Evaluating EHR at the Point of Care

1. Evaluating EHR at the Point of Care Physicians’ Perspective, & Perspective on Physicians Stephen R. Levinson, M.D. (March 7, 2005) CMO, iMedX ASA,LLC

2. Attendee Demographics • Physicians • Solo private practice • Group practice • Medical center • Organization • Administrators • IT companies • Lab and Radiology ASA,LLC

3. Background: • E/M coding trainer • Medicare committees • TPA management • Spec soc. Quality and insurance committees • Compliance expert for MDL • AMA book on Practical E/M Coding and Documentation for Quality Care • CMO for iMedX • 26 yrs Medical Practice ASA,LLC

4. Quality of Care E/M Compliance Efficiency Productivity Physician usability (friendliness) Interface Graphic Narrative Data entry personnel Physician Staff Patient Format ** Data Storage/Retrieval Data Entry Terminology of “Practical E/M”MeasuresTools ASA,LLC

5. Questions for EHR Functionality • What digital data needs to be entered? • What digital data needs to be accessed? • Outcomes studies • EBM • Clinical Decision support • What studies have been done concerning impact of EHR at the POC??? ASA,LLC

6. Format: Separate Consideration for Data Storage from Data Entry • Prior to EHR, regardless of data entry format, the only data storage format was Paper charts ASA,LLC

7. For Hippocrates, Data Entry & data storage/retrieval, on papyrus ASA,LLC

8. Modern Medical Records Subbed Paper for Data Entry & Storage ASA,LLC

9. Pattern changed with Intro of Dictation for Data Entry • This did not change data storage in paper charts • Landmark of data entry having different format from data storage & retrieval • ALL discussion of advantages and disadvantages confined to data entry • Legibility • Turnaround speed • Cost $$$$ ASA,LLC

10. Introduction of E Health Records • First change in format for data storage & retrieval • Dramatic reversal: now ALL discussion of advantages and disadvantages has been confined to enhancing benefits of data storage and retrieval • Total absence of assessment of data entry features of Electronic Health Records • Analyze impact on MD & Pt at POC • Analyze impact on “measures” of medical records ASA,LLC

11. Straightforward Access problems Cost problems Features ?? Sophisticated Access success Cost issues Features Searchable Interconnectivity Interoperability CPOE Data for EBM Clinical decision support at POC Data Storage/Retrieval FeaturesPaperEHR ASA,LLC

12. Examine Format for Data Entry • Need to bring the same innovation, enthusiasm, and commitment to EHR data entry design that developers are bringing to data storage design • Review must be fair and honest, to stimulate optimal data entry design enhancements ASA,LLC

13. Fundamental Assumptions Incorporated in Existing EHRs • The physician is assigned as the data entry operator (‘DEO’) • Format for data entry is the same as format for data storage (i.e., direct data entry into the computer) • Cascade of consequences of these two assumptions: • 1) For patient-physician interaction at POC • 2) For quality of data entered into medical record ASA,LLC

14. Consequence 1: Patient/Physician Interaction at the Point Of Care ASA,LLC

15. Patients Want & Expect to See This (and so do Physicians) ASA,LLC

16. Patients Do NOT Want This ASA,LLC

17. Or This ASA,LLC

18. However, Everyone’s Happy with a Hybrid System! ASA,LLC

19. Consequence 2: Impact on Quality of Data Entered • It is critical to have optimal data entry for EHRs to achieve their goals for quality & safety • Loss of quality data entry creates “GIGO” ASA,LLC

20. That is, Conclusions Are No Better Than the Data They are Based Upon(Image from Google.com, from website: www.turkkupetcentre.fi/…/model_application.html) ASA,LLC

21. Effect on the Tools of Practical E/M • Interface • Graphic - maintained • Narrative - LOST • Data entry personnel • Physician - maintained • Staff – possible • Patient - LOST ASA,LLC

22. Loss of the Narrative Interface • Written narrative provides quality and efficiency for multiple sections of med record • HPI • Positive responses to ROS graphic interface • Abnormal exam findings • Details of Medical Decision Making • Keyboard entry could duplicate the enriched multilevel descriptions needed for Quality ASA,LLC

23. Loss of the Narrative Interface • How many physicians can type while looking at, and concentrating on, patient at the same time? NONE • Therefore, EHRs lose narrative interface for data entry due to fundamental assumptions ASA,LLC

24. Evaluating EHR Alternatives to the Narrative (free text) Interface • Pick Lists • Generic templates containing general descriptions related to patient’s chief complaint • Physician fills in a few variables through either pick lists or limited keyboard entry ASA,LLC

25. What Happens When We Force a Richly Descriptive Narrative Into a Graphic Format (Pick Lists or Templates)? • Let’s picture Will Shakespeare’s first effort at writing Hamlet, using a 200-phrase pick list: ASA,LLC

26. “Hamlet comes home from school. Father died. Mother married Father’s brother in one month. • Hamlet disturbed. Sees ghost. Hamlet more disturbed. • Hamlet acts crazy. Torments girlfriend (Ophelia); says become a nun. Ophelia disturbed, kills self. • Hamlet kills Polonius. • Hamlet talks to a skull (Yorick). Skull doesn’t answer. • Rosencrantz and Gildenstern die. ASA,LLC

27. Actors visit castle. Hamlet chooses play and writes a new scene. • Play disturbs Hamlet’s uncle. Play disturbs Hamlet’s mother. Uncle kills Mother. • Big sword fight. Hamlet kills opponent. Hamlet kills Uncle. Hamlet dies. • Everyone dead. • Play ends • {Fortunately for world literature, Shakespeare did not have to use a pick list to create Hamlet.} ASA,LLC

28. Hypothesis: Effect of Lost Narrative on Diagnostic Paradigm • Optimal Paradigm: Good History Guides Dx • With pick lists and generic templates, cascade of: • Limited history information (i.e., CC) guides selection of a non-specific history • Record for 1 patient with a disease reads same as record for every other patient with that disease • Non-specific history insufficient for precise Dx ASA,LLC

29. Effect on Diagnostic Paradigm • Increased reliance on routine laboratory and radiographic testing • Increased costs and decreased efficiency • Increased “blanket” testing • Increased number follow-up visits • Decreased quality of care • Lost ability to recognize when test results don’t fit the history • Physician “lost” when test results negative (no basis to explain symptoms or guide future care) ASA,LLC

30. Effect of Lost Narrative on E/M Compliance Audit • Automatic defaults to negative or normal = fail • PFSH & ROS positive responses not documented = fail • Similar documentation visit after visit and case after case shows only that EHR can enter the same template over & over = fail ASA,LLC

31. Demo EHR Evaluation Protocol • Phase I: Enter complete detail of 4 – 5 charts into EHR demo. • Analyze usability and efficiency vs. usual approach • Phase II: Repeat process with MD asking questions of spouse, acting as pretend patient & reading chart responses while MD enters the data into the HER • Analyze usability and efficiency • Have spouse analyze impact on the patient ASA,LLC

32. Hypothesis: Effect of Lost Narrative on Success of EHR Adoption • Efficiency of data entry  for 6 – 12 months • MDs then “master” the input into pick lists or pre-written templates for speed • What happens to bring about this change???? • ??MDs cease trying to input a customized narrative • They can increase speed of data entry only by entering similar generic information on every similar patient in order to ‘get the work done.’ • Those who refuse to adapt have system failure ASA,LLC

33. Effect of 2 EHR Assumptions on the Measures of “Practical E/M” • Efficiency • Reduced by loss of patient for data entry • Productivity • Reduced by loss of efficiency, sub-optimal E/M coding • E/M Compliance • Reduced by similarity of descriptions among patients • Quality of Care • Reduced by loss of narrative interface • Physician usability (friendliness) • Reduced by requirements for direct computer entry ASA,LLC

34. When Is a Doctor Too Old? Or Too Young?By Abigail Zuger, M.D.New York TimesFebruary 8, 2005 • The young doctor remembered little about each patient from visit to visit, but typed volumes, and was a big fan of medical software that supplies preformed phrases, sentences and paragraphs - the results of an entire physical exam, for instance - at the click of the mouse. Sometimes the mouse clicked just a little too quickly and erroneous information crept into the charts.

35. When Is a Doctor Too Old? Or Too Young?By Abigail Zuger, M.D.New York TimesFebruary 8, 2005 • Insurance reviewers occasionally confused the old doctor's terse notes with incompetence. Patients occasionally complained bitterly about the young doctor, deploring that habit of pounding the computer keyboard for the duration of their visit and never once looking them in the eye. Both doctors, learning of these misunderstandings, were mortified and furious. Colleagues who had to wade through charts belonging to either one just tore their hair.

36. A Patient’s Perspective • “If I wanted to have a visit with a keyboard, I’d sit at home and surf the Internet • Something else is supposed to happen in the doctor’s office • You don’t need 10 years & $250,000 of education to be spent on typing • Perhaps keyboard input should be banned from the exam room”

37. It’s Time to Re-examine the 2 Data Entry Fundamental Assumptions • The physician must record data, • But must the physician be the individual entering that data directly into the computer? • Who does the CEO of a company appoint to enter information into their computer system? • CEO • Senior Management • Administrators • Clerical staff ASA,LLC

38. Shipping your luggage to S.F. – What’s the Most Effective Option?

39. What Happens When We Change the Data Entry Assumptions? • Hybrid I: At least one company has opened this door by allowing the option of MD dictation • DEOs or voice recognition software enter the narrative data • Innovative first step • Requires further examination of structure and function of data entry format to satisfy all medical record measures ASA,LLC

40. Possible Solution: Hybrid System II • Professional DEOs enter medical information into EHR • Physician has full flexibility for a “data transfer medium” • Achieves compliance, efficiency, quality, usability ASA,LLC

41. Data Transfer Medium Options • Structured paper templates (IMR) • Narrative interface options • Patient data entry PFSH & ROS graphic interface templates • Complete E/M compliance documentation and guidance • Dictation • Tablet PC written entry

42. Additional EHR Issues • What should we measure for quality, including “pay for performance”? • How will “clinical decision support” function and be received? • What about physician training? ASA,LLC

43. Issue 1:Data for “Pay for Performance”? • Management of chronic illnesses (e.g., DM, CHF) • Preventative care (e.g., mammography, colonoscopy, PSA) • ??? Diagnostic insight • Number of visits prior to establishing a diagnosis for a given symptom • Appropriateness of testing • Appropriateness and timeliness of referrals ASA,LLC

44. Issue 2: Response to Clinical Decision Support? • In the journal/DVD/Internet era, • IOM reports: It takes about 17 years for a proven new therapy to be adopted into standard care • WHY ??? ASA,LLC

45. ½ Life of MD Practice = 17 Yrs! • “I finished my training in 1976” • Not trained for change • Not trained for E/M coding • Not trained for EHR • Not trained for Interconnectivity • Financial constriction has destroyed physician time for creative improvement • When an electronic message arrives in an empty forest, is there a change in behavior? ASA,LLC

46. How Effective is the Telephone - If No One’s Listening on the Other End?? ASA,LLC

47. Issue 3:To Digitize the Healthcare Environment, We Must Include Physician Training ASA,LLC

48. Questions?? Answers???? ASA,LLC