluation of associated uses cases informed system integration is allowing spatially-aware research and practice to be more quickly realized.
Community Health Information Resource Guide: Volume 1 - Data
(The Polis Center at IUPUI, 2011-06) Comer, Karen F; Derr, Michelle; Seyffarth, Chris; Thomaskutty, Champ; Kandris, Sharon; Ritchey, Matthew
This resource guide contains useful information for those who would like to use data to assess the health status of an Indiana community. Targeted users include local organizations such as county health departments and community health coalitions. Being able to access and use relevant data and information resources is a common hurdle for those interested in assessing and advancing community health. As a result of this need and at the request of the Community Advisory Council of the Community Health Engagement Program, we developed this resource guide to assist individuals, organizations, and coalitions in Indiana in identifying appropriate resources that guide their community health research and evaluation activities. The term “data” is used in this volume in reference to both data and information sources. While data consist of raw facts and figures, information is formed by analyzing the data and applying knowledge to it so that the findings are more meaningful and valuable to the community. The benefit of using data is that you can often manipulate it for your specific purposes. The benefit of using information sources is that the work of generating meaning from the data might already have been done, while a potential downside is that the available sources might not answer your specific questions. There are diverse sources of data that can be used as a basis for community health evaluation and decision making. Those looking to use data must consider multiple factors before determining the appropriate data to seek and use.
Digital Atlas of American Religion
(2013-04-05) Bodenhamer, David; Kandris, Sharon; Devadasan, Neil; Colbert, Jay; Dowling, Jim; Danielson, Laura
Our poster presentation will introduce DAAR, the Digital Atlas of American Religion (http://www.religionatlas.org). DAAR is a web-based research platform with innovative data exploration and visualization tools to support research in the humanities. Time and location are essential components of humanities exploratory research; however, GIS technology, especially in its web form, does not support the easy exploration and visualization of the complex spatio-temporal data manipulated by humanists. DAAR presents researchers with an integrated solution stemming from several fields including GIS, visualization, and classification theory. Researchers using DAAR are provided with the following exploration/visualization techniques: maps, cartograms, tree maps, pie charts, and motion charts. Using these tools and methods, researchers can explore patterns, trends, and relationships in the data that otherwise are not apparent with traditional GIS or statistical software. DAAR allows researchers to understand the multiple dimensions and diversity of religion across geographies, or within geographies. Paired with historic census data, it allows them to explore relationships to give better context and meaning to the patterns and trends. Maps provide the spatial patterns and relationships, tree maps show relative strength and relationships, charts show trends, cartograms reveal relative numbers of adherence, and motion charts animate trends over time.
Improved Analysis and Visualization of Community Indicators and Indices
(Office of the Vice Chancellor for Research, 2013-04-05) Farah, Christopher; Kandris, Sharon; Frederickson, Karen Comer
The analysis and interpretation of community indicators has been widely conducted to understand community trends, and subsequently, to support program planning, public policy initiatives, and target geographic regions for research. Given the importance of the outcomes, selecting good indicators is key, and usually a balance of stakeholder input and analytical evaluation. The most common analysis method used to evaluate a set of indicators is principal component analysis (PCA), a linear multivariate analysis method. However, the assumptions of PCA may be too restrictive and consequently, the analysis may fail to provide a sound evaluation of the set of indicators. In response to this shortcoming, we paired PCA with an unsupervised, non-linear multivariate method, known as self-organizing maps (SOMs), to analyze a set of indicators focused on population trends in education, income, employment, among others, at both the county level and the census tract level. The joint results were used to: exclude or include indicators from the indicator set, determine the latent primary dimensions of the dataset, identify peer counties and census tracts (relative to Indiana counties / census tracts), identify associations among different indicators at different geographic scales, identify temporal changes in the value of indicators, and develop one or more indices to describe socio-economic conditions of communities. Outcomes are presented geographically, topologically, tabularly, and graphically, offering different mechanisms of understanding and interpreting the analysis results. A goal of this project is to provide a web-based interface for researchers and community stakeholders to identify and evaluate candidate sets of community indicators, potentially accelerating sound public policy decisions and public health research.
Promotion and tenure for community-engaged research: An examination of promotion and tenure support for community-engaged research at three universities collaborating through a Clinical and Translational Science Award
(http://dx.doi.org/10.1111/cts.12061, 2013-06-06) Marrero, David G.; Hardwick, Emily J.; Staten, Lisa K.; Savaiano, Dennis A.; Odell, Jere D.; Frederickson, Karen; Saha, Chandan
Introduction. Community engaged health research, an approach to research which includes the participation of communities, promotes the translation of research to address and improve social determinants of health. As a way to encourage community engaged research, the National Institutes of Health required applicants to the Clinical and Translational Science Award (CTSA) to include a community engagement component. Although grant-funding may support an increase in community engaged research, faculty also respond to the rewards and demands of university promotion and tenure standards. This paper measures faculty perception of how three institutions funded by a CTSA support community engaged research in the promotion and tenure process. Methods: At three institutions funded by a CTSA, tenure track and non-tenure track faculty responded to a survey regarding perceptions of how promotion and tenure committees value community engaged research. Results: Faculty view support for community engaged research with some reserve. Only 36% agree that community engaged research is valued in the promotion and tenure process. Discussion: Encouraging community engaged scholarship requires changing the culture and values behind promotion and tenure decisions. Institutions will increase community engaged research and more faculty will adopt its principles, when it is rewarded by promotion and tenure committees.
Measuring Population Health Using Electronic Health Records: Exploring Biases and Representativeness in a Community Health Information Exchange
(IOS, 2015) Dixon, Brian E.; Gibson, P. Joseph; Comer, Karen Frederickson; Rosenman, Marc; Department of Epidemiology, Richard M. Fairbanks School of Public Health
Assessment is a core function of public health. Comprehensive clinical data may enhance community health assessment by providing up-to-date, representative data for use in public health programs and policies, especially when combined with community-level data relevant to social determinants. In this study we examine routinely collected and geospatially-enhanced EHR data to assess population health at various levels of geographic granularity available from a regional health information exchange. We present preliminary findings and discuss important biases in EHR data. Future work is needed to develop methods for correcting for those biases to support routine epidemiology work of public health.
Using Electronic Health Record Data to Improve Community Health Assessment
(UKY, 2016) Dixon, Brian E.; Zou, Jian "Frank"; Comer, Karen F.; Rosenman, Marc; Craig, Jennifer L.; Gibson, P.; Epidemiology, School of Public Health
Background: Community health assessments assist health departments in identifying health needs as well as disparities, and they enable linking of needs with available interventions. Electronic health record (EHR) systems possess growing volumes of clinical and administrative data, making them a valuable source of data for ongoing community health assessment. Purpose: To produce population health indicators using data from EHR systems that could be combined and visually displayed alongside social determinants data, and to provide data sets at geographic levels smaller than a county. Methods: Data from multiple EHR systems used by major health systems covering >90% of the population in a metropolitan urban area were extracted and linked using a health information exchange (HIE) network for individuals who had at least two clinical encounters within the HIE network over a 3-year period. Population health indicators of highest interest to public health stakeholders were calculated and visualized at varying levels of geographic granularity. Results: Ten population health indicators were calculated, visualized, and shared with public health partners. Indicators ranged from the prevalence of a disease to the proportion of individuals with poor maintenance of their chronic condition. Calculating rates at the census-tract level or larger (e.g., average population size > 4000 people) is preferable to smaller geographic units of analysis. Implications: Extraction and linking of EHR system data are feasible for public health via an HIE network. While indicators can be derived, biases exist in the data that require more study. Further, HIE networks do not yet possess data for all conditions and measures desired by local public health stakeholders. The data that can be extracted, however, can be combined with public datasets on social determinants
Unequal access: Tobacco Retail in the Indianapolis Metro Area
(The Polis Center, Indiana University at Indianapolis, 2017-07) Comer, Karen; Davila, Kelly; Hollon, Deb; Nowlin, Matt
Retail access to various smoking products is an important consideration when discussing community action to improve a community’s health. Studies show that tobacco outlet density and proximity are linked to tobacco use–particularly in poor areas. We used socioeconomic data culled from the SAVI community information system to examine the density and proximity of tobacco outlets relative to vulnerable communities in Marion County. The report serves as a companion piece to the IU Richard M. Fairbanks School of Public Health’s September 2016 Report on the Tobacco Epidemic in Marion County and Indiana.

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