1. Acknowledgements Epidemiologic Query & Mapping System Patrick O’Carroll Clark Johnson Richard Hoskins Cathy O’Connor Sherrilynn Fuller Principal Investigator Public Health System Linkages – Bench to Bedside and Beyond

2. EpiQMS URL http://198.187.0.45/EpiQMS/ Also EPIQMS in www.google.comwww.google.com

3. Components WWW based - high speed access by local health Three user levels (public, practitioner, need-to-know) Rates with statistical measures Charts & graphs, time trends Deals with small numbers (empirical Bayes spatial modeling) Static, dynamic and full GIS mapping Multiple geographies Queries a dynamic database (no or little on-line calculation) Allows central Q&A (software & data & statistical measures) Comprehensive security model Individual id protection (available dimensions) Only aggregated data Tutorials Components

4. Datasets for EpiQMS ABORTIONS 1991-1999 BIRTHS CERTIFICATE 1980-1999 CANCER Registry CENSUS DATA 1980 1990 – 1998 2000 ( state, county, census tract, legislative district, school district, Zip Code, SES cluster zones, climate zones, rural areas) COMMUNICABLE DISEASE 1980-1997 DEATHS 1980-2000 ICD9 – ICD10 HOSPITALIZATIONS 1990 -1999 HOSPITALIZATIONS (EPI FILE) 1990-1999 INFANT DEATHS 1981-1999 STD 1993-1999 TUBERCULOSIS 1992-1999 HIV 1992 – 1999 Health of Washington State Youth Violence Crime, housing Available now In preparation Requested

5. Original and still primary objective: Communicable disease tracking Geographically oriented (maps) Small numbers Ease of use and access Low cost for users Why do this?

6. Objectives Ease of access to public health data by all citizens while paying strict attention to individual privacy. Allow medical practitioners routine access to support assessment and surveillance in local health departments, communities, WA DOH, and public health research. Get people who use public health data to think geographically. Many geographies, some non-standard. Uniformity of epidemiologic measures. Offer on-line instruction in how to use and intrepret public health data. Software burden is on DOH not users. Allow down loading of information – tables, charts, maps.

7. Diagram DOH databases PreProcessing SAS EpiQMS database EpiQMS: Data Server Population data Static Maps Aggregated data EpiQMS Internet Engine Dynamic mapping engine Web server Data formating Full GIS SAS preprosessing Geocoded data WWW users citizen userspractitioners need-to-know How it works … No identifiers ! DOH:Secure Data Server SQL server

8. Indexing - primary key Disease Race Age Year Geography Sex No Yes No OOXOX15 Generates Index: 15XOXOO Aggregating events by: Breast cancer Yes

9. Cancer Registry security model level I

10. Concurrent dimensions security model level II

11. Who decides which users get various levels of access? Data “owners” Not EpiQMS team Tools to help data owners decide: Probability studies Count suppression

12. Thematic Maps Trivial pursuit word: choropleth Beginning to think geographically... Map

13. Issues in thematic mapping Different conclusions can be drawn from maps of the same data. Natural break Equal ranges Equal counts

14. MAUP The Modifiable Areal Unit Problem (MAUP) A form of ecological fallacy associated with the aggregation of data into areal units for geographical analysis. There are two effects: Scale effect: The larger the unit of aggregation, the larger, on average, is the correlation between two variables. Aggregation effect: By aggregating data into different blocks, you can get different correlations. 1960 election: +0.44 correlation between rural non-farm voting for Nixon in using Census nine-region division -0. 22 correlation using the Census four-region division.

15. Empirical Bayes estimation Smoothing to reflect confidence of local estimation of risk Prior knowledge of about rates and the observed data are used to develop a prior distribution posterior likelihood prior distribution of data distribution previous data intuition good guess (or even a bad one) the data itself - Empirical Bayes Mean (smoothed rates) std error ( Bayesian confidence intervals ) How to estimate disease rates in “small” areas?

16. Deaths from breast cancer in age 35-44 women No Bayes Bayes Zipcodes Blank areas indicate no deaths Map

17. What does it take to run EpiQMS? User Internet Explorer Internet connection 56k or > Two plug-ins which are easy to deal with. (SVG for maps, ChartFX for charts) DOH SQL server ChartFX – charting software SAS for the prep of data Visual Interdev – standard Internet site development tool. RoboHelp – help system development package http://198.187.0.45/EpiQMS/ Fast!