1. Join the conversation! Our Twitter hashtag is #CPI2011. Garbage in, garbage out: Barriers to Efficient Data Capture and Review A case study in maximizing EMR utilization and management of high-risk patient populations by: Matthew Huspeni, BS; and Dr. Jonathan Zonca, MD

2. Why invest time reviewing data capture? Measure and address quality of care –Strive to provide best care for individual patient –Ability to track entire high-risk patient populations –Proactive vs. reactive care strategies

3. Why invest time reviewing data capture? Patient Centered Medical Home (PCMH) –Quality measurement practices –Health information technology systems Becoming a PCMH takes time, effort, and change

4. Why invest time reviewing data capture? Reimbursement stipulations –Provide current and accurate patient tracking info in order to receive payment –HMO –Medicare –PQRI Data

5. Why invest time reviewing data capture? YOU MIGHT BE SURPRISED WHAT YOU FIND IN TERMS OF REPORTING ACCURACY! Bad in, bad out.. –Cannot make informed decisions on patient care with bad data Must develop accurate data collection procedure

6. Our Initial Goals Small family practice office taking initial steps to fit the PCMH model Audit data capture and reporting so as to be able to implement patient tracking system to proactively care for our high risk patients

7. Methods Electronically generated Crystal Reports were run to capture key diabetic measures Tracked: Hb-A1c, BMI, LDL, foot exam compliance, dilated eye exam, microalbumin

8. Methods Measured Crystal Reports against manually generated Excel spreadsheet (i.e. - chart audit) Compared individual patients visits and data captured in automated reports

10. Results HUGE discrepancies between manual and automated reports Data so inaccurate as to be completely unusable for our purposes of patient tracking Starting point moved from improving care via patient tracking to understanding our EMR system

11. Results

13. During generation of manual list numerous carting inconsistencies observed amongst providers Where/how is information charted? –Free text vs. searchable –How does your system create reports? –Do you create reports? –Does your clinic have a clear chronic condition flow involving whole team?

14. Can of worms… BIG PICTURE: Our electronically generated data was completely unusable for patient monitoring and tracking! Data is misleading and potentially dangerous. Need to relearn EHR system and understand the reporting function.

15. Further investigation Necessitated a reevaluation of our project goals, more was wrong with our Crystal Reports than originally anticipated –Where do the reports pull data from? –What input format allows for discrete data capture.

16. Further investigation Input format –QL7 and HL7 format vs. jpeg and free text –Provider dependent order entry (i.e.- PQRI) –Faxed and scanned docs from specialists and other offices (also requires manual update into chart) –Which allows for discrete data capture?

17. Further investigation In office charting practices –What gets charted (BMI not always tracked) –Where it gets charted (HPI, provider orders, exam, lab results, documents from other providers) –HOW AND WHERE TO INPUT DATA Orders vs. history vs. data driven

18. Further investigation Patient inactivity tracking –Found significant % of patients reflected in Crystal Reports were deceased, had moved, or had switched providers –Cannot effectively track patient population w/o up-to-date patient lists –Data complicated by patients who are followed by Endocrinology

20. Results

21. Bottom line… NO QUICK FIX! –Need to invest the time to identify and address errors data capture Even with software updates, Crystal Reports still inaccurate and unusable Need to create outside registry or utilize function within system

22. Moving forward Recommend performing a “mini audit” to assess baseline data quality –Run several Crystal Reports capturing key parameters –Randomly select 5-10 patients –Compare electronically generated data with a manual search through patient chart

23. Moving forward Software update –Did not fix any of our CR problems e-MD customer support training sessions –Info available at: http://www.e- mds.com/support/training/index.htmlhttp://www.e- mds.com/support/training/index.html –Phone support disappointing

24. Moving forward In-house provider meeting –Meet w/ office providers to standardize charting practices –Provide expectations –Develop plan of care for patients –Discuss registry of patients, use recall function of EHR, manually input eye/foot exams.

25. Moving forward Overdue rule report –Reporting system within e-MDs using the Rule Manager function –Providers educated on orders documenting clinical status (ie. Hb-A1c <7) and use of Rule Manager

29. Moving Forward Registry processor reminder system –Would allow providers to custom tailor reminder reports and track patients. –Function potentially useful but unable to run useful report due to lack of training –In the process of educating ourselves on its utilization

30. Moving forward

31. Integrated patient registry software –Several options available –Expensive: Base model +50k Not feasible for most small offices

32. Moving forward: Low tech soln. Excel based registry system –http://www.aafp.org/fpm/2006/0400/p47.ht mlhttp://www.aafp.org/fpm/2006/0400/p47.ht ml –Pro: Easy to use, no need to worry about complex software systems –Con: Data must be input manually, no automated update or reminder system

33. Moving forward: Low tech solns

34. Diabetes care flow-sheet filled out by provider with the patient –Patient responsible for the folder and getting it filled out by the appropriate provider (neuro, optho, primary) –Goal is to increase patient compliance –Novo Nordisk provides diabetes care flowsheet (www.novomedlink.pro)

35. Moving forward: Low tech solns

36. Take Home Points This small project opened a can of worms for our small office –Baseline data assessment  Mini audit –Investigate where reporting functions gather data from –Educate providers –Implement reasonably easy/inexpensive measures to track your patients