Mining an EHR for Quality Data:

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1 Mining an EHR for Quality Data: Practice Culture, Workflow & Technical Issues Bill Jones, Deborah Mielke, M.D., Theresa L. Cleary, RN October 23, 2009

2 Theresa L. Cleary, RN Clinical Informatics Nurse

3 OCHC s History & Mission The mission of Open Cities Health Center is to provide culturally competent primary and preventive health care and related services to all people throughout the Twin Cities metropolitan area. The goal is to improve the health and well-being of high-risk and vulnerable populations through the provision of affordable medical and dental care and related services.

4 Who Does OCHC Serve? 65% of our patients have income levels at or below the Federal Poverty Level. 31% of our patients are uninsured. Over two-thirds are people of color. 39% African American 21% South East Asian 5% Hispanic/Latino 1% Native American 13% are better served in a language other than English. 62% of our patients are female.

5 An Organic Approach to EHR Implementation "Many times we let barriers stop us in our tracks - we have to go around them and keep on walking. There are a lot of people that are cheering for you to be successful." Dorii Gbolo, CEO Open Cities Health Center

6 Executive EHR Committee Medical Director, Deborah Mielke, MD IT Director, Bill Jones Health Information Manager, Pamela Akins Clinical Informatics Nurse, Theresa L. Cleary, RN Clinical Director, Sherry Pittman, RN

7 OCHC Receives MN e-health Implementation Grant 12/1/2007 MN e-health Grant project begins. Clinical Informatics Nurse joins EHR committee.

8 OCHC s EHR/HIT Vision To have a fully integrated, interoperable system that incorporates evidence-based standards to enhance workflow, promote patient safety, and elicit clinical outcomes to improve patient care.

9 A Stepwise Approach to Implementation Diabetic Flow Sheet Asthma Template Measures

10 Building the Foundation. Create policies for quality reporting based on funding requirements and/or quality measures. Define/Maintain Clinical documentation standards. Select the right tools to support effective documentation. Strengthen the knowledge and understanding of staff regarding the value of their clinical data documentation toward population health monitoring and improvements.

11 Building the Foundation

12 Disease Specific Flow sheets Summary of quality measures Retrievable and Reportable Standardizes documentation Patient centered approach Warnings included for omissions

13 Balancing act.. Revise workflows to ensure user-friendly process for capturing comprehensive data. Keep EHR code sets up to date to ensure compliance and HL7 exchange. Perform routine audits for accuracy.

14 Deborah Mielke, MD Medical Director

15 How do we use EMR in real practice? Data needs to be entered into the computer by support staff and providers How and where the data is entered affects the ability to use this data in reports How the system retrieves the data also affects the reports

16 PHM Rule Td/Tdap Status

17 How is data entered into EMR? Clinical Reference Items- Vitals, labs Preventative Health Module Immunization module Prescription writer Template trees*** Free text *** Dictations ***

18 Preventative Health Maintenance (PHM) Reminders & Reports

19 Clinical Decision Support Specialized visit templates and flow sheets Online references & calculators Best practice order sets PHM Reminders & Reports

20 Online References & Calculators

21 Data forms that are not retrievable Template trees Free text Dictations Hand written notes Scanned items

22 S: This patient is in today for follow-up on his multiple medical problems. Patient has a history of renal insufficiency and is being followed by nephrology at this time. The patient states that he refuses to have dialysis. Patient also has a history of heart disease. He has a history of hypertension, history of elevated cholesterol, he has had abdominal aortic aneurysm repair in the past, degenerative arthritis of multiple joints and obesity. Patient also comes in today complaining of erectile dysfunction. O: Vitals: Age: 70. Weight: 300 pounds. Height: Temperature: Blood pressure: 150/72. Pulse: 76. Respirations: 20. Generally, the patient is an obese male seen in no distress. Lungs: Clear. Heart: Rhythm regular. No murmurs or gallops heard. GI: Abdomen is obese. No masses or tenderness. Extremities: There is trace edema in the lower extremities. A: 1) Diabetes Mellitus, Type II. 2) Arteriosclerotic heart disease.

23 4) Hyperlipidemia 5) Renal insufficiency, severe. 6) Status post aortic aneurysm repair. 7) Anemia, probably associated with renal insufficiency. 8) Degenerative arthritis of multiple sites, primarily of the knees and ankles. 9) Erectile dysfunction. P: Patient will be restarted on Furosemide 80 mg. daily. He also was given samples of Cialis 20 mg. every 36 hours as needed. Continue Plavix 75 mg. daily, Norvasc 10 mg. daily, Cozaar 100 mg., Coreg 25 mg. twice daily, Prilosec 20 mg. daily, Clonidine 0.2 mg. twice daily, Simvastatin 40 mg. daily, and NovoLog mix insulin

24 Prescription Writer

25 How is the data retrieved? Some one has to ask the right questions Too much data is not useful Total counts of patients not useful What population are you looking at? Numerator and Denominator Data analysis for accuracy

26 Useful reports and data Patient registries Dashboards for providers UDS reports Pay for performance reports MN community measurement reports

27 How are we doing with these? Problem with registries- too much data, incomplete, need to add and change over time. Provider dashboards- Data linked to diagnosis and is not consistent MN community measures- Our reports missing data that is in dictations and not retrievable

28 What is working? Prenatal registry using information from prenatal module Ongoing data collection for diabetic patients Beginning to build a diabetic registry List of children needing shots Reporting influenza like illness to CDC

29 Bill Jones, IT Director

30 Measures

31 OCHC Reports and Data

32

33

34 Considerations 1. Data Integrity 2. Work back from report to data 3. Continuous verification (don t expect to be notified of process changes) 4. Data capture is the beginning

35 A 1c A1 c BP BP LD L LD L 100% 7 90% 40% 70% 12% 70% 90% 80% S m ok e S m ok e E ye F o ot M / A % of registr y with A1c data A1 c > On e A1 c % of regis try with 2 A1c' s BP # % of regist ry with a BP enter ed BP <1 30/ 80 % of BP with SYS <13 0/80 lipi ds tes ted % of regi stry with ldl entr y LD L< 10 0 % of lipid s <10 0 do cu me nte d sm oki ng % ask ed abo ut sm oki ng cur ren t sm ok er %of regis try who smo ke ey e ex a m % of regis try with eye exa m Fo ot ex a m % of regis try with foot exa m m i c r o t e s t e d a s pi ri n u s e % usin g aspir in ther apy Sel f Mg mt 71% % % % % 80 57% N/A N/A N/A N/A N/ A N/A N/ A N/A 72% % % % % 88 48% N/A N/A N/A N/A N/ A N/A N/ A N/A 82% % % % % % % % 30 4% 27 3% 25 3% 37 83% % % % % % % % 29 3% 23 3% 17 2% 49 83% % % % % % % % 29 3% 23 3% 14 2% 53 83% % % % % % % % 28 3% 30 3% 15 2% 60 84% % % % % % % % 27 3% 33 4% 18 2% 69 84% % % % % % % % 27 3% 31 4% 16 2% 72 84% % % % % % % % 27 3% 32 4% 16 2% 74 85% % % % % % % % 26 3% 41 5% 27 3% 80 86% % % % % % % % 27 3% 39 4% 24 3% 87 85% % % % % % % % 25 3% 43 5% 32 4% % % % % % % % % 48 6% 47 6% 38 4% % % % % % % % % 68 8% 75 9% 72 8% 111

36 Age s HIV Test ed (age 24-59) in last 12m o. % HIV test ed 1 ye ar old s An em ia T mo to 45 5d ay s % Ane mia test ed age 50 + He mo cc ult for ag e 50 + in las t 12 m % He m oc ult 2n d birt hd ay in pri or mo nth 1 9 s h ot s gi v e n % all Sho ts by age 2 Fem ale age s F age d w/ Pap test in last 36 mo. % Pap test ed ag e 0 firs t visi t by 32 da ys % Ne wb orn s w/fi rst visi t by 32 day s ag es 1,2,3 act ive pat ien ts ag e 1,2,3 w/l ea d tes t las t 12 mo. % 1,2, & 3 yr. old s Lea d test ed in last yr ag e 3 A g e 3 wi th > 6 W C C' s 3yr.ol ds- -% wit h > 6 W CC Fe ma e age % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % 161

37 Electronic Medical Records provides an opportunity to quickly monitor/audit patients and see how well they and we are doing This is not an easy process but it is worth every hour and every dollar we spend on it.

38 Questions? Please contact:

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