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State of the Clinic

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  1. State of the Clinic Northeast August 6, 2013

  2. Introductory comments • My thanks to Lou for presenting 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. Jennifer & The Integrating Public Health Inquiry and Transformation (IPHIT) team

  3. Objectives • Review Northeast Clinic demographics, geo-maps and quality metrics • Look at different ways data can be asked and presented • Explore examples of how to data can inform future investigations and interventions • Share the state of clinic finances • Provide examples of your own individual data

  4. Goals • As you look at this data, formulate your own questions: • What else do you want to know? • What seems to be missing? • What assumptions are we making? • In preparing this presentation, I have inserted black slides followed by my own questions and thoughts as examples of how data can move us to inquiry and, hopefully, ultimately to action.

  5. Our patients • In May 2013 12,075 patients were assigned to a PCP at Northeast clinic. From this we have panel-based data. • From 7/1/12 to 6/30/13 (FY13) • 7,704patients were actually seen at Northeast at least once during this year. From this we have service-based data. • There were 30,650 visits including lab, xray and nurse visits • There were 23,428 visits with NE providers • Thus every patient who had >0 provider visits in FY13 was seen an average of 3 times (23,428/7,704)

  6. This is how it looks: Not NE assigned Service Panel • Panel: patients assigned to a PCP at NE on May 2013 • Service: patients seen at NE during 7/1/12-6/30/13 • Not NE assigned: patients not assigned to a PCP at NE

  7. Panel vs Service vs Visit Data • Which questions are best answered with panel data? • Which questions are best answered with service data? • Which questions are best answered with visit data?

  8. DEMOGRAPHICS The following slides are based on panel-based data unless noted

  9. Gender distribution

  10. Age distribution 65+ Children

  11. Race/ethnicity

  12. Language preference

  13. Includes lab and xray encounters (30650 encounters) • 61% female, 39% male

  14. * Includes lab and xray encounters (30650 encounters)

  15. New RRC requirementsfor resident visits • Ten percent of the FMP patient visits must be with patients less than 10 years of age. • Ten percent of the FMP patient visits must be with patients 60 years of age or more • So what is the visit mix for the NE residents?

  16. Includes only residents’ visits (6389 visits)

  17. Notice how insurance status affects access/utilization data. Payor mix By Panel By Service

  18. Any Thoughts? As youdevelop QI and community medicine projects here at Northeast, start by sifting through the data. Here’s what caught my eye…

  19. Example • Our data shows 14.9% of our patients are black • According to the U.S. census bureau, Blacks make up • 5.4% of the population in Dane County • 6.5% in WI • 13.6% in the U.S. http://quickfacts.census.gov/qfd/states/55/55025.html • Did you know that we are caring for a relatively large percentage of black patients in our clinic relative to their prevalence in our community?

  20. GEO-MAPPING Where are our patients?

  21. Mapping NE patients: To orient you, we have no patients in the lakes

  22. An example of geo-mapping application • We have adopted Lake View Elementary School • We overlaid the census tract data of the Northeast Clinic population ages 5-11 years old with the Lake View Elementary School district map • Then we added data about BMI %ile

  23. This shows most NE obese elementary school-age children don’t live in the Lake View Elementary school district (in light green).

  24. CONDITIONS (Some) Northeast Diagnostic Codes

  25. Chronic diseases at Northeast 7/1/12-6/30/13

  26. And more 7/1/12-6/30/13

  27. Are we interested in the gender mix regarding these conditions? Maybe. But how about: how are we doing compared to Dane County, WI and the nation?

  28. Another look at chronic diseases at Northeast www.countyhealthrankings.org ??? Christina Lightbourn would likely disagree with this. Remember data is limited by what you input. What diagnosis code(s) are we using here? 7/1/12-6/30/13

  29. What intrigues you? We have developed some great interventions around diabetes at Northeast, but look at back pain and opiods…

  30. Chronic diseases at Northeast 7/1/12-6/30/13

  31. And yet another look:panel vs service data 7/1/12-6/30/13

  32. Our chronic pain champions • Carrie Stoltenberg and Ann O’Connor have founded and led our Chronic Controlled Substance Work Group at Northeast. This group • Uses a pain registry • Meets regularly and review our top users • Develops QI tools and protocols such as our CCS contracts

  33. Reflecting upon the data • Pain patients are high utilizers of health services. • Almost twice as many women as men have back pain and chronic opioid use • Group visits (e.g. yoga) for chronic pain patients? • A smoother process for refill of chronic controlled substances? • … What the data shows What ideas do you have?

  34. QUALITY INDICATORS Some data you can access immediately from your EPIC dashboard

  35. Examples of clinical metrics that you can find on your dashboard on the clinic level and on a provider level

  36. Examples of scheduling (access) and Avatar (patient satisfaction) metrics Looks like we need to work on access issues.

  37. Data Handouts… • Clinic level data • Avatar % top box • Diabetes registry performance • Immunizations • Pay for performance

  38. Although these metrics are important to track and work on, there are others you could search out.

  39. Keep health disparities in the forefront It’s in the data

  40. PHOTO BY UCI DIGITAL COLLECTIONS “Of all the forms on inequality, injustice in health care is the most shocking and inhumane.” Rev. Martin Luther King, Jr

  41. An example Asthma

  42. Asthma • UWMF has no quality incentives to encourage the health care community to focus upon asthma parameters But consider the following slides (and remember about 1 in 6 patients at NE are black):

  43. Being non-white in WI with asthma Adult Asthma Prevalence, 2008 Child Asthma Prevalence, 2008 http://www.cdc.gov/asthma/stateprofiles/Asthma_in_WI.pdf

  44. Age-adjusted asthma mortality by race, 2007 http://www.cdc.gov/asthma/stateprofiles/Asthma_in_WI.pdf

  45. Chronic diseases at Northeast 7/1/12-6/30/13

  46. At NE, 1122 patients have asthma

  47. The % afflicted with asthma within each racial/ethnic grouping

  48. Where are they? A geo-mapping example: Northeast African American patients

  49. Another layer: African American+ Age (0-17 years) + Asthma They’re mostly in our backyard.

  50. Is there a future project in the data? • This is an example of the kind of data that you can request of our DFM data warehouse from which could stem future projects • Jennifer Edgoose can help you focus your question to request data from Wen-Jan Tuan, database administrator, at the DFM