Smart Use of State Public Health Data for Health Disparity Assessment

Health services are often fragmented along organizational lines with limited communication among the public health–related programs or organizations, such as mental health, social services, and public health services. This can result in disjointed decision making without necessary data and knowledge, organizational fragmentation, and disparate knowledge development across the full array of public health needs. When new questions or challenges arise that require collaboration, individual public health practitioners (e.g., surveillance specialists and epidemiologists) often do not have the time and energy to spend on them. Smart Use of State Public Health Data for Health Disparity Assessment promotes data integration to aid crosscutting program collaboration. It explains how to maximize the use of various datasets from state health departments for assessing health disparity and for disease prevention. The authors offer practical advice on state public health data use, their strengths and weaknesses, data management insight, and lessons learned. They propose a bottom-up approach for building an integrated public health data warehouse that includes localized public health data. The book is divided into three sections: Section I has seven chapters devoted to knowledge and skill preparations for recognizing disparity issues and integrating and analyzing local public health data. Section II provides a systematic surveillance effort by linking census tract poverty to other health disparity dimensions. Section III provides in-depth studies related to Sections I and II. All data used in the book have been geocoded to the census tract level, making it possible to go more local, even down to the neighborhood level.

Table of Contents:
Enhanced Public Health Program Collaboration through Data Integration Introduction Data Integration at the National and State Levels Infrastructure Approach to Data Integration Chapter Highlights References Common Population-Based Health Disparity Dimensions Introduction Race and Ethnicity Gender Socioeconomic Status Other Dimensions of Health Disparities Chapter Summary References Common Public Health Data in a State Health Department Introduction Hospital Discharge Data Nebraska Cancer Registry Data Crash Outcome Data Evaluation System NTR Data Traumatic Brain and Spinal Cord Injury Registry Nebraska Parkinson’s Disease Registry Nebraska State Immunization Information System Emergency Medical Services Enhanced HIV/AIDS Reporting System Nebraska Emergency Room Syndromic Surveillance Behavioral Risk Factor Surveillance System Vital Records Birth Defect Registry National Electronic Disease Surveillance System Nebraska Newborn Screening Pregnancy Risk Assessment Monitoring System Nebraska Adult Tobacco Survey and Social Climate Survey Nebraska WIC Program Pregnancy Nutrition Surveillance System Pediatric Nutrition Surveillance System Youth Risk Behavior Survey Nebraska Youth Tobacco Survey Nebraska Risk and Protective Factor Student Survey References Data Linkage to Gain Additional Information Introduction Data Linkage Essentials Case Study: A Complete Linkage Process Other Issues in Record Linkage Chapter Summary References Indexing Multiple Datasets: A Bottom-Up Approach to Data Warehousing Introduction Top-Down and Bottom-Up Approaches to Data Integration Piloting Bottom-Up Process to Gain Experience Developing an Agency-Wide Strategy for MPI for Data Integration Chapter Summary References Using GIS for Data Integration and Surveillance Introduction Geocoding-Related Measures in Spatial Analysis Geocoding Strategies: Toward a Master Address Index Attaching Census Tract Data to Each Patient Spatial Visualization and Disease Surveillance Chapter Summary References Methodological Preparation for Health Disparity Assessment Introduction Setting the Surveillance Scope Study Design Cross-Sectional Measurements Intertemporal Measurements Chapter Summary Appendix References SES Disparities in Hospitalization Introduction Analytical Approach to Neighborhood SES Disparity Assessments Surveillance Results Concluding Remarks Appendix References Sex Disparities in Hospitalization Introduction Using Hospital Incidence and Prevalence Data to Revisit the Morbidity–Mortality Paradox Using Prevalence Data to Assess Diseases More Common among Females Assessing Hospital Procedure Disparities Assessing Measurement Consistency Chapter Summary References Rural–Urban Disparities in Hospitalization Introduction Our Approach to Model Rural–Urban Difference Rural–Urban Hospitalization Disparity Surveillance Results Case Study: Rural–Urban Injury Surveillance Chapter Summary Appendix References Racial Disparities in Hospitalization Introduction Using Multiple Data Sources to Generate the Race Variable for HDD Patient-Based Assessment for Major Comorbidities Prevalence, Readmission, and Mortality for Major Hospitalizations Case Study: Racial Disparity in Rehabilitation among Elderly AMI Patients Chapter Summary and Concluding Remarks Appendix A: Race Adjustment Strategies Using the 2010 Census Data Appendix B: Companion Tables for Tables 11.2 through 11.4 References Using Emergency Department Data to Conduct Surveillance Introduction Influenza and Population Vulnerability Linking Weather Data to Hospital Data Chapter Summary and Concluding Remarks Appendix References Linking Cancer Registry Data to Hospital Discharge Data Introduction Method Results Chapter Summary References Mother Index and Its Applications Birth Certificate Data Linkage: A Brief Review NMI and Its Applications Using NMI and Geocoded Data to Construct Residential Mobility Information Chapter Summary References Assessing and Managing Geocoding of Cancer Registry Data Introduction Geocoding Assessments Geocoding Workflow Development Other Secured Internet Data Sources for Geocoding Concluding Remarks References Sex Difference in Stroke Mortality Introduction Methods Results Chapter Summary and Discussion Summary References Model Outcomes of Acute Myocardial Infarction (AMI) by Residence and Hospital Locations Introduction Method Results Concluding Remarks References Disparities in Motor Vehicle Crash Injuries: From Race to Neighborhood Introduction Phase I Project: MVC Disparity Based on Police-Reported Injury Severity Phase II Project: Using MAIS for Hospital-Based Surveillance Phase III Project: Georeferencing MAIS-Based Injury Event to Census Tract for SES Analysis Chapter Summary and Concluding Remarks Appendix References Linking Cancer Screening and Cancer Registry Data for Outcome Assessments Introduction Method Results Discussions and Conclusions References Linking Environmental Variables to Parkinson’s Disease Introduction Environmental and Disease Data Processing Cluster Detection and Exposure Comparison Using Case-Control for Exposure Surveillance Conclusion and Discussion Appendix: Results from Satscan Test and Associated Pesticides and Herbicides within and outside of the Cluster References

About the Author :
Ge Lin is a professor of epidemiology in the School of Community Health Sciences, University of Nevada, Las Vegas. He is trained in spatial demography and geographic information systems. He is known for his work in spatial modeling, spatial statistics for count data, and spatial disparities in health. His most recent research focuses on the science of public health data. He uses the infrastructure approach to develop integrated data marts, data analysis utilities, and training modules for public health data specialists. He has been supported by several national and state organizations, including the National Institutes of Health. Ming Qu is administrator of the Epidemiology and Informatics Unit, Nebraska Department of Health and Human Services (NEDHHS), which provides statistical, epidemiological, and geographic information services that support public health actions and policies. He previously was an injury epidemiologist and Crash Outcome Data Evaluation System administrator for the NDHHS, where he was instrumental in the development of the Nebraska Injury Surveillance System. Dr. Qu supervises functions of professionals and disease and injury surveillance, data collection and quality assurance, data analysis and reporting, data system development and evaluation. He is the author of numerous papers and book chapters.