Evaluating EHR at the Point of Care

Transcription

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

2 Attendee Demographics Physicians Solo private practice Group practice Medical center Organization Administrators IT companies Lab and Radiology 2

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 3

4 Terminology of Practical E/M Measures Tools 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 4

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

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 6

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

8 Modern Medical Records Subbed Paper for Data Entry & Storage 8

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 $$$$ 9

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 10

11 Data Storage/Retrieval Features Paper EHR Straightforward Access problems Cost problems Features?? Sophisticated Access success Cost issues Features Searchable Interconnectivity Interoperability CPOE Data for EBM Clinical decision support at POC 11

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 12

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 physician interaction at POC 2) For quality of data entered into medical record 13

14 Consequence 1: Patient/Physician Interaction at the Point Of Care 14

15 Patients Want & Expect to See This (and so do Physicians) 15

16 Patients Do NOT Want This 16

17 Or This 17

18 However, Everyone s Happy with a Hybrid System! 18

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 19

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

21 Effect on the Tools of Practical E/M Interface Graphic - maintained Narrative - LOST Data entry personnel Physician - maintained Staff possible Patient - LOST 21

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

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 23

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

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

26 Hamlet comes home from school. Father died. Mother married Father s 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( Yorick). Skull doesn t t answer. Rosencrantz and Gildenstern die. 26

27 Actors visit castle. Hamlet chooses play and writes a new scene. Play disturbs Hamlet s s uncle. Play disturbs Hamlet s 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.} 27

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 28

29 Effect on Diagnostic Paradigm Increased reliance on routine laboratory and radiographic testing Increased costs and decreased efficiency Increased Increased blanket testing Increased Increased number follow-up visits Decreased quality of care Lost Lost ability to recognize when test results don t fit the history Physician Physician lost when test results negative (no basis to explain symptoms or guide future care) 29

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 30

31 Demo EHR Evaluation Protocol Phase I: Enter complete detail of 4 5 charts into EHR demo. Analyze 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 Analyze usability and efficiency Have Have spouse analyze impact on the patient 31

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 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 32

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 33

34 When Is a Doctor Too Old? Or Too Young? By Abigail Zuger, M.D. New York Times February 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. 34

35 When Is a Doctor Too Old? Or Too Young? By Abigail Zuger, M.D. New York Times February 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. 35

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 36

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? CEOCEO Senior Senior Management Administrators Clerical Clerical staff 37

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

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 39

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 40

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 41

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? 42

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 Number of visits prior to establishing a diagnosis for a given symptom Appropriateness of testing Appropriateness and timeliness of referrals 43

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??? 44

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? 45

46 How Effective is the Telephone - If No One s Listening on the Other End?? 46

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

48 Questions?? Answers???? 48