1. Belleville Family Health Center September 5, 2013

2.  Many thanks to Wen-Jan Tuan for assistance with data gathering for this talk  Please complete the required IPHIT participant form for our HRSA grant.  Please complete the evaluation form at the end or email me any feedback you have about this presentation so we can continue to improve upon it. Thanks – Jen and The Integrating Public Health Inquiry and Transformation (IPHIT) team

3.  Review Belleville Clinic demographics, geo- maps and quality metrics  Share the state of clinic finances  Look at different ways in which data can be queried and presented  Explore examples of how to data can inform future investigations and interventions

4.  As you look at this data, formulate your own questions:  How was this data extracted?  Do we think it is accurate?  What else do you want to know?  What seems to be missing?  What assumptions are we making?

5.  As of June 1, 2013 5,633 patients were assigned to a PCP at Belleville clinic and have had some contact with UW Health in the past 3 years. From this we have panel-based data.  From 7/1/12 to 6/30/13 (FY13) 4,633 patients were actually seen at Belleville at least once during this year. From this we have service-based data.

6. Panel: patients assigned to a PCP at BV on June 1 2013 and contact with UW in the past 3 yrs Service: patients seen at BV during 7/1/12-6/30/13 Not BV assigned: patients not assigned to a PCP at BV Panel Service Not Belleville assigned This is how it looks:

7. Which questions are best answered with panel data? Which questions are best answered with visit data?

8.  FY 2013 (July 1, 2012 – June 30 2013): ◦ There were 19,425 visits – includes faculty, residents, nurses, lab and x-ray.

17. Belleville Patients Count of Patients by Census Tract 1,600 1

18.  What do you think our top 5 patient issues are?

19. Condition# of Patients%Patients%Female Obesity1,46930.4%49.4% Hyperlipidemia1,20321.4%46.1% Hypertension1,12319.9%48.5% Depression83014.7%69.9% Smoking77613.8%43.9%

20. Condition# of patients% patients% Female Obesity131831.9%51.1% Hyperlipidemia114624.7%47.6% Hypertension111024%48.7% Opioid71515.4%56.9% Depression65814.2%72.8%

21. Condition # of Patients on panel %Patients in panel # of patients seen in the past year with this diagnosis % of patient visits with this diagnosis Obesity1,46930.4% 131831.9% Hyperlipidemia1,20321.4% 114624.7% Hypertension1,12319.9% 111024% Depression83014.7% 65814.2% Smoking77613.8% 56912.3% Opioid69511% 71515.4% Anxiety Disorder5979.5% 4409.5% Chronic Back Pain5568.8% 47110.2% Asthma4066.4% 3487.5% Osteoarthritis3745.9% 3487.5% Diabetes3496.2% 3627.8%

22.  What are the questions that come to mind for you?  What would you like to know more about?  How could we query this data?

24.  How would you identify our obese patients in Epic? ◦ Problem list? ◦ Billing diagnosis code? ◦ BMI from vital signs?

25.  BMI>=30 as recorded in the vital signs

26.  Any problems with this?

27.  BMI>=30 as recorded in the vital signs  Any problems with this?  No differentiation made for age of the patient  - misleading data for children in this report: under-reporting

28. agesN % of patients in this age range with obesity Odds ratio* *N not large enough for this to be reliable 18-3424325.9%1.0 35-4942841.3%2.05 (1.69-2.49) 50-6448743.3%2.13 (1.76-2.58) 65-7926648.3%2.47 (1.50-4.04) 80+4931.4%1.22 (0.66-2.25)

29. Belleville Obese Patients Count of Patients by Census Tract 200 1

31. 2013“The work we do”“The money we get”“Money/Work” PayorCharges% of ChgsPayments% of PaysCollection % GHC $656,96512%$464,60317%71% Medicaid $455,2279%$118,3524%26% Medicare $1,413,59727%$460,72817%33% Physicians Plus $509,51210%$181,8717%36% Unity $775,98915%$439,37816%57% Workers Comp $29,6051%$24,9381%84% All others & self pay $1,418,85027%$1,009,34637%71% TOTAL $5,259,745100%$2,699,216100%51%