Chicago Health Atlas - Context, Current Status, and Future Work
Chicago Health AtlasContext, current status, and future workApril 30, 2013Roderick (Eric) Jones, MPHChicago Department of Public Health
Session Preview• What is the Chicago Health Atlas?• Background:Contextual factors that play a role in thecollaboration• Current work:Getting started, developing matching algorithms,minimizing reidentification risk• Challenges and lessons learned:Deriving meaning and delivering it to people whocan use it
Chicago Health Atlas is a . . .collaboration• Informatics researchers from multiplehealthcare institutions• Chicago Regional Extension Center(CHITREC)• Chicago Community Trust• Chicago Department of Public Health
Chicago Health Atlas is a . . .database• De-identified electronic health recorddata for ~1 million Chicagoans• In-patient and out-patient visits spanning2006-2011• Individual patient records matchedacross institutions
• Public policy and legislation (n=56)• Health education and awareness (n=45)• Interventions and programs (n=92)Healthy Chicago sets goals for. . .
HEALTHY CHICAGOChicago Department of Public HealthInfrastructure
HighlightsInfrastructure• Establish an Office of Epidemiology andPublic Health Informatics• Expand epidemiology capacity through anincrease in staff and the development ofstrategic partnerships with other entities whouse or collect public health data
NYC MacroscopeScientific Advisory Group• New York City has embarked on a study tovalidate population health estimates from itsPrimary Care Information Project• CDPH involvement has lead to collaborationon developing vision and methodology formore widespread use of EHR data for publichealth
HighlightsInfrastructure• Increase theavailability ofpublic health datathrough the Cityof Chicagowebsite
Even if we don’t have a matureHIE or a Regenstrief Institute,is it possible to . . .• Leverage existing EHR data,• Weave together data from multipleinstitutions with publicly available data,• Measure disease burden and care delivered?
Process – getting started• Coordinated IRB approval across multipleinstitutions• Limited to structured data, no free text• Constrained to adults aged 18-89• Focus on 606xx zip codes, with knownoverlapping care institutions and highpopulation density
Data Dictionary• Standardized specifications for dataextractions from participating sites–Demographics–Vital signs–Encounter type–Diagnoses–Medications–Laboratory tests
MethodsPatient de-identification andmatching across sites
How we “Hashed” our DataOne-way hash algorithms take in identifiers and produce a fixed-size outputcalled a hash value or “message digest”John O’Dwyer 6/12/1970 M 987654329 20802322ED366A1EFD562A6219C4D7AF993BADADJava application is run on institution side of firewall,creates 5 hash IDs depending on availability of last name, first name,date of birth, gender, Social security number.X:DataInstitution A patients
Two ways to de-identify information(1) the removal of individual, familial,household, employer identifiers(2) a formal determination by a qualifiedstatistician . . .Ensuring privacy andminimizing risk of re-identification23
Determine through “generally acceptedstatistical and scientific principles andmethods, that the risk is very smallthat the information could be used,alone or in combination with otherreasonably available information, bythe anticipated recipient to identify thesubject of the information.”. . .Formal Determination(abridged)24
Assessment of records thatare unique . . .. . . with respect to age, sex,race-ethnicity, and ZIP Codeof residence
FindingsA promising source of prevalence estimates
Data contribution summary,April 20131 2 3 4 5 6Demographics C C C C C PCDiagnoses C C C C C PCVisit type C C C C C PCBMI, BP C PP N N N PCGlucose, HbA1c C C C N N PCMedications C C C N N PCInstitutionData TypeC: complete; N: not yet incorporated;PP: partial time period; PC: partial cohort
Sample size/cohort comparison,by residential ZIP code,BRFSS* vs. Chicago Health AtlasSource Min Median Mean MaxIL BRFSS, Chicago2011 respondents 4 15 16 33Chicago HealthAtlas, patient with2010 visit1,339 10,031 9,270 21,289*CDC Behavioral Risk Factor Surveillance System survey, Chicagosub-sample from Illinois dataset.
Percent=# of patients with > 1 diabetes mellitus diagnosis code# of patients with visit in 2006-2010Diabetes prevalence estimateby residential ZIP
Finding type 2 diabetesin the health record• Diagnosis codes• Labs• Medications• Number of visits Yes, patient has type 2 diabetesNo, patient does nothave type 2 diabetes
Minimum number of visits recordedPercentPercent of Atlas patients withdiabetes diagnosis in 2006-2010Illinois BRFSS estimates the prevalence of diabetes in Chicago at 9-11%.
ChallengeApplying estimates to Chicago– rather than patient – populations
Age groupsPercentAge distribution comparison, 2010
Race-ethnicity comparisonGroupPercentAtlasof total2010 CensusNon-Hispanic black 31 32Non-Hispanic white 20 32Hispanic 14 29Non-Hispanic Asian 4 5Not given/Unknown 31 0
Percent=# of patients with visit in 20102010 Census populationGeographic coverageby residential ZIPAdditional text
Making data available for useTo participating institutions–Piloting query systemTo public–Chicago Health Atlas website
Website work has involved• Identifying health-related data frompotential partners• Evaluating need for data-sharingagreements• Securing and importing the data• Developing procedures and bestpractices for ongoing integration of data
Developing procedures andbest practices• Public health indicators from City Data Portalcan be viewed for temporal and neighborhoodtrends• Incorporating CDC guidelines for classificationof map categories• How to make metadata easily accessible tousers• How to deal with aggregated geographies andtime periods
Chicago Health Atlas Funders• Otho S.A. Sprague Institute• Northwestern Memorial HospitalCommunity Engagement
Health Atlas Research Team• Northwestern University: Abel Kho, John Cashy, AnnaRoberts, Sara Lake• Univ. of Illinois-Chicago: Bill Galanter, John Lazaro• Cook County Hospital System: Bala Hota, Amanda Grasso• Univ. of Chicago Medical Center: Chris Lyttle, Ben Vekhter,David Meltzer• Alliance of Chicago: Erin Kaleba, Fred Rachman, JermaineDellahousaye• Rush University Medical Center: Shannon Sims, Aaron Tabor• Vanderbilt University: Brad Malin• UIC Intern team: Ariadna Garcia, Pravin Babu Karuppaiah,Shazia Sathar, Ulas Keles (Sid Battacharya, Faculty mentor)