1. 1 Resident QI Curriculum, version 2.0 Windy Stevenson, MD Medical Director, Doernbecher Quality Program

2. 2 How has quality evolved? 1800’s: Quality Assurance- credentialing, accreditation Did the dog get fed? Who forgot to feed the dog? 1900’s (mid): Statistical Quality Control & CQI- variations, profiling How many times a week do we forget? Who’s the worst offender? 1900’s(late) : Outcomes analysis- systems thinking, patient focused Is the dog maintaining a healthy weight? Is Beech right for the job? Can we make it easy for Beech to feed the dog? Is the dog being fed the cat’s food? 2000’s: Rise of Big Management If we post our results to the whole neighborhood, will the dog get fed more often? Last 5 years: Quality Cacophony- seeking the sweet spot of transparency, efficiency, outcomes, and patient centeredness Does data demonstrate that we transparently, accountably, efficiently, effectively, safely, timely, equitably provide canine sustenance in a dog-friendly way? Today: Cacophony with a mandate- The whole concept of pet ownership is at stake, here, Beech! Concepts courtesy Donald Fetterolf, President of the American College of Medical Quality

3. 3 Where is that sweet spot? Healthcare is a business, but taking care of a patient is not. -Victor Traztek, Mayo Clinic Scottsdale

4. 4

5. 5 Learning about donkeys (and carts)

6. 6 My donkey is pathetic! 15 kg

7. 7 Your first PDSA cycle 15 kg

8. 8 My wagon doesn’t have a back stop!

9. 9 My donkey is up in the air!  Is that really our problem? What OUTCOME matters?  What causes have we not yet explored?

10. 10  You don’t have to study other people’s wagons unless you intend them to use your modification(s)  Get enough data to take the next step  ASK WHY  Beware of random folks walking up asking you to design donkey weights or backstops for wooden carts

11. 11 Systems Every system is perfectly designed to achieve the results it gets.

12. 12 Where do you start? Project Selection...  Do we have a problem? What is our problem?  Will fixing our problem improve quality? –IOM Dimensions- Safety, Timeliness, Equity, Efficiency, Effectiveness, Patient Centeredness  Is the outcome important? Why do we care? Why? Why? –To providers? To patients or families?  Are we likely to be able to overcome foreseeable barriers?  Is the project meant to improve an observable process?  Is it within our scope to make this change?  Is this reasonable? Is it focused enough to make success likely in our timeframe?  Does the cost of effort seem to be in good balance with likelihood of returns?  Are people already passionate or curious?

13. 13 Where do you start? You already do this every day! There is no such thing as being too focused.

14. 14 Ambulatory problem lists are incomplete and inaccurate So, let’s start fixing them! How do we define success? Failed attempt to measure “completeness” What kids do we start with? Diagnosis Based? All patients with asthma All obese patients All patients seen by genetics All former preemies Age Based? Start with all newborns Target a certain WCC Exclusion based? (The Sarah Green effect) Should we focus on the kids who are normal?? Other ideas? Who owns the list? What is it even for?

15. 15 What are we even trying to accomplish? Provide Safer Care Save time Populate the problem list in an efficient way that will support/drive good patient care Populate the problem list of obese children to efficiently drive good patient outcomes Why obesity? What practice settings? What ages? Residents? Attendings? All? How good do we want to be?

16. 16 Our AIM  >95% of patients >2yo seen by a provider in the gen peds clinic or Westside clinic (including acute care; excluding healthy lifestyles) who have a BMI >85%ile will have “BMI; category” listed on their problem list

17. 17 Is our Aim Statement SMART?  Specific we chose ONE thing  Measurable we can prove we’ve impacted it  Actionable there are no known insurmountable barriers  Realistic it’s within our scope  Timely we’ll do it within a time frame Aim: >95% of patients >2yo seen by a provider in the gen peds clinic or Westside clinic (including acute care; excluding healthy lifestyles) who have a BMI >85%ile will have “BMI; category” listed on their problem list

18. 18 WHY? The Doernbecher Purpose…

19. 19 Measurement We MEASURE! Outcomes measures Process measures Balancing measures When we try to improve a system we do not need perfect inference about a pre- existing hypothesis: we do not need randomization, power calculations, and large samples. We need just enough information to take a next step in learning. – Donald Berwick AIM: >95% of patients >2yo seen by a provider in the gen peds clinic or Westside clinic (including acute care; excluding healthy lifestyles) who have a BMI >85%ile will have “BMI; category” listed on their problem list

20. 20 Measurement AIM: Outcomes measures: Are we getting there? Process measures Are we doing the right things to get there? Balancing measures Are we messing things up by getting there? On time delivery % populated #packages Resident time spent Donkey lifespan Clinic delays MEASURES : Not everything that can be counted counts, and not everything that counts can be counted. Albert Einstein, US (German-born) physicist (1879 - 1955) >95% of patients >2yo seen by a provider in the gen peds clinic or Westside clinic (including acute care; excluding healthy lifestyles) who have a BMI >85%ile will have “BMI; category” listed on their problem list

21. 21 The baseline data  37% overall success (457/1220 patients)

22. 22 Age and BMI

23. 23 Testing MEASURES: % problem lists populated TEST: AIM: REMEMBER: Populate your problem lists! >95% of patients >2yo seen by a provider in the gen peds clinic or Westside clinic (including acute care; excluding healthy lifestyles) who have a BMI >85%ile will have “BMI; category” listed on their problem list

24. 24 Testing

25. 25 Testing MEASURES: % problem lists populated TEST: Poster TEST: Use BPA and Smartset to drive care TEST: ??? AIM: >95% of patients >2yo seen by a provider in the gen peds clinic or Westside clinic (including acute care; excluding healthy lifestyles) who have a BMI >85%ile will have “BMI; category” listed on their problem list

26. 26 Current status  Future state taking shape  Smart set in EPIC- PDSAs underway  Obtaining heights on acute care visits  Ongoing data pull being finalized  EPIC requests for populating problem list from an order and driving PCP appointment generation Pt >2yo checked in and ht/wt recorded EPIC uses ht and wt to generate BMI and flags if >85%ile Provider sees banner under Quality issues and clicks associated smart set Acute care visit- problem added; follow up appt made with PCP Family stops at desk to get appt WCC- provider adds problem; uses smart set to guide care

27. 27 Next steps  Final adjustments to the EPIC product  Flip the switch  Start measuring and reporting

28. 28 Using Six Sigma and Lean methodologies, I will invoke Deming and Shewart’s approaches while conducting a Kaizen event to reduce the muda through process mapping, aggregate patient-level data, and reliability analysis to create a standardized deliverable. Be as smart as you can, but remember that it is always better to be wise than to be smart - Alan AldaAlan Alda Be as smart as you can, but remember that it is always better to be wise than to be smart - Alan AldaAlan Alda I know a way to make this system work better tomorrow.

29. 29 Take Home Points Real (sustainable) change comes from changing systems, not changing within systems Understand the problem before you hypothesize the causes Be specific about what you want to accomplish, and why Focus on patients Start before you think you are ready Don’t get paralyzed by lack of research-level data or by how much there is to do

30. 30 What if you want to know more?  IHI Open School –http://ihi.org/IHI/Programs/IHIOpenSchool/WhatstheIH IOpenSchool.htmhttp://ihi.org/IHI/Programs/IHIOpenSchool/WhatstheIH IOpenSchool.htm  Call me, page me, email me –4-1321 –15763 –lammersw@ohsu.edu