EMR overview: Opportunities, Realities and the Practice/Research Divide

1. EMR overview:Opportunities, Realities and the Practice/Research Divide Rockville, MD 2009 07 13 Clement J. McDonald MD Lister Hill National Center for Biomedical Communications National Library of Medicine

2. Disclaimer • These remarks are based on my opinion and experience and do not necessarily represent an official opinion or position of the National Library of Medicine or NIH Clem McDonald - Lister Hill Center

3. Background

4. Opportunities

5. Where are the opportunities • Repositories , EMRs • Personal health records • Networked devices and instruments Clem McDonald - Lister Hill Center

6. Repositories, EMRs Lots of data – more to come

7. Current state of world • Clinical repository • Everyone has or is close to having them • If they are only halfway decent - everyone loves them -doctors and administrators • EMR (with CPOE +- note entry) • Slower uptake • Takes doctors time – • Primary care doctors have NO time Clem McDonald - Lister Hill Center

8. Typical clinical repository content • Any information generated via computer systems • ORDERS /Prescriptions • Dictation (op notes, visit notes discharge summaries) • Laboratory results • Radiology reports • Radiology images • Endoscopy reports • Admission and discharge DX’s =and more Clem McDonald - Lister Hill Center

9. EKG flow sheet- click to get the tracing Clem McDonald - Lister Hill Center

10. Clem McDonald - Lister Hill Center

11. Radiology studies- click to get the study

12. Radiology images - thumbnail Clem McDonald - Lister Hill Center

13. BIGGER Clem McDonald - Lister Hill Center

14. Research uses • Find numbers and statistics needed to plan studies and write grants. • Help to recruit study patients with providers consent and involvement- • E.g. Regenstrief Institute, Columbia, Harvard • De-identified studies and statistical analysis (many examples) • Provide follow up data for longitudinal studies. • At IU , 80% of human studies used the Regenstrief Data during some point of their evolution. Clem McDonald Lister Hill Center NLM

15. Huge repositories with much research use at many institutions • Broad spectrum of structured data - billions of data points • Partners HealthCare (Sean Murphy) • Regenstrief Institute (Marc Overhage) • Kaiser Permanente • Veterans Administration • Columbia University • Mayo Clinic Clem McDonald Lister Hill Center NLM

16. Tools available for querying EHRs at many institutions • They have invested in the hard work of regularizing / standardizing the data - at many levels. Clem McDonald - Lister Hill Center

17. Harvard-Partner’s Query tool Query items Person who is using tool Query construction Results - broken down by number distinct of patients Clem McDonald Lister Hill Center NLM

18. Vanderblit’s clinical and specimen search Search requirements specify to return only records with biological samples available over a certain volume amount • Researcher selects samples • Researcher executes search using defined parameters Select Researcher selects most appropriate records Keywords in context provide information for evaluating records Clem McDonald Lister Hill Center NLM

19. Regenstrief SPIN tool Clem McDonald Lister Hill Center NLM

20. What use for drug and alcohol abuse research • Care institutions can and do capture info about smoking, do CAGE screening- etc • Should be a part of routine data gathering at intake • Can be the basis of interventions • Treatment center data is never available, by law. • But repositories do carry related data obtained in course of routine care- e.g. Ethanol levels. Medications – prescribed during acute care Clem McDonald - Lister Hill Center, National Library of Medicine

21. RHIOS –the next step –even more data, population based • Examples • INPC central Indiana (2 Billion results- (Marc Overhage) • (McDonald 2006 Health Affairs) • Memphis – (Marc Frisse -Vanderbilt) • The Ontario Children's network (all test results from all pediatric hospitals made available to all pediatricians ) Gill Hill • Massachusetts e-Health project - five practices, many sites (David Bates) Clem McDonald Lister Hill Center NLM

22. More RHIOs on the way Clem McDonald Lister Hill Center NLM

23. A national infrastructure, RHIOs and standards • Big federal push for clinical data and message standards • This will facilitate and foster RHIOs (EHIs). And they will ink blot across the country • And permit links between these regional networks. • Huge research opportunities • Will return to the subject Clem McDonald - Lister Hill Center

24. Personal Health Records (PHRs) Clem McDonald - Lister Hill Center

25. PHRs - who is providing them Everyone Google Health https://www.google.com/health/html/faq.html My Medicare (and 2 other pilots) http://www.mymedicare.gov/ Microsoft- HealthVault http://www.healthvault.com/ Intuit – Quicken Health http://quickenhealth.intuit.com/ Many other institutions Clem McDonald , Lister Hill Center, NLM 25

26. Special features of PHRs • Some connect to home instruments • E.g. weight, glucometers, exercise (esp Microsoft) • Continua – a consortium of device vendors working on standards for capturing home instrument data • Many research and treatment opportunities • Collect day-to-day status of patients in research studies • With patient consent- options for patient recruitment • Rule rules can provide he behavioral intervention • Could be the core of a drug treatment record – with patient in charge

27. Some examples of active and research use – (of PHR Portals) • Active research projects and patient usage • Partners HealthCare • Children's Hospital of Boston • Vanderbilt University • Department of Veterans Affairs • Kaiser Permanent Clem McDonald - Lister Hill Center

28. NLM’s PHR

29. Overview • Uses NLM’s standard vocabularies • LOINC for observations • Rx.Terms (subset of Rx.Norm) for drugs • SNOMED CT for conditions and findings • HL7 data types • Links to information sources from NLM (MedlinePlus, ClinicalTrials.gov), CDC, etc • Open Source

30. NLM-PHR Highlights • One page data entry form – no jumping around to complete an entry • Codes key information - e.g. drugs, problems, etc • One click links to educational info • Rule-based reminders about prevention and healthy behavior ( Behavioral interventions) • Automatic computation of derived values and defaults • Rule-based form morphing • What shows on the form changes based on what is entered

31. Gender, female, Pap and mammogram

32. Change to male and immediately

33. Discontinue, Revise, Delete to Generate Dynamic Accurate Medication Tracking

34. Delete the beclomethazone (permanently)

35. Form can morph to ask any set of questions- e.g. Phq-9

36. Could (will) use exact same method for NIDA’s abuse screener Clem McDonald - Lister Hill Center

37. NLM PHR Demo • https://phr.nlm.nih.gov/ • not yet publicly available Clem McDonald - Lister Hill Center

38. Home monitoring devices Clem McDonald - Lister Hill Center, National Library of Medicine

39. Opportunities for NIDA treatment programs • Devices getting cheap – and options for direct delivery to PHRs or treatment centers are coming • Conceivable that a package of physiologic measures –pulse, skin conductance, activity level, could provide info for titering drugs during initial treatment • We have an epidemic of methadone related deaths • Would continuous O2 monitoring and email alarms to treatment centers prevent ? Clem McDonald - Lister Hill Center, National Library of Medicine

40. THE DIVIDE Clem McDonald - Lister Hill Center

41. Different directions in standards • Clinical world has been using the HL7 message standard for 15 years • Federal government has defined very specific standards that leverage these existing standards • HL7 V2.5 and HL7 CDA for messages • LOINC and Rx.Norm and SNOMED for codes • http://www.himss.org/ASP/topics_FocusDynamic.asp?faid=211 Clem McDonald - Lister Hill Center, National Library of Medicine

42. HITSPI • ONC has $2 billion to push and complete this trend. • Research interest in standards is newish – and mostly going in its own direction Clem McDonald - Lister Hill Center, National Library of Medicine

43. The two worlds have different ways of thinking about data structures • Makes it harder to even talk about the differences • Researchers uses a flat data structure (often a spread sheet) where the variables are defined as column headers. So you see Cholesterol as the a column name and a value 210 (below it ) The units are assumed. • Clinical systems use a stacked data structure. So reading across a row you see Cholesterol within one cell, 170 in another cell and mg/dl in yet another cell. Clem McDonald - Lister Hill Center, National Library of Medicine

44. Flat structure Clem McDonald - Lister Hill Center

45. Stacked structure Operational Data Base: One Record Per Observation Clem McDonald - Lister Hill Center

46. Research World Uses Flat Structure • When number of variables (questions) is small , they are easier to manage and analyze as a flat structure • But – for longitudinal studies, the changes that creep into study protocols generate many different flat files that are difficult to integrate • Woman’s Health study • Easier to combine data from across studies if stacked structures were used -- Clem McDonald - Lister Hill Center

47. Clinical World Uses Stacked Structure • More general structure • Can accommodate the thousands (or tens of thousands ) of variables • Allows repeat measures at varying time intervals • Allows storage of additional attributes per result – like who recorded per variable, normal ranges, etc • Allows rich definitions of variables in a master file tied directly to the variable in the database Clem McDonald - Lister Hill Center

48. Crux of HL7 V2.x • The messages have a stacked data structure ( • Contain only printable characters (ASCII text) ––V2.5 and uses delimiters to define the fields and sub fields within its “records” • Vertical bars (|) separate fields • Hat ( ^ ) separate subfields • (There is also an XML version of HL7 V2. Clem McDonald - Lister Hill Center

49. Fields have data types. • An espescially important one • CWE = Coded • Code1 ^ print text ^ Code system Clem McDonald - Lister Hill Center

50. Here it is – yellow is variable. Orange is value Patient levelPID|||0999999^6^M10||TEST^PATIENT^||1992022 5|F||B|4050 SW WAYWARD BLVD | Order/report level • OBR|||H9759-0^REG_LAB|24358-4^Hemogram^LOINC • Discrete Results OBX|2|NM||789- 8^RBC^LOINC||4.9|M/mm3| 4.0-5.4 OBX|3|NM|718-7^HGB^LOINC||12.4|g/dL|12.0 5.0||||F| OBX|4|NM||20570-8^HCT^LOINC||50|%|35-49|H|||F| OBX|5|NM||30428-7^MCV^LOINC||81|fL|80-94||||F|b Clem McDonald - Lister Hill Center