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Quality Improvement Series Session 9 Baseline Data Windy Stevenson Cindy Ferrell. Today’s Agenda. Recap. Problem: The DCH ambulatory clinic problem lists are incomplete and inaccurate. Problem: Patients with BMI>85%ile do not have obesity or overweight listed on their problem lists.
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Quality Improvement Series Session 9 Baseline Data Windy Stevenson Cindy Ferrell
Recap Problem: The DCH ambulatory clinic problem lists are incomplete and inaccurate. Problem: Patients with BMI>85%ile do not have obesity or overweight listed on their problem lists. 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.
Current status • Future state taking shape • Order set request in EPIC queue- ready for PDSA • Obtaining heights on acute care visits- what state? • EPIC requests for populating problem list from an order and driving PCP appointment generation • Exploration of adding prompt to notes template • Baseline data available (next slides!)
Baseline Data- The process • Residents define inclusion/exclusion criteria • Population, setting, timing • How to define a YES • Windy attempts to accurately describe criteria to non-clinical data guy (Adam) • Adam clarifies request, determines he can’t access BMI calculator • Adambuilds BMI calculator and runs data • Windy validates data by doing chart review • Windy and Adam redefine search criteria • Windy begins data analysis; builds graphs for review • Team validates data (DO IT. Take the time.)
The baseline data • The pull: patients >2yo and <18yo seen by a provider in the gen pedsclinic, adolescent clinic, or Westside clinic (including acute care; excluding healthy lifestyles) from 07-01-10 to 03-31-11 who have a recorded BMI >85%ile, with stratification of those who have any of the identified problems noted on their problem list
The baseline data • 37% overall success (457/1220 patients)
Questions to ponder • Should this count?
Baseline Data, continued >99% Problem List
Questions to ponder • Does age matter (this one is 5yo)?
Questions to ponder • What about the first time you meet a 3yo?
Questions to ponder • How important is the REMOVAL of the problem from the list?
Future State- data • What do we want to know? • Will EPIC (retrospective) reports be sufficient? • When do we want to know it? • Where can we post it? • How can we use it to motivate and maintain?
Measurement • What’s the Hawthorne Effect? • What’s a run chart? • What’s it good for?