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Kensaku Kawamoto, MD, PhD Initiative Coordinator, Health eDecisions Associate Chief Medical Information Officer, Univ. of Utah Health Sciences Center Tonya.

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Presentation on theme: "Kensaku Kawamoto, MD, PhD Initiative Coordinator, Health eDecisions Associate Chief Medical Information Officer, Univ. of Utah Health Sciences Center Tonya."— Presentation transcript:

1 Kensaku Kawamoto, MD, PhD Initiative Coordinator, Health eDecisions Associate Chief Medical Information Officer, Univ. of Utah Health Sciences Center Tonya Hongsermeier, MD, MBA Chief Medical Information Officer, Lahey Health Aziz Boxwala, MD, PhD, FACMI President, Meliorix, Inc. Victor C. Lee, MD Vice President of Clinical Informatics, Zynx Health Jacob Reider, MD Acting National Coordinator for Health IT Health eDecisions: A Public-Private Partnership to Enable Standards-Based Clinical Decision Support at Scale 1

2 Introductions and Lineup PanelistTitleInitiative Role Jacob Reider, MDActing National Coordinator for Health IT Executive Sponsor Tonya Hongsermeier, MD, MBA CMIO Lahey Health Past Initiative Coordinator Kensaku Kawamoto, MD, PhD Associate CMIO University of Utah Initiative Coordinator Aziz Boxwala, MD, PhD President Meliorix, Inc. Subject Matter Expert Victor Lee, MDVP of Clinical Informatics Zynx Health Key Community Contributor 2

3 Agenda TopicPanelist ONC perspective on motivation for initiating HeDReider Overview of HeD and its methodologyHongsermeier Foundational data model: HL7 Virtual Medical RecordKawamoto HeD Use Case 1: sharing CDS through standard knowledge artifacts Boxwala HeD Use Case 2: sharing CDS through CDS guidance services Kawamoto Pilots overview and vendor perspectiveLee Panel discussion, and questions from audienceReider 3

4 Jacob Reider, MD Acting National Coordinator for Health IT Executive Sponsor, Health eDecisions ONC Perspective on Motivation for Initiating HeD 4

5 The Promise of CDS RCTs demonstrating CDS effectiveness available for almost 40 years 1 Actionable, computer-generated CDS provided automatically at the point of care has significantly improved care quality in >90% of RCTs 2 Ref 1. McDonald C. NEJM. 1976;295: Ref 2. Kawamoto K et al. BMJ. 2005;330:765. 5

6 The Reality of CDS CDS commonly available for drug-drug interactions and drug-allergy contraindications Robust CDS for other domains available in select healthcare systems However, in general, CDS use is relatively limited Ref: Osheroff JA et al. A roadmap for national action on clinical decision support. J Am Med Inform Assoc. 2007;14:

7 Key Barrier: Limited CDS Portability Most existing CDS systems and their knowledge bases have limited portability 1 Ref 1: Osheroff JA et al. J Am Med Inform Assoc. 2007;14:

8 Potential Solutions Define standard, universal format(s) for CDS knowledge that can be written once and imported anywhere Define standard, universal format for encapsulating and accessing CDS capabilities as a software service 8

9 Why HeD? The nice thing about standards is that there are so many to choose from –Andrew Tanenbaum Relevant prior work that can be leveraged, plus need to align and harmonize Market forces alone maybe inadequate to move CDS-enabled health and healthcare improvement forward 9

10 The Opportunity: Alignment with MU Meaningful Use (MU) –Federal program that incentives adoption of EHR systems fulfilling MU certification requirements –Administered by U.S. Office of the National Coordinator for Health IT (ONC) MU Focus –Stage I ( ): data capture and sharing –Stage II (2014): advance clinical processes –Stage III (2016): improved outcomes, with CDS as a key component 10

11 Tonya Hongsermeier, MD, MBA Chief Medical Information Officer, Lahey Health Past Initiative Coordinator, Health eDecisions (Jun-Dec 2012) Overview of HeD and its Methodology 11

12 Health eDecisions (HeD) ONC-sponsored, public-private initiative to develop and validate standards to enable CDS at scale (www.healthedecisions.org)www.healthedecisions.org –Will inform MU Stage III EHR certification criteria Brief timeline –April 2012: face-to-face planning discussion, DC –June 2012: initiative kickoff –Jan, May, Sept 2013: HL7 ballots –March 2013+: pilots –Late 13/early 14 (anticipated): draft MU criteria 12

13 Key Contributors Wide, deep range of contributors ONC: Jacob Reider, Alicia Morton, Joe Bormel, Amy Helwig Initiative Coordinator: Ken Kawamoto (1/13+), Tonya Hongsermeier (6/12-12/12) Initiative SMEs: Aziz Boxwala, Bryn Rhodes Terminology SMEs: Robert McClure, Mark Roche Project Management and Support: Jamie Parker, Atanu Sen, Anna Langhans, Saunya Williams, Virginia Riehl, Divya Raghavachari Community Contributors: Zynx Health (Claude Nanjo* and Victor Lee*), Univ. of Utah (David Shields*), Intermountain Healthcare, ASU, Wolters Kluwer Health, VHA, Allscripts, newMentor, CDC, Design Clinicals, and many, many others *Each with hundreds of hours of contribution 13

14 HeD Goal To define and validate standards that facilitate the emergence of systems and services whereby CDS interventions can be shared or accessed by any healthcare stakeholder via an importable format or via a CDS Web service In short, to define and validate standards that enable CDS sharing at scale 14

15 HeD Scope Use Case 1: standard format for sharing CDS knowledge artifacts –Rules, order sets and documentation templates –Goal: CDS knowledge authored in standard format can be imported and used in any EHR system Use Case 2: standard interface for accessing CDS Web services –Goal: CDS capability encapsulated using standard interface can be integrated with any EHR system 15

16 Standards & Interoperability (S&I) Framework Methodology Structured framework for defining and validating standards for consideration in MU Tools and Services Use Case Development and Functional Requirements Standards Development Support Standards Development Support Harmonization of Core Concepts Implementation Specifications Pilot Demonstration Projects Reference Implementation Architecture Refinement and Management Certification and Testing 16

17 Prior Work Analyzed Standard, universal format for CDS knowledge –HL7 Arden Syntax, HL7 GELLO, HL7 Order Sets, ASTM GEM, GLIF3, CDS Consortium L3 model, SAGE, Asbru, PROforma, PRODIGY, AHRQ eRecommendations, etc. Standard interface for submitting patient data and obtaining patient-specific care guidance –HL7 Decision Support Service, IHE Request for Clinical Guidance, OpenCDS, CDS Consortium ECRS, SEBASTIAN, etc. Standard information models –HL7 Virtual Medical Record, C-CDA, QRDA, various HL7 V3 models, FHIM, FHIR, etc. Ref. Kawamoto K et al. Open Medical Informatics Journal. 2010, 4:

18 Health eDecisions Timeline March May Feb Apr June July Aug Dec Consensus Reached on UC 2 UC Harmonization Begins Pilot Work Begins Pilot Activities Completed 18 June 12 Nov Sept Aug Dec Jan 13 Kickoff Consensus on Project Charter Reached Consensus Reached Consensus Standards Reached HL7 Ballot Submitted Presented at HL7 – Affirmative Vote Received Pre- Discover y Discovery ImplementationPilot Use Case One Use Case Two Discovery Implementation Present 5 UC 2 Artifacts to Sept Hl7 Ballot Sept Oct Nov Reconcile all ballot comments and submit UC 2 Artifacts to HL7 for Jan 2014 Ballot 18

19 Deliverables Overview Foundational Deliverables –Functional requirements, including scope specification, use cases, and data requirements –Analysis of relevant efforts (esp. standards) Standards –HL7 Virtual Medical Record (multiple facets) –HL7 Decision Support Service Release 2 –Use Case 1 and 2 implementation guides 19

20 Kensaku Kawamoto, MD, PhD Associate Chief Medical Information Officer, University of Utah Initiative Coordinator, Health eDecisions HeD Key Deliverable 1: Foundational CDS Information Model 20

21 Disclaimers I am, or have been in the recent past, a consultant on clinical decision support to the following entities: I have no competing interests related to OpenCDS 21 Office of the National Coordinator for Health IT (ONC) Partners HealthCare RAND Corporation ARUP Laboratories McKesson InterQual ESAC, Inc. Inflexxion, Inc. Intelligent Automation, Inc.

22 Underlying Information Model Need –Standard CDS data model that is simple and intuitive for a typical CDS knowledge engineer to understand and use Relevant Prior Work Evaluated –HL7 Consolidated Clinical Document Architecture (C-CDA) –HL7 Quality Reporting Document Architecture (QRDA) –HL7 Fast Healthcare Interoperability Resources (FHIR) –HL7 Virtual Medical Record (vMR) –IHC Clinical Element Models, OpenEHR templates, others Decision –HL7 vMR with templates derived from C-CDA and QRDA 22

23 vMR Background A holy grail of clinical informatics is scalable, interoperable CDS Key requirement for interoperable CDS and re-use of CDS knowledge resources = use of a common patient data model –Referred to as a Virtual Medical Record or vMR (Johnson et al., AMIA Annu Symp Proc, 2001) Needs to be easy and safe for a typical CDS knowledge engineer to understand and use Lack of a common vMR has been a major barrier to sharing knowledge and scaling CDS 23

24 Example Challenge without VMR Observation Code = BP Value = 120/80 mmHg Blood Pressure Systolic = 120 mmHg Diastolic = 80 mmHg Code = BP Value = 120/80 mmHg Observation Code = BP Observation Code = SBP Value = 120 mmHG Observation Code = DSP Value = 80 mmHg Vital Signs Type = BP Value = 120/80 Units = mmHg 24

25 vMR Goal Provide standard information model for CDS that (i) can be used across CDS implementations and (ii) is simple and intuitive for a typical CDS knowledge engineer to understand, use, and implement 25

26 Development Methodology Analysis of data required by 20 CDS systems from 4 countries (Kawamoto et al., AMIA 2010) Analysis of various standard information models –HL7 CCD, C-CDA, QRDA, Pedigree model, Clinical Statement pattern, etc. Analysis of orderables from hundreds of hospitals Iterative refinement from pilot use –In particular, through OpenCDS (www.opencds.org) and HeD pilotswww.opencds.org –Initial ballot in 2010; Sept = 4 th round of balloting 26

27 Why Not Just Use C-CDA as the vMR? CCDA 1.1 representation of Patient has had asthma since

28 Why Not Just Use C-CDA as the vMR? entry[typeCode=DRIV and act[classCode=ACT and moodCode=EVN and /templateId[root= ] and /code[codeSystem= and code=CONC] and /statusCode[code=completed] and /entryRelationship[typeCode=SUBJ and /observation[classCode=OBS and moodCode=EVN and /templateId[root= ] and /code[codeSystem= and code= ] and /statusCode[code=completed] and /effectiveTime[/low[value<= ]] and /value[xsi:type=CD and codeSystem= and code= ] and /entryRelationship[typeCode=REFR and /observation[classCode=OBS and moodCode=EVN and /templateId[root= ] and /code[xsi:type=CE and codeSystem= and code= ] and /statusCode[code=completed] and /value [xsi:type=CD and codeSystem= and code= ] ] ] ] ] ] Sample CDS expression that Patient currently has active asthma using CCDA 1.1 Data Model 28

29 vMR Representation of Equivalent Content Sample CDS expression for Patient currently has active asthma using vMR clinicalstatement[xsi:type=vmr:Problem and /templateId[root= ] and /problemCode[codeSystem= and code= ] and /problemEffectiveTime[/low[value<= ]] and /problemStatus[codeSystem= and code= ] ] vMR representation of Patient has had asthma since

30 Simplification – Data Types HL7 Version 3 Release 2 Data Type Model for Integer Constrained HL7 Version 3 Release 2 Data Type Model for Integer used in vMR Value of the INT 30

31 Example vMR Template Example: 31

32 Aziz Boxwala, MD, PhD President, Meliorix, Inc. Subject Matter Expert, Health eDecisions HeD Key Deliverable 2: HL7 CDS Knowledge Artifact Implementation Guide (IG) (HeD Use Case 1 IG) 32

33 Goal CDS interventions must be made shareable and implementable so that they can be acquired and deployed by any organization 33

34 Use Case Overview 34

35 Design objectives Format for specifying computable CDS knowledge –Knowledge can be imported into existing CDS systems Not creating a new execution format –Format must be flexible Support different CDS intervention types –More than alerts and reminders Knowledge must be portable 35

36 Approach Reviewed several existing knowledge representation formalisms –Did not meet requirements completely Solution is a harmonization of several formats and ideas –CDSC-L3, ArdenML, CREF –HL7 Order Sets Specification, Infobutton –GEM, HQMF, eRecommendations, GELLO, research from SHARP-C, … 36 CDS Artifact Sharing Use Case FR & Data Elements VMR GEM eRECS CDSC L3 HL7 Order Set Model SHARP ARDEN Inputs HeD Knowledge Artifact Schema HeD Knowledge Artifact Schema Harmonization and Modeling CREF

37 Knowledge artifact schema Modular, component based solution Specifies key components of any CDS intervention –Metadata –Expression language –Action –Trigger –Data model (by reference) vMR 37

38

39 Knowledge artifact schema Schemas defined by composition of components Currently supported CDS interventions –Event-condition-action rules –Order sets –Structured documentation templates In future, can be expanded –E.g., Plans of care, infobutton rules/knowledge, relevant data display 39

40 Expressions External Data –Specifies the data required to evaluate the artifact Logic –Criteria used within CDS Calculations –Dosing, risk 40

41 External Data Example Pertussis problem 41 Addressing the curly braces issue using HeD expression language and the VMR

42 Conditions Example (Patient lives in SD or Care encounter was in SD) and (Diagnosed with Pertussis or Cause of Death was Pertussis or culture results positive for pertussis) 42

43 Actions Create/Modify/Remove Action –Create indicates proposal for an action as a vMR object e.g. create a SubstanceAdministrationProposal create a CommunicationProposal Collect Information Action –Defines information to be collected Action Groups –Provide structure for grouping actions 43

44 Communication Action 44

45 Kensaku Kawamoto, MD, PhD Associate Chief Medical Information Officer, University of Utah Initiative Coordinator, Health eDecisions HeD Key Deliverable 3: HL7 Decision Support Service IG (HeD Use Case 2 IG) 45

46 Goal Allow any organization to easily obtain CDS guidance through a secure, standard Web service interface. 46

47 Use Case Overview CDS Guidance Requestor CDS Guidance (care guidance) CDS Guidance Supplier CDS Request (patient data) 47

48 Key Standards HL7 Decision Support Service (DSS) –Defines SOAP and REST Web service interfaces for CDS guidance services HL7 Virtual Medical Record (vMR) –Provides easy-to-understand data model for CDS HL7 Consolidated CDA (C-CDA) and Quality Reporting Document Architecture (QRDA) –Terminology bindings and value sets largely being adopted within vMR as vMR templates 48

49 CDS Guidance Service – Example Decision Support Service EHR System vMR Eval. Result 49

50 Sample CDS Guidance Services Evaluation InputEvaluation Output Medication identifier, age, gender, weight, serum creatinine level Recommended maximum and minimum doses for medication given patient's estimated renal function Insurance provider, data relevant to prescription Prior authorization to prescribe medication Patient summaryWide range of care recommendations Patient age, gender, past health maintenance procedures List of health maintenance procedures due or almost due 50

51 Sample Current Implementers OpenCDS (www.opencds.org)www.opencds.org –Multi-institutional open-source effort led by Univ. of Utah –Implements HL7 DSS and vMR; will support HeD UC 2 –200+ members from 150+ organizations –Example implementation: Immunization Calculation Engine (ICE), led by HLN Consulting, & used by New York City, Alabama, eClinicalWorks Enterprise Clinical Rules Service –Part of CDS Consortium effort Epic EHR –Will support CDS Guidance Services in 2014 release 51

52 OpenCDS Knowledge Editor 52

53 53

54 Standards Status 54 StandardDescriptionHL7 Status Comments HL7 vMR Logical Model Base UML specification Passed HL7 ballot Sept HL7 vMR XML Specification XML specificationPassed HL7 ballot Sept HL7 vMR Templates Includes terminology binding Passed HL7 ballot Sept Developing additional templates HL7 CDS Knowl. Artifact IG Use Case 1 IGPassed HL7 ballot Jan HL7 DSS Release 2 DSS base specification Passed HL7 ballot Sept with 100% affirmative vote HL7 DSS IGUse Case 2 IGPassed HL7 ballot Sept with 100% affirmative vote Ref:

55 Victor Lee, MD Vice President of Clinical Informatics, Zynx Health Community Contributor, Health eDecisions Pilots and Vendor Perspective 55

56 56

57 57

58 Do the right thing 58

59 59

60 Pilot Partnerships – HeD Use Case 1 EHRPilotContent Supplier Design Clinicals Order Set – Heart Failure Zynx Health AllscriptsRule – NQF 068 (Million Hearts) newMentor AllscriptsRule – San Diego Pertussis CDC VADocumentation Template – UTI Wolters Kluwer Health 60

61 Order Set Exchange Pilot 61

62 WKH Doc. Template in VA CPRS © 2013, Kensaku Kawamoto 62

63 63

64 People who say it cant be done should get out of the way of people who are doing it. 64

65 Jacob Reider, MD Acting National Coordinator for Health IT Executive Sponsor, Health eDecisions Conclusions and Panel Discussion 65

66 Conclusions True community effort Remarkable achievements in limited timeframe Unique opportunity to realize the promise of CDS and make Meaningful Use of EHRs 66

67 Discussion Questions What do you think of HeD and its potential impact? How can we best encourage CDS sharing at scale? How can we best align CDS with healthcare transformation? What more can the public and private sectors do to facilitate CDS-enabled healthcare improvement? How can we start to make progress NOW? What kind of content would be most useful? 67

68 Thank You! Kensaku Kawamoto, MD, PhD Associate Chief Medical Information Officer, Univ. of Utah Health Sciences Center Initiative Coordinator, Health eDecisions Tonya Hongsermeier, MD, MBA Chief Medical Information Officer, Lahey Health Aziz Boxwala, MD, PhD President, Meliorix, Inc. Victor C. Lee, MD Vice President of Clinical Informatics, Zynx Health Jacob Reider, MD Acting National Coordinator for Health IT 68

69 Backup Slides 69

70 S&I Framework Phases PhaseActivities Pre-Discovery Development of Initiative Charter Definition of Initiative Goals & Outcomes Discovery Development of Use Cases & Functional Requirements Review and analysis of existing standards Implementation Development and balloting of needed standards Development of tools to facilitate implementation of standards Pilot Pilot implementation of the standards Refinement of standards based on lessons learned Evaluation Measurement of initiative success against goals and outcomes Provide recommendations to ONC for potential wider scale deployment 70

71 Ref 1. Osheroff et al. JAMIA. 2007;14: Clinical Decision Support (CDS) Definition –Provision of pertinent knowledge and person-specific information to clinical decision makers to enhance health and health care 1 Examples –Alerts and reminders –Order sets, documentation templates –Infobuttons, data displays 71

72 Metadata Identifiers –Id, Title, Description, Artifact Lifecycle Documentation –Documentation, Related Resources Supporting Evidence Data Models Key Terms 72

73 Metadata (Example) 73

74 Pilots Overview HeD Use Case 1 pilots –Completed summer 2013 –Focus of discussion today HeD Use Case 2 pilots –Various groups are using earlier versions of standards in production systems –Pilots of current versions of standards in progress 74

75 Pilot Partnerships – HeD Use Case 1 EHRPilotContent Supplier Design Clinicals Order Sets – Heart FailureZynx Health AllScriptsRule –NQF 068 (Million Hearts) NewMentor AllscriptsRule - San Diego PertussisCDC VADocumentation Template – Urinary Tract Infection Wolters Kluwer Health 75

76 General Approach CDS knowledge artifact expressed using HL7 standard Model transformed from HeD format to EHR- specific format using model mapping tool –Bryn Rhodes: HeD Schema Framework –Robert Lario: UML Modeling Transformation Framework Knowledge artifact consumed in EHR 76

77 HeD to Allscripts CREF Example 77

78 Order Set Exchange Pilot CDS Supplier: Zynx Health Claude Nanjo Victor Lee CDS Consumer/EHR Vendor: Design Clinicals Dewey Howell 78

79 UML Modeling Transformation Framework (R. Lario) 79

80 Model Transformation © 2013, Kensaku Kawamoto 80


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