PH+Reporting+User+Story+-+UW+MED+PHINEX

include component="page" wikiName="siframework" page="PHRI Header" =User Story: UW MED - PHINEX -- University of Wisconsin Medical Record - Public Health Information Exchange=

Contact Info:
Lawrence P. Hanrahan PhD MS (lawrence.hanrahan@dhs.wisconsin.gov) -- Director of Public Health Informatics, Chief Epidemiologist, Wisconsin Department of Health Services, Division of Public Health, Office of Health Informatics

Theresa W. Guilbert MD MS (tguilbert@pediatrics.wisc.edu) -- Assistant Professor, UW Department of Pediatrics, University of Wisconsin School of Medicine and Public Health (UW MED-PHINEX PI)

Date Received:
11/18/2011


 * What It Is**: PHINEX links clinical care and public health through electronic medical record (EMR) exchange. It provides advanced, user friendly data analysis tools to mathematically represent the chronic care model. This more completely describes disease risk, disparity, and health care quality determinants at the patient, clinic, health care system, and community level.


 * The Data:** We have 2007-9 data which will be updated through 2012. It covers 25 UW Department of Family Medicine clinics, 192,000 patients, 2.54 million encounters, 3.1 million diagnoses, and 1.58 million laboratory results. The data comply with the HIPAA Privacy Rule for limited data sets. All Protected Health Information (PHI) are removed except that date of encounter is included, zip code, and census block group of the patient’s address is coded. We have IRB approval to expand and include UW pediatrics and internal medicine clinics. Using the census block group, we are able to link ~6,000 community level variables on census characteristics (e.g. education, median income, economic hardship index, social vulnerability index), businesses (e.g. fast food retail density), and consumer behaviors (e.g. fast food consumption, fresh fruit & vegetable consumption, etc.).


 * Analysis Capabilities**: EMR data are sent to the PHIN – the Division of Public Health’s Public Health Information Network. Using SAS Enterprise Miner and ESRI ArcGIS, it provides sophisticated analytic capabilities, including multivariate and mixed model regression, data mining, mapping, and GIS.


 * Health Outcomes of Interest**: We currently are investigating asthma, diabetes, obesity, and influenza. But we are also developing others, such as studying MCH, environmental health, and other chronic disease outcomes.


 * Focus**: Our current emphasis is on the development of data visualization and analysis standards. Because of this, we are not presently receiving this data through an HIE network. UW is on an EPIC network, but we do not have a real-time interface between it an our PHIN Analysis, Visualization, and Reporting (AVR) services. We presently receive the data extract encrypted on a portable media. The capability to receive data from providers through an HIE network is planned for the future after the statewide HIE network infrastructure and state-level HIE services are in place. Instead we have developed initial requirements for univariate, multivariate and mixed-model regression, data mining techniques, and GIS / spatial analyses. Specifications for multivariate asthma and diabetes analyses have been completed. Compared to the BRFSS telephone survey, our results have demonstrated that the EMR data exchange can provide superior surveillance information on non-reportable chronic conditions such as asthma and diabetes.

Supporting Files:

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