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.
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
Biography
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.