Instructions to cook up the Baker’s Dozen

1. Instructions to cook up the Baker’s Dozen Made Fresh Daily Kelly Friar, Chief, Office of Health and Vital Statistics and Accreditation Coordinator Ohio Department of Health

2. Significance for Public Health • Public Health Accreditation Board • PHAB • Community Health Assessment • Community Health Improvement Plan • Dept. Strategic Plan • Quality Improvement Plan • Workforce Development Plan • Performance Management System

3. 2012 Vision Awards Achieving Excellence in Public Health Through Innovation Category A – Programs with a budget of greater than $250,000 First Place Ohio Department of Health Ohio Perinatal Quality Collaborative (OPQC) The Ohio Perinatal Collaboration to Improve Birth Data and Prematurity Outcomes is a creative approach to using public health surveillance data (birth certificates) as a supplement to data collected from medical records to serve as the metrics that can inform and accelerate perinatal quality improvement initiatives. The Ohio Perinatal Quality Collaborative (OPQC), Ohio’s public/private partnership focused on improving health outcomes using quality improvement science, has documented early successes in reducing late preterm scheduled deliveries without medical indication in 20 delivery hospitals in Ohio. Spreading what works will be essential in reducing prematurity and having a measurable impact on population health. This effort is state administered by investing and partnering in OPQC where the improvement happens. Over many decades Ohio has relied heavily on birth certificates as source of data to measure population-level changes over time, but only recently has turned to them to measure improvements in health care and outcomes.

4. The Baker’s DozenTop Key Variables in IPHIS

5. Why Are We Doing This? • OPQC’s Mission: Improve Infant Health • Through collaborative use of improvement science methods, reduce preterm births and improve outcomes of preterm newborns in Ohio as soon as possible • What Causes Perinatal & Infant Mortality? • Preterm Birth • Birth Defects • SUID et al

6. Our Shared Vision • Decrease prematurity and infant mortality in Ohio • OPQC, ODH-Vital Statistics and OHA • Using the PLAN-DO-STUDY-ACT cycle of continuous quality improvement to facilitate improved data collection to accurately measure progress toward goal of reducing non-medically indicated deliveries prior to 39 weeks gestation

7. Bill Callaghan, MD MPHCenters for Disease Control and PreventionDecember 1, 2011 “The focus of healthcare for women and infants over the next century depends on the quality of the data collected by those who fill out the birth certificates.”

8. Obstetric Quality 2007 “ There are currently no uniformly accepted measures of obstetrical quality. Many traditional measures of obstetrical quality are flawed and newer measures are still undergoing necessary validation.” - Jennifer L. Bailit, MD, MPH OBG Survey 2007

9. OB Quality Monitoring • National Quality Foundation • Joint Commission • Ohio Hospital Compare • Leap Frog • CMS • Ohio Perinatal Quality Collaborative • PCPI • PQRS

10. JOINT COMMISION: Perinatal Care Measures • PC-01 Elective Delivery • PC-02 Cesarean Section (NTSV) • PC-03 Antenatal Steroids • PC-04 Health Care-Associated Bloodstream Infections in Newborns • PC-05 Exclusive Breast Milk Feeding https://manual.jointcommission.org/releases/TJC2013A/PerinatalCare.html

11. PC -01 • Numerator: Patients with elective deliveries • Denominator: Patients delivering newborns with >= 37 and < 39 weeks of gestation completed • Inductions and cesarean delivery included

12. JOINT COMMISION: New for July 1, 2013 “It is acceptable to use data derived from vital records reports received from state or local departments of public health if they are available and are directly derived from the medical record with a process in place to confirm their accuracy. If this is the case, these may be used in lieu of the acceptable data sources listed below.” https://manual.jointcommission.org/releases/TJC2013B/DataElem0265.html

13. <39 Week Scheduled Delivery – 20 Charter Hospitals UH Case MacDonald Women’s Promedica Toledo Hospital Mercy St. Vincent Medical Center Fairview Hospital Metro Health Hillcrest St. Elizabeth Health Center Akron Children’s MFM Akron General Summa Health System Aultman Hospital Mt. Carmel St. Ann’s Mt. Carmel East Mt. Carmel West Miami Valley Hospital OSU Wexner Riverside Methodist Mercy Anderson UH Cincinnati Good Samaritan

14. BC Data Varies By: • Hospital • Maternal Dis • Credentials • State

15. Effects of the Initial OPQC39 Week Scheduled Birth ProjectSeptember 2008  March 2013 • 30,000 births shifted to 39-41 weeks • Conservative estimate = 3% fewer “near term” NICU admissions: N = 950 • 950 x $20,000 per NICU Admission = • $19,000,000 savings in 4 ½ years

16. Lessons From the Initial 39 Week Project • Create A Culture of Change • Learn From All Participants • Improve Communication • Data Collectors, Data Users, Data Analysts • OPQC = Data for You to Use, Not the Police • Birth Certificate = A Q.I. Instrument • More Training and More Cross Talk • Use  Greater Accuracy  Promotes Use • Rapid Turnaround Essential

17. <39 Week Scheduled Delivery and Birth Certificate Accuracy 15 Pilot Hospitals Ashtabula County Bay Park Promedica Lake East Mercy Regional Lorain Blanchard Valley Mercy Canton St. Rita’s Lima Southview Good Samaritan Dayton Kettering Genesis Bethesda Fairfield Lancaster The Christ Hospital Southern Ohio Medical Center Bethesda North

18. Team Sharing and Learning Harvard School of Education http://socrativegarden.wordpress.com/2011/08/04/1-2-3-word-cloud/

19. Two reasons for inaccurate gestational age entry 1. Sometimes the gestational age is “rounded up” in IPHIS. • Gestational age is NEVER TO BE ROUNDED UP; it is recorded in completed weeks. • For example, 38 weeks, and 5 days is properly termed 38 weeks. 2. Often there is no agreement re: where in the medical record gestational age should be recorded; in addition, varying gestational ages are found in the medical record. • Consistent agreement regarding where in the medical record the IPHIS variable for gestational age is found willgreatly increase your accuracy.

20. Remaining 73 Ohio Maternity Hospitals • January 2013 thru April 2014 • Divided into three separate “Waves” with staggered start dates Differences from Charter and Pilot Sites • Updated the report of allowed medical indications from Birth Registry/IPHIS data • *Change in measure from 36.0 - 38.6 weeks to 37.0-38.6 weeksgestation; more in harmony with Joint Commission, Leap Frog and Ohio Hospital Care

24. Can You Do This In Your Hospital ?What Are The Keys to Success? • Adopt ACOG Guidelines • Use a Scheduled Birth Form (ACOG or Site Specific) • Document the Pregnancy Dating Method • Document the Reasons for Scheduled Birth • OPQC Is Not The Police = Start with Soft Stop • Rapid Data Turnaround • Frequent Group & Site PDSA’s • Enthusiasm from Local Leaders

26. PDSA • Plan • Look at a particular aspect of project • Review intervention options • Plan implementation of intervention • What do you predict will happen? • Do • Execute the intervention

27. PDSA • Study • How did the intervention go? • Did it go the way you expected? • What was the outcome? • Was the a measure? • Act • Accept • Adopt • Abandon

28. 13 Key IPHIS Variables Handout

29. Is there any way to get gestational age correctly recorded in IPHIS all the time?

30. Essential Data Elements to Accurately Document Gestational Age Earliest Ultrasound that documented GA Ideal CRL Best < 20 weeks gestation documentation by provider estimate of GA what it is based on

31. Second Step-entering Data into IPHIS Make sure everyone agrees where to find best OB estimate of GA and EDD • acquisition of data • Recording of data • Transfer of data • Monitoring of process

32. IPHIS to Patient Medical Record Checklist Directions, Data Dictionary, and Examples Photo courtesy of fotolia.com

33. IPHIS to Patient Medical Record ChecklistHospital: ____________________ Month: ____________

34. Step 1Analyze results and dig deeper Is there any difference among data suppliers, documentation, data collectors? What data do you want to work on ?

35. Fishbone Diagram: Design Policies People Primary Cause Cause of Primary Cause ProblemStatement Procedures Place

36. Fishbone Diagrams: Tips • Use Fishbone Diagram on an on-going basis • Identify contributing factors to each cause • Dig deeply into the causes of the causes • May do multiple diagrams to get at the root cause • Use data to verify – what is causing the most or worst error of error? • Don’t jump to solutions!

37. Reviewed 10 charts: information in chart, on the ODH facility worksheet and in IPHIS. Discovered: Missing/incorrect data in numerous IPHIS fields. Plan: Change the way data is collected and review data prior to entering in to IPHIS. What We Are Doing

38. Scheduled Delivery Form • One Page Inclusive: Facilitates information from admitting physician. • Variables from IPHIS that are medical indications for elective delivery <39 weeks. • Faxed to Maternity Dept. • Reviewed by RN prior to scheduling mother for elective delivery.

39. Step 2. Experiment with a solution: improve a specific problem with a specific solution • Pilot • Run • Audit

40. UCL Sigma= Checksheets LCL Sigma= CCR X X Gap Step 3: Display Results Data

41. Hover Function

42. Modules • Why is the birth certificate important to the healthcare of women and newborn infants? Use of the birth certificate as a QI tool is discussed in detail in this Module. • What are the variables in the Ohio birth certificate and what do they mean? The importance of obtaining the correct gestational age is highlighted as well as the “Bakers Dozen of the Most Important Variables,” with appropriate definitions for each. • Where are select birth certificate variables found in the medical record? Select variables are highlighted as well as the need for collaboration between the clinical and data abstraction teams. • How can I know if I have accurately entered data into IPHIS? This is the most technical of all the Modules, providing an overview of the IPHIS software and the data checks within it. A suggested quality review of hospital’s submissions is also covered. • How can I Improve the data entry processes at my hospital? This Module reviews the Model for Improvement, AIM statements, & PDSA’s.

43. Keys to Success • Communication • Don’t assume • Consensus and key personnel buy-in • Grit and determination • Monitoring of efforts (DATA)