UW MED – PHINEXUniversity of Wisconsin Medical Record–

Public Health Information Exchange

Wisconsin’s Clinical EMR – Public Health Data Exchange Pilot

Theresa Guilbert, MD, MSProject PI

University of Wisconsin-MadisonDepartment of Pediatrics

tguilbert@wisc.edu

Why study chronic disease risk factors present in the environment &

community?

Multi-Level Approach

• A multilevel approach that includes an ecological viewpoint may help to explain heterogeneities in chronic disease expression across socioeconomic behavioral, and geographic boundaries that remain largely unexplained

• Improved knowledge regarding disease disparity is important in order to develop intervention strategies

Overall Hypothesis

• Data exchange between UW Dept Family Medicine (DFM) clinics and the Wisconsin State Division of Public Health (DPH) and subsequent linking of these data to public databases on geographical, environmental, socioeconomic, and demographic profiles will highlight areas of disparity and discover novel chronic and communicable disease risk factors

Rationale

• By having such a large clinical data set and using sophisticated spatial and multivariate modeling and data mining tools, areas of healthcare disparities will be highlighted

• New information about risk factors will be discovered to guide:– Clinical care– Inform clinical quality improvement– Design public health interventions– Facilitate further research

Specific Aims• Establish a health information exchange between

DFM clinics the DPH using a HIPAA privacy rule compliant limited data set– All Personal Health Identifiers are removed except for

gender, ethnicity/race, birth year/month, dates of service, zip code, and census block group

– This approach has been proved by the UW IRB

• Determine areas and populations of chronic and communicable disparity through collaboration with the UW Applied Population Laboratory (APL)

Specific Aims• GIS and spatial analyses of population trends to

chart areas of disparity and geographic characteristics of those communities that can lead to hypotheses regarding etiology

• Assess novel environmental and community risk factors by matching CBG coded EHR to its community level demographic and socioeconomic characteristics using data bases available through the APL and DPH.

Specific Aims• Use multivariate (logistic and Poisson regression,

fixed and random effects regression modeling) and data mining techniques at DPH to create predication models that specify risk factors associated with asthma among many environmental and community based factors from the census and commercial databases

• Using statistical clustering techniques analyze and determine prominent within patient disease co-morbidity groupings and determine the individual and community risk predictors of these clusters

Specific Aims• DPH operates the Public Health Information Network

(PHIN), a secure, web based system: – Advanced statistical and GIS modeling services– SAS Business Intelligence Server/Enterprise Miner– ESRI ArcGIS server

• Available community level databases include:– Census Demographic– Tapestry Segmentation– Consumer Spending– Business Summary and Location– Retail Market Place

Multi-Level Modeling and Data Mining of Disease Risk, Disparity, and Health Outcome Quality

Outcomes = Patient Clinician Clinic Community

Factors + Factors + Factors + Factors

Asthma Age Age Location Census Block Group:

Diabetes Gender Gender Capabilities Poverty

CVD / CHF Race/ethnicity Certifications Processes Education level

Immunizations Co-morbidities Graduation   Built environment:

Obesity Medications date   Traffic

Hypertension Education Years of practice   Recreation / parks

Smoking Literacy   Safety / crime

Alcohol Language     Psycho-demographics

A1c level Insurance     Restaurant mix

LDL Urban / Rural     Fast food sales

HDL Census Block Group     Fresh fruit & vegetable sales / consumption

BP        

Hospitalizations       Public Health Program Information

Health Care -Process factors

       

(e.g, time to repeat follow-up)

       

Electronic Health Record & Hospitalization Data Census / ESRI BA Data

Data Sets

• Public Health – Behavioral Risk Factor Surveillance System 2004-2009

• Clinical – UW Family Medicine & UW Hospitals and Clinics (demographics, diagnoses, problem lists, laboratory test results, vital signs, procedures, medication lists)

• Community Data – ESRI geo-coded data (CBG)

ESRI Data Bases Fresh Fruit & Vegetable Consumption Index

Milwaukee & Suburbs – Census Tracts

Color Ramp

Grey –Lowest

White-Low

Cream-Medium

Yellow-High

Red-Very High

Source:

ESRI / BLS Consumer Expenditure Survey

Fresh Fruit & Vegetable Consumption IndexWith Individual Store Location / Sales Volume

Milwaukee & Suburbs – Census Tracts

Color Ramp Grey –LowestWhite-LowCream-Medium Yellow-HighRed-Very High

Circle size = store sales volume

Source:ESRI / BLS Consumer Expenditure Survey

Disparity in Dane County?• ~50% of K-12 students in Madison schools are

economically disadvantaged (> 70% in some)• 50% of the kids in the Madison Metropolitan School

District are of racial/ethnic minority groups (poor access to care)

• Disparity does not always correlate with poverty– Falk Elementary School (West Madison) has 9% children

with asthma and a 65% poverty rate with 70% minorities – Mendota Elementary School (North Madison) has 22%

children with asthma and a 70% poverty rate with 74% minorities

Collaborative Effort

• Brian Arndt-UW DFM• Bill Buckingham-UW APL• Tim Chang-UW Biostats• Dan Davenport-UW Health• Kristin Gallager-UW Pop

Health• Theresa Guilbert (PI)-UW

Peds • Larry Hanrahan-DPH

• David Page-UW Biostats• Mary Beth Plane-UW DFM• David Simmons-UW DFM• Aman Tandias-DPH• Jon Temte-UW DFM• Kevin Thao-UW DFM• Carrie Tomasallo-DPH

What have we learned so far?

Presenters• Brian Arndt MD-UW Family Medicine

UW MED- PHINEX Diabetes & Obesity Use Case Clinician Lead

Estimating the Prevalence of Diabetes in Wisconsin

• Kevin Thao-UW Family MedicineThe Prevalence of Type 2 Diabetes Mellitus in a

Wisconsin Hmong Patient Population

Presenters• Carrie Tomasallo, PhD, MPH-Wisconsin

Division of Public Health Wisconsin Asthma Program

Estimating Wisconsin Asthma Prevalence Using Clinical Electronic Health Records and Public Health

Data