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  1. 1. Clinical InformaticsClinical Informatics W. Ed Hammond. Ph.D., FACMI, FAIMBE Director, Duke Center for Health Informatics Professor , Department of Community and Family Medicine Professor, Department of Biomedical Engineering Adjunct Professor, Fuqua School of Business Duke University Vice-chair HL7 Nothing to Disclose
  2. 2. Enabling Model Output
  3. 3. Application of HIT 3 Feedback Loop Outcome Understand the problem to be solved. Understand causes, factors, issues Understand measurements and data required to monitor & solve Implement proposed solution. Evaluate outcome
  4. 4. What problem does the EHR solve? • Documents patient care • Provides data for decision making • Provides for continuity of care • Provides data for billing • Can be mined for new knowledge • Can be used to measure performance • Contributes to patient safety • Source for reporting, audits 4
  5. 5. HIT – Stimulus target • Inclusion of $36.5 billion to create nationwide network of EHRs • Can HIT improve health and health care? • Can HIT save $77.8 b each year through universal use of HIT? • What is meaningful use of EHR? • Will the goal be met: will every citizen have an EHR by 2012?
  6. 6. Rising CostsRising Costs • For the past 4 decades, per capita health care spending grew much more rapidly than per capita GDP • Most experts agree that the key factor driving the long-term growth of health care costs has been the emergence, adoption, and widespread diffusion of new medical technologies and services. • Technological advances are likely to yield new, desired medical services in the future, fueling further spending growth and imposing difficult choices between health care and other priorities. 6 CBO Testimony, 2008
  7. 7. 7 Australia $2,876 18.2 88 34 80 8.8 0.4 Canada $3,165 17.7 92 26 82 12 0.5 France $3,159 18.4 75 n/a 79.7 8 0.5 Germany $3,005 17.5 106 28 78 11.9 0.6 Japan $2,249 19.6 81 n/a 79 10.3 0.2 New Zealand $2,083 17.1 109 38 79 10.9 n/a UK $2,546 16.9 130 13 80 11 0.5 US $6,102 16.6 115 51 88.9 14.8 0.7 Expenditures percapita Lifeexpectancy atage60 Preventabledeaths per100,000pop. Access Problems 5Yr.survival breastcancer MI30day hospitalmortality Deathsfromsurgical ormedicalmishaps per100,000pop Source: BMJ, 2007 Healthcare Indicators
  8. 8. Reducing Disparities in Cost • Why are costs for health care so different around the world when outcomes are particularly different? Some countries have better outcomes at half the cost. – Costs are also related to administrative and fiscal structure of healthcare system. – New technologies frequently increase the cost without significant improvement in outcomes • What role does appropriate and effective care play? Is more better? • What should be evaluation criteria for the introduction of new technologies? 8
  9. 9. Technology • Technology has been one of the major factors that has increased human life expectancy about 3 months for every 1 year for the past century. • Does technology save money? – Technology costs money! – Longevity increases cost of healthcare. – We can now treat diseases that were previously untreatable. • Imaging increases cost – is the resulting value worth it? 9
  10. 10. Value • Evidence has not shown that increasing costs for health care has resulted in commensurate gains in health • Further, excessive spending may result in steps not being taken that could prevent the onset of disease – even when clear evidence exists about the benefits of such steps • What is the value evidence for the widespread use of CIS in healthcare? 10
  11. 11. Value of HIT • Efficiency in data capture • Continuity of care – aggregation of data from all sites of care • Increased consistency of care – for an individual and across populations • Increase in quality of care by timely access to data and knowledge by both provider and consumer • Reduced cost through elimination of redundant testing and unnecessary testing • Reduced cost through elimination of medical errors 11
  12. 12. Value of HIT • Improved accuracy of diagnoses and precision of therapeutic interventions • Through use of geocoding, better understanding of environmental and social factors impact on cause and course of disease • Identification of all factors involved in impacting disease and quality of life • Provide national statistics on prevalence of disease • Better health through delivery of higher quality care • Higher quality of life and longer life through instilling healthy behavior 12
  13. 13. Value of HIT • Data and outcomes available for the understanding of the effects of treatment and for the extraction of knowledge • Through measurement, a better understanding of cause and effect • Creating models that will better predict the cost of health care • More rapid identification of candidates for clinical trials • Quicker determination of global adverse drug events • Quicker awareness of disease outbreaks 13
  14. 14. Value of HIT • Data is reusable; provides value for multiple secondary uses • Analysis of patient conditions, treatments, outcomes, demographics and environment produce new knowledge that is automatically fed back into the care process. • Models of care are produced that permit projections for improved outcomes, reduced costs, higher quality. 14
  15. 15. Why is HIT a high priority? • Patient safety – Increased concerns related to safety of prescription drugs – New emphasis on eliminating Healthcare Affiliated Infections • Efficient and effective health care delivery a must • Health surveillance, bio-defense and natural disaster; increased mandatory reporting requirements • Demand for quality; pay related to performance and outcomes • Cost containment in face of increasing costs of healthcare • Accommodating an aging and mobile population • Effective management of chronic disease 15
  16. 16. Why is HIT a high priority? • Equal access to care • Consumer sophistication and knowledge in health; mobility • Increasing importance of multiple uses of data – translational medicine • Changes in doctor’s information gathering skills • Increase in options for testing and treatment • Limited connectivity among providers with multiple providers involved in care • The Healthcare Gamble – who calls the play? 1
  17. 17. Why is HIT a high priority? • Practice of medicine that is predictive, personalized and pre-emptive • Resources are becoming limited – Decreasing number of providers – Smaller hospitals disappearing – Long waits for appointments – Few walk-in appointments available • Changing models for healthcare – Consumer driven health care – Health savings accounts – Shopping mall clinics, Doc in Box clinics – Wal-Mart, Google and Microsoft movement into healthcare 17
  18. 18. Why is HIT a high priority? • Volume of data about a patient has increased tremendously over the past decades – Increasing number of diagnostic tests – Increasing numbers and modality of images – Genetic testing – Access to data at place and time of decision making is critical – Informed decision requires data – Data must be used for multiple purposes – From bytes to kilobytes to megabytes to gigabytes to terabytes to petabytes to … 18
  19. 19. Why is HIT a high priority? • Sources and amount of knowledge have increased exponentially over the past decades – Amount of new knowledge introduced each year would take more than 200 years to assimilate into one’s practice reading and understanding two papers each night – Undergraduate and graduate education is based on out of date concepts – Continuing medical education is inadequate • We can’t learn fast enough to be effective • New knowledge requires new skills and new understanding 19
  20. 20. Focus • Improving quality, safety, efficiency, and reducing health disparities • Engaging patients and their families • Improving care coordination • Ensuring adequate privacy and security precautions for personal health information • Improving population and public health 20
  21. 21. Meaningful Use Preamble: “We recommend that the ultimate goal of meaningful use of an Electronic Health Record is to enable significant and measurable improvements in population health through a transformed health care delivery system. The ultimate vision is one in which all patients are fully engaged in their healthcare, providers have real-time access to all medical information and tools to help ensure the quality and safety of the care provided while also affording improved access and elimination of health care disparities. “
  22. 22. A “meaningful use” vision • A ubiquitous infrastructure that permits the creation of an Electronic Health Record in which all relevant data about an individual is aggregated across regional, state and national boundaries. • This EHR serves all sites, views, presentations and purposes relating to health and health care. • With a single data entry, the EHR meets all data reporting requirements as well as health care. Its every thing for every body. • The EHR becomes an active partner, not just a passive data repository. 22
  23. 23. A “meaningful use” vision • Comprehensive data for patient care • Integrates data with knowledge for cognitive support of both providers and patients • Accommodate heterogeneity of many sites of care • Empower persons to become involved in the healthcare • Provide operational value through aggressive interaction with patient and provider • The vision depends on understanding what problems you are trying to solve at the moment and at that location. 23
  24. 24. Meaningful Use • Primary objectives – stage 1 – Capture health information in a coded form – Use data to track key clinical conditions and communicate for care purposes – Implement clinical decision support tools – Report clinical quality measures and public health information to relevant government officials. • Primary objectives – stage 2 – Heighten quality management requirements – Move to the most structured format for information exchange 24
  25. 25. Meaningful use for providers (1/4) 1. Use CPOE 2. Implement drug-drug, drug-allergy, drug-formulary checks 3. Problem list of current and active diagnoses [ICD9-CM or SNOMED] 4. Generate and transmit prescriptions electronically 5. Maintain active medication list 6. Maintain active allergy list 25
  26. 26. Meaningful use for providers (2/4) 7. Record demographics 8. Record and chart changes in vital signs 9. Record smoking status [>13 yo] 10. Incorporate clinical lab test results as structured data 11. Generate lists of patients by specific conditions for use in quality improvement, reduction of disparities, research, outreach 12. Report ambulatory quality measures to CMS 26
  27. 27. Meaningful use for providers (3/4) 13. Send patient reminders for preventive follow-up 14. Implement 5 clinical decision support rules 15. Check insurance eligibility electronically 16. Submit claims electronically 17. Provide patients electronic copy of health information 18. Provide patients with electronic access to health information 27
  28. 28. Meaningful use for providers (4/4) 19 . Provide patients clinical summaries for each office visit 20. Exchange key clinical information 21. Perform medication reconciliation at relevant encounters 22 Provide summary care record for each encounter and referral 23 Submit immunization data to immunization registries 24 Provide electronic syndromic data to public health agencies 25 Have certified EHRS 28
  29. 29. 29 Stakeholder Interoperability Security/ Privacy Interoperability Functional Interoperability Semantic Interoperability Business Interoperability Technical & Syntactical Interoperability eHealtheHealth SystemicSystemic InteroperabilityInteroperability Communications Interoperability Legal, ethical and societal Interoperability Human/computer Interface Interoperability All impact patient safety and quality. International Interoperability
  30. 30. Clinical Information System • Computer-based system that is designed for collecting, storing, manipulating, and making available clinical information for healthcare delivery process. • May be limited to a single area (laboratory system, pharmacy system, imaging system, etc.) or they may be widespread and include virtually all aspects of clinical records (e.g. electronic medical records) • Provide a clinical data repository that stores clinical data such as patient’s history of illness and interactions with care providers. • Includes service functions such as Hospital Information Systems (HIS), functional systems (ADT, scheduling), departmental systems (LIS, RIS, PIS), Computerized Physician Order Entry systems (CPOE), ePrescribing systems 30
  31. 31. CIS is about … • Data and data management – The right data and only the right data – Complete, aggregated, timely, trustworthy, unambiguous, reusable, logically accessible – Event driven displays, logically driven • Knowledge and knowledge management – Evidence-based, up-to-date, appropriate, integrated into work flow, human and computer useable • Processes and work flow – Effectively and efficiently combines data with knowledge to enable optimum human decision-making – Monitor decisions and outcomes and provide safety checks, feedback and recommendations – Integrate data collection, presentation and decision support transparently into care delivery process 31
  32. 32. 32 Building the pieces EHRSCPOEe-Prescribing EHRS CPOE
  33. 33. Functional Components for CIS Planning Phase Data Transfer Store Presen- tation Collection Decision Support EHR Functions Data Exchange Other Systems Reports External Systems Query What is required to provide the interoperable connectivity? A suite of standards! 3
  34. 34. Planning • Defining and understanding problem to be solved • Defining and understanding requirements • Understanding data flow • Understanding work flow • Understanding linkages • Understanding data requirements 34
  35. 35. What are the tools for planning? • Start with defining use cases, story boards or scenarios in order to understand actors, interactions, activity diagrams, required data elements, data flow, trigger events, work flow, and decision support required. – Use cases are created by many groups including HITSP, HL7, IHE, CDISC, caBIG, VA, DOD, FDA, CDC, … • Package as Domain Analysis Model 35
  36. 36. Establish a common base • Need a common base so different groups can work independently yet still maintain interoperability • Start with a common Reference Information Model on which all data items, entities, acts, roles and relationships are defined. [ISO/HL7 RIM is a global standard.] [CEN 13606] • Data models [BRIDG], [CDISC], [caBIG] 36
  37. 37. Data elements • Fundamental component for data interchange • Key attributes include: – Unique persistent identifier code – ISO OIDs, UMLS, other ? – Precise definition validated by domain experts – Single terminology assigned to data element derived from controlled vocabulary – Data types (HL7/CEN/ISO) – Standard units (ISO/HL7) – Classifications – Defined value set – Synonyms – Other attributes • Centrally maintained; globally distributed; free to users; dynamically maintained; appropriate tools • ISO 11179 underlying standard 37
  38. 38. The Terminology Dilemma • SNOMED CT (clinical terminology) • LOINC (laboratory tests) • RxNorm (orderable clinical drug codes and formulations, mapped in UMLS) • Structured Product Labeling – dosing, potential interactions, etc. • VA NDF-RT (therapeutic classification, components, mechanism of action, physiologic effect, diseases treated) • FDA terminology sets (dosage form, packaging, routes, application methods) • MedDRA – adverse events • ICD-9 or ICD-10 for reimbursement and clinical • CPT – procedures • ICPC – primary care • MEDCIN – clinical terminology • IEEE medical devices • Local terminologies 38 Mapping is a workable solution but costs extra, is never synchronized, and loses information.
  39. 39. Approach to Semantic Interoperability 3 Terminology Master Data Element Set Value Sets NCI Thesaurus SNOMED-CT LOINC RxNorm ICD9/10 Others Attributes including code, name, definition, units, datatype, class, … Leveraged in interchange standards, data models, ontologies, etc. Data Elements collected in this facility Data Elements collected in this facility Healthcare facility A Healthcare facility B Business Agreement
  40. 40. Compound data elements • Attributes similar to data elements • Examples include blood pressure, heart murmur, titers • Expressed as – Templates (HL7) – Archetypes (openEHR) – Common Message Element Type (CMET) • Use XML syntax • Clinical Example – Blood Pressure • Systolic • Diastolic • Arm • Position of patient • Cuff size 40
  41. 41. Complex data elements • Attributes similar to data elements • Examples include drug sensitivity, microbiology results, body mass index, pulmonary functional tests • Administrative such as name, address, telephone • Extended into data groupings – patient admit profile – TB screen – Well-baby workup – Clinical trial component • Trigger-driven data transport profiles – Data required when a patient is transferred from hospital to nursing home • Disease Management Profiles 41
  42. 42. Document standards • Clinical Statements • Clinical Document Architecture (CDA) – Radiology reports – Patient summary – Discharge summary – Referrals – Claims attachments – Infectious Disease Reports • Continuity of Care Document (CCD) • Structured Documents 42
  43. 43. <ClinicalDocument> ... <structuredBody> <section> <text>...</text> <observation>...</observation> <substanceAdministration> <supply>...</supply> </substanceAdministration> <observation> <externalObservation> ... </externalObservation> </observation> </section> <section> <section>...</section> </section> </structuredBody> </ClinicalDocument> D O C U M E N T B O D Y Header S E C T I O N S Narrative Block E N T R I E S External References Major Components of a CDA Document
  44. 44. <section> <code code="48765-2" codeSystem="2.16.840.1.113883.6.1" codeSystemName="LOINC"/> <title>Allergies and Adverse Reactions</title> <text> <list> <item><content ID="A1">Penicillin - Hives</content></item> <item>Aspirin - Wheezing</item> <item>Codeine - Itching and nausea</item> </list> </text> <entry> <observation classCode="OBS" moodCode="EVN"> <code code="247472004" codeSystem="2.16.840.1.113883.6.96" codeSystemName="SNOMED CT" displayName="Hives"> <originalText><reference value="#A1"/></originalText> </code> <entryRelationship typeCode="MFST"> <observation classCode="OBS" moodCode="EVN"> <code code="91936005" codeSystem="2.16.840.1.113883.6.96" codeSystemName="SNOMED CT" displayName="Allergy to penicillin"/> </observation> </entryRelationship> </observation> </entry> </section> CDA, Release Two 4
  45. 45. <Results> <Result> <CCRDataObjectID> 2.16.840.1.113883.19.1 </CCRDataObjectID> <DateTime> <Type> <Text>Assessment Time</Text> </Type> <ExactDateTime> 200004071430 </ExactDateTime> </DateTime> <Type> <Text>Hematology</Text> </Type> <Description> <Text>CBC WO DIFFERENTIAL</Text> <Code> <Value>43789009</Value> <CodingSystem>SNOMED CT</CodingSystem> </Code> </Description> <Status><Text>Final Results</Text></Status> <section> <templateId root="2.16.840.1.113883.10.20.1.14" <code code="30954-2“ codeSystem="2.16.840.1.113883.6.1" codeSystemName="LOINC"/> <title>Laboratory results</title> <text> CBC (04/07/2000): HGB 13.2; WBC 6.7; PLT 123* </text> <entry> <organizer classCode="BATTERY" moodCode="EVN" <templateId root="2.16.840.1.113883.10.20.1 <id root="2.16.840.1.113883.19" extension=" <code code="43789009" codeSystem="2.16.840.1.113883.6.96" codeSystemName="SNOMED CT" displayName="CBC WO DIFFERENTIAL"/> <statusCode code="completed"/> <effectiveTime value="200004071430"/> Continuity of Care Document (CCD) • CCD maps the CCR elements into a CDA representation. 4
  46. 46. Continuity of Care Document (CCD) • CCD sections include: – Payers – Advance Directives – Support – Functional Status – Problems – Family History – Social History – Alerts (e.g. Allergies, Adverse Events) – Medications – Medical Equipment – Immunizations – Vital Signs – Results – Procedures – Encounters – Plan of Care 4
  47. 47. Data Collection • Machine interfaces • Personal health devices • Xforms • Clinical Guidelines • Electronic Data Collection (EDC) • Decision Support Algorithms • CDA • Integrated collection for multiple purposes 47
  48. 48. Communications standards • W3C, OMG, OASIS, IETF, HL7 others • Include XML,TCP/IP, HTTP, Web services, SOAP, CCOW • Supported by schemas, XSL, OCL, OWL, GIS • Web services – Web 2.0, Web 3.0 • WIFI standards • RFID standards – GS1 48
  49. 49. Data Interchange • Messages – Content – Trigger events – Routing – Timing and synchronization – Corrections – Business agreements – Security – Authentication 49
  50. 50. Data interchange standards • HL7 V2 and V3 for data and document transport • DICOM for imaging • HL7, NCPDP for prescription and related data • HL7, X12N for claims data • IEEE for medical device, sensors • OASIS for business data • IHE XDS • Document standards (CDA, CCR, CCD) 50
  51. 51. 51 HL7 v2.x Syntax MSH|^~&|REGADT|MCM|IFENG||199112311501||ADT^A04^ADT_A01|000001|P|2.4||| EVN|A04|199901101500|199901101400|01||199901101410 PID|||191919^^GENHOS^MR~371-66-9256^^^USSSA^SS |253763|MASSIE^JAMES^A||19560129|M|||171 ZOBERLEIN^^ISHPEMING^MI^49849^""^| |(900)485-5344|(900)485-5344||S^^HL70002|C^^HL70006|10199925^^^GENHOS^AN |371-66-9256|| NK1|1|MASSIE^ELLEN|SPOUSE^^HL70063|171 ZOBERLEIN^^ISHPEMING^MI^49849^""^ |(900)485-5344|(900)545-1234~(900)545-1200|EC1^FIRST EMERGENCY CONTACT^HL70131 NK1|2|||123 Industry Way|Shepeming^MI^49849^””^||(900)545-1200 |EM^EMPLOYER^HL70131|19940605||PROGRAMMER|||ACME SOFTWARE COMPANY PV1||O|O/R||||0148^ADDISON,JAMES|0148^ADDISON,JAMES||AMB|||||| |0148^ADDISON,JAMES|S|1400|A|||||||||||||||||||GENHOS|||||199501101410| PV2||||||||199901101400|||||||||||||||||||||||||199901101400 ROL||AD|CP^^HL70443|0148^ADDISON,JAMES OBX||NM|3141-9^BODY WEIGHT^LN||62|kg|||||F OBX||NM|3137-7^HEIGHT^LN||190|cm|||||F DG1|1|19||0815^BIOPSY^ACODE||00| GT1|1||MASSIE^JAMES^""^""^""^""^||171 ZOBERLEIN^^ISHPEMING^MI^49849^""^ |(900)485-5344|(900)485-5344||||SE^SELF^HL70063|371-66-925||||MOOSES AUTO CLINIC |171 ZOBERLEIN^^ISHPEMING^MI^49849^""|(900)485-5344| IN1|0|0^HL70072|BC1|BLUE CROSS|171 ZOBERLEIN^^ISHPEMING^M149849^""^| |(900)485-5344|90||||||50 OK|
  52. 52. 52 Model-based DevelopmentModel-based Development HL7 FrameworkHL7 Framework HL7 SpecificationHL7 Specification RIM Datatypes Data elements Vocabulary Templates Clinical Statements CoreStructured Content •V3 Messaging •CDA Specifications •System Oriented Architecture
  53. 53. Decision support • Knowledge reference framework and knowledge representation – Arden Syntax, Protégé, PRODIGY, vEMR, GELLO • Clinical Guidelines – Guideline Interchange Format (GLIF) [HL7] – Guideline Elements Model (GEM) [ASTM] • Disease Management Protocols • Evidence-based Care Plans • Infobutton [HL7] 53
  54. 54. EHR standards 54 • Functional Requirements – HL7 Draft Standard for Trial Use -2004 • Site variation – functional profiles • Content standards • Structure/architecture • Screens/presentation/icons • Document Registration, IDs, and Naming
  55. 55. Presentation • Independent of collection • Depends on event or circumstances, logically driven • Priority-based and filtered • Dashboards • Wireless devices • Smart phones 55
  56. 56. Identifiers • Provider identifier – National Provider Identifier [HIPAA] • Facility Identifier • Employer Identifier – IRS tax identifier • Person Identifier – Debate: Unique identifier vs identifying parameters • Patient registries - Master Patient Index (local, regional, national) • Record Locator Service 56
  57. 57. Medical and personal health devices • Interface standards for medical devices – Cable connected – Infrared – Wireless • Simple to sophisticated devices • Sensors • Terminology • Safety • Integration of SDOs – IEEE,CEN,DICOM, HL7, ISO 57
  58. 58. Supporting standards • Implementation manuals (HITSP, HL7) – Standard developers – System designers – Implementers – Users • Service-oriented architecture (HL7/OMG) • CCOW • Tool sets (HL7) – Data element/terminology servers – Transitional tools – Message/document creators 58
  59. 59. Other standard requirements • Repositories – Master data element set – Messages – CDA applications – DAMs – Clinical guidelines – Decision Support Algorithms 59
  60. 60. Application profiles • Integration profiles (IHE) • End to end information flow • Defined domain by domain • Includes concepts of persistent objects • Examples – Integrating the Healthcare Environment [IHE] – EHRVA Roadmap – ELINCS – CHI 60
  61. 61. Security/privacy Interoperability • Security, Privacy and Confidentiality – Authentication – Authorization – Role Based Access – Access logs – Audit Control – Digital signature – PKI – Integrity – Non-repudiation – Encryption – De-identification standards – Probability of risk vs value • ISO, CEN, HL7, others outside of health care 61
  62. 62. Privacy • No person should be harmed by the release of health-related data • No person should be denied proper treatment as a result of privacy concerns • Unique personal identifiers do not mean privacy is invaded; may be the opposite. • There is a social responsibility to share data. 62
  63. 63. 63 Planning Phase Data Data Exchange Data Store Reposi- tories Collec- tion Decision Support EHR Applica- tions Presen- tation ISO, CEN, HL7, CDISC, DICOM, IEEE, IHTSDO,LOINC, GS1, IHE, NCPDP, X12, openEHR, WHO/ICD, … Reports Audits Story boards Use cases Data models RIM MDF DAM BRIDG SOA Data Elements Data types Terminology Units CMETS Templates Archetypes Templates Clinical Statements CDA CCD CTS CDASH XFORM Templates CDA HL7 v2 HL7 v3 CEN 13606 IEEE DICOM ISO EHR FM PHR FM CCOW Geno- mics ISO Arden Syntax GELLO GLIF Info buttons Privacy and Security StandardsPrivacy and Security Standards IdentifiersIdentifiers ProfilesProfiles Queries Filters Medical Devices PHD New Needs Supply ChainSupply Chain Dem Lab Meds Probs AE CDW
  64. 64. What have we missed? • We have designed systems that mimic the paper based system; we have not taken advantage of technology; we have not stated or understood the problems we want to solve. • We have yet to answer the simple question: “What is the purpose of the Electronic Health Record, and how can it most effectively be used?” • Legacy is overpowering. We are dominated by the past; we have not been bold enough to tempt the marketplace with new vision. 6
  65. 65. 65 Creative use of HIT • Rather than using technology to identify medical errors, use technology to prevent medical errors. • Real time analysis of data to direct safe and quality care. – Dashboard displays at each level to focus on priority interventions. – Stop errors before they happen – Order timely and effective testing for disease • Proactive presentation of data with understanding of next event. • Not just show but inform.
  66. 66. Requirements • Comprehensive data on patients’ conditions, treatments and outcomes that will lead to safe, high quality, less expensive, and more efficient health care • Cognitive support for health care professionals & patients to help integrate – Patient-specific data – Evidence-based practice guidelines & research results • Accommodation of growing heterogeneity of locales for provision of care • Empowerment of patients and their families in effective management of health care decisions and their implementations 6
  67. 67. And more … • Effective and timely disease management with a personalized approach • Knowledge driven filters for presentation and exchange of data • Proactive recommendation of actions for both providers and patients • Determine factors that impact health including social, economic, and environmental situation. Focus on reducing impact of negative factors. • Influence the way providers practice medicine; it must change. 6
  68. 68. 68 What is the Potential? • Comprehensive data for patient care • Integrate data with knowledge for cognitive support of both providers and patients • Accommodate the many and heterogeneous sites of care, understanding how they fit together • Provide universal access to care • Empower personal involvement in healthcare • Provide operational value through aggressive interaction with patient and provider • The vision depends on understanding what problems you are trying to solve at that moment and at that location.
  69. 69. • Technologists – more appropriate use of technology; understanding the problems that need to be solved; better coupling with the clinical community • Clinical community – recognize what technology can do to significantly enhance health care; become the drivers for the use of eHealth; understand value of team approach thst includes the patient • Patient – Accept responsibility for one’s own health; become engaged in decision-making related to one’s own health; enhanced awareness of personal risk factors; practice prevention Requires paradigm shifts by stakeholders 6
  70. 70. The Enablement EHR Patient Care Personalized Care Community Care Public Health EHR – The Centerpiece of HIT 7 Data Creation Data Collection Data Interchange Data Aggregation Real-time integration of knowledge to direct and control collection of data. Proactive interpretation of data to direct behavior to enable quality care. Includes the service functions: HIS, CPOE, CDS, ePrescribing, billing
  71. 71. 71 Home HealthHome Health EmergencyEmergency CareCare IntensiveIntensive CareCare PrimaryPrimary CareCare NursingNursing HomeHome (LTC)(LTC) InpatientInpatient Electronic HealthElectronic Health RecordRecord Electronic HealthElectronic Health RecordRecord What is common and what is different among these sites of care? How do we effectively put this package together? SpecialistSpecialist CareCare Centralized vs Federated
  72. 72. 72 The Electronic Health Record • Architecture designed for fast and varied retrieval and presentation; independent of collection modality; anticipates query • Purpose is to enhance and enable the care of the individual; reusability of data is also a goal • Content focused on informational value; contains only data contributing to current and future health of person; store only what varies with patient; data warehouse satisfies complete and permanent storage for legal, other purposes • Structured for unambiguous clarity, understanding and interoperability • Support common core throughout varied sites of care • Patient-centric = one person, one EHR • Rich in functionality; varies with site • Includes workflow and process management
  73. 73. 73 EHR • Demographics – Why important? – Includes demographics, living environment, occupation, family history, preferences, quality and nature of life, stress and pain, geocoding • Clinical Data – Why important and what content? – Includes laboratory tests, diagnostic tests, diagnostic images, subjective and physical findings, diseases, behavior
  74. 74. 74 EHR • Treatments – Why important? – Understand why choices made; define expected results • Outcomes – Why important? – Feed back to influence treatment and enhance knowledge and understanding of disease and related factors • The EHR must contain everything anyone might need as part of the healthcare process.
  75. 75. 75 Structured Data Storage (1) • Demographics (including living situation, occupation, …) • Summary Problem List • Procedures • Studies (laboratory, radiology, diagnostic tests, …) • Therapies (prescription drugs, immunizations, blood products, alternative medicines, over-the- counter drugs, …) • Allergies, adverse events, drug reactions
  76. 76. Structured Data Storage (2) • Subjective & Physical Findings (history, physical exam) • Encounter (place, date_time, providers, problems, procedures, studies, therapies, S&P, supplies, disposition) • Providers involved in care • Scheduling • Protocols and disease management, trigger event flags • Patient education record 7
  77. 77. Patient-centric Electronic Health Record • Contains all data related to patient’s present and future care from all sites of care using a standard structured architecture with standard data elements. • Content – Structured Architecture • Data elements (compound, complex, templates) • Defined and mapped location for each and every data component • Organized by category of data – Organization independent of collection and presentation 7
  78. 78. 78 EHR • Architecture of EHR that can support at variety of uses. – Requires independence of data from application set • Data must be interoperable; it must be automatically reusable; it must be capable of integrating with new data to produce new value and understanding. • Granularity of data must start at lowest levels to permit effective computer analyses and understanding • Reevaluate patient care and treatment as new data enters incorporating old data
  79. 79. Electronic Health Record • Cognitive support provides intelligent interaction with content • Access requires meeting privacy requirements and a master patient registry and record locator. • Is an active partner with human in awareness, evaluation and decision making • Supports push, pull, interactive queries, packaged queries, event-based queries 7
  80. 80. 80 Download Process HL7 Message ID Double Encryption Silicon Encoder Sensitive Demographic Data Encrypted ID Identifying Data, name, address, etc. Identifying Data, Translated (e.g. Zip). Aggregated Summary Population EHR Summary Data ID
  81. 81. 81 EHR Interoperability Diagram Patient Encounter Provider EHR Database Personal EHR Summary EHR Profile Profile Profile Research Database Enterprise Data Warehouse Personal EHR Profile Disease Registry Profile Billing/Claims Institution EHR Database Research DatabaseResearch Database Disease RegistryDisease Registry Derived from master data element registry
  82. 82. Possible Scenario 8 Institutional Data Repository Data Clinical Data Warehouse Service Applications (CPOE, ePrescribing, etc.) Filter The Patient-centric Essential EHR Data Mining Other systems Serves Population Linkage Push, pull or query based Knowledge Database Contained in Regional HIE
  83. 83. Mining the Data Warehouse • Compliance and performance measures • Patient care/safety • Revenue • Research – Provides evidence for EBM – Outcomes monitoring shows effectiveness of treatment – New knowledge is translated quickly into practice 8
  84. 84. 84 Creation of aggregated EHR Institutional EHR Institutional EHR Institutional EHR The Patient EHR Personal Health Record Component of Population Health Record
  85. 85. Why 3 databases? • Institutional EHR – Permits site variation in data kept in record – Supports institutional business requirements – Used with service applications • Clinical Data Warehouse – Supports institutional research, quality and performance measures, compliance, patient safety • EHR – Is the essential EHR that serves as the patient-centric EHR and linked creates the population health record 8
  86. 86. 86 What is behind this model? • Standards • Infrastructure to support aggregation of data into a single patient record which requires … • Infrastructure to support a regional network • Infrastructure and linkage of regional networks to provide a virtual national network • A business case based on supported facts and includes a financial model that balances rewards with costs • A workable process that permits us to reach the destination in doable chunks • Understanding and creating the necessary linkages among stakeholders • State efforts blended into a common process that will support interoperability among states
  87. 87. 87 These views must serve … • Real-time connectivity to provide appropriate and controlled access to aggregated patient data. • Disease registries permit the monitoring and assurance of high quality care. • Research databases are derived for specific purposes and for specific periods of time. • Reimbursement is derived from clinical data, ideally in real time. • Accreditation, credentialing and statistical reporting are derived products. • The data warehouse contains all data for legal and archiving purposes. • Support consumer driven healthcare • Mandatory reporting such as immunizations, HAI, etc.
  88. 88. 88 Institutional EHR • Presents a provider-centric view of the patient’s record • Record contains patient data as well as intellectual content from provider of care; serves multiple purposes; may contain notes of provider only. • Patient should have access to data and be able to identify errors and require correction of errors • Content is driven by the institutional needs and varies from site to site • Should contain all data important for patient’s care plus other data required by the institution • Constitutes the billing record • There is a need to interchange data with other sites at which patient receives care • EHRS support full functionality for site care and management
  89. 89. 89 The Inpatient View • Deals with acute events and data; has mostly immediate value for decision making and intervention. After intervention occurs, data has less value. (Short persistence) • Required functionality deals primarily with service activities – ordering, results review, admission and discharge • CPOE systems particularly valuable to support services • Real-time decision support valuable • Inpatient version of ePrescribing, unit dose • Patient monitoring, medical device component of IT support • More tolerance for additional time required for IT activities • Administrative support provides value to physicians – rounding data • Intensive care even more acute. High payoffs for decision support; very short persistence of data
  90. 90. 90 The Inpatient View • Presentation of data for direct patient care – Ease documentation requirements – Evidence-based clinical pathways/guidelines/protocols – Multiple views of data, usually time-oriented – Automatic creation of discharge summaries • Task and workflow management – Automatic linkage to task management – Coupled to scheduling for radiology and diagnostic tests, e.g. – Patient location, patient status • Asynchronous communication among healthcare providers and workers
  91. 91. 91 Outpatient view • Data vary over a longer period of time. Data have a longer persistence. • Trend analyses are important. • Outpatient ePrescribing valuable; medication history key. • Focus on prevention and management of chronic disease. • Primary responsibility, with patient, for the patient’s overall health, i.e., medical home • Educational and behavioral modification • Depends on integration of data from multiple sources • Provider overhead for IT critical
  92. 92. 92 Personal Health Record  Permitting the patient to view an institution’s EHR is NOT a PHR  PHR has three components  Clinical data that will be similar to the summary health record plus data that is entered directly or by sensor into the PHR. Clinical data is downloaded from sites of care. Data may be uploaded to site EHRs.  Management of a person’s health including prompts for appointments, medication refills, screening tests, immunizations, etc. Decision support algorithms suggest what provider should be doing in terms of frequency of visit, tests, etc.  Access to knowledge that is tailored to a person’s needs and is driven by clinical data.  May be located at a site of care, at a PHR provider or on the person’s personal computer. Backup issues are important.
  93. 93. Personal Health Record • EHR data, including clinical data, demographic, images, genomic data, and biomarkers, is downloaded into PHR. • Decision Support algorithms analyze data to do risk assessment and create a personal health plan. With the entry of each new data, the risk factors and personal health plan are re-evaluated, and patient is advised of changes. • Manages health-related activities • Encourages behavioral modifications for better health 9
  94. 94. Personal Health Record • PHR includes data from personal health devices including sensors and hand-entered data. Examples include: – Exercise – Food intake by coded entry – Pain monitoring – Attitude and mood – Travel – Health journaling and health concerns 9
  95. 95. Personal Health • Disease Management accomplished as team effort with provider, health workers and patient. Disease management is personalized to the individual. Feedback to patient is important. • Medical Home concept provides a primary focus and specific responsibility for a patient’s health status and care. 9
  96. 96. 96 Risk Assessment Personal Health Plan PATIENT PHYSICIAN Home Enhancement Tools HEALTHCARE TEAM Lifestyle Treatments Procedures Other Investigations Clinical/Images Biomarkers Genomics Demographics Outcome Tracking Personalize Health Feedback loop Measurements
  97. 97. 97 Community or Public Health View • A summary record (essential EHR) from all sites and sources of care; RHIO EHR • Linkage of data for new sites of care as well as base for population surveillance, research, quality, analysis • Data arrives as identified data, available as de-identified • Data source for authorized providers; provides connectivity • Provides – Utilization data – Accurate and timely statistics about health and disease in population – Accurate reporting of events, disease and outcomes – Early discovery of outbreaks, new diseases, bioterrorist attacks – Immunizations, infectious disease tracking – Creation of “on-the-fly: randomized clinical trials – With geocodes, permits understanding statistics of health, spread of disease
  98. 98. Population Health • Enhanced understanding of the prevalence of disease by many categories – Using geocoding, by location to very detailed levels – By social and economic categories – By occupation – By race or ethnicity • Automatic reporting of public health data including immunization, infectious disease, other 9
  99. 99. Population Health • Health surveillance – Automatic reporting – Search robots looking locally, regionally, and nationally – Design models for predicting spread of disease and, more importantly, design processes to control spread of disease • Evaluate impact of health care strategies including immunization, good health behavioral programs, others 9
  100. 100. Population Health • Disaster Management – By knowing dependencies, appropriate interventions can occur before events – Data can be transported to alternative points of care – Disaster planning becomes easier and more effective 10
  101. 101. 101 Regional Center • Accommodates 3 to 5 million persons • Contains summary, aggregated data • Is a local database • Available 24/7 • Contains linkages to other centers so patients crossing boundaries of regions can be aggregated • De-identified data available for local or global queries and analysis
  102. 102. Enabling Model EHR EHR EHR EHR EHR EHR EHR EHR EHR EHR EHR RHIO EHR EHR EHR EHR EHR EHR EHR EHR EHR EHR EHR RHIO EHR EHR EHR EHR EHR EHR EHR EHR EHR EHR EHR RHIO POPULATIO N HEALTH NETWORK Serves as NHIN 102
  103. 103. 103 Regional Linkages Estimate approximately 100 such centers at implementation cost of $2m each and maintenance of $0.5M.
  104. 104. 104 RHIOs/HIEs Estimate approximately 100 such centers at implementation cost of $3m each and operational cost of $1 M. RHIO RHIO RHIO •Each RHIO provides backup for other RHIOs. •MPI identifies home RHIO
  105. 105. 105 Regional Health Information Organizations • Regional collaboration of multi-stakeholder organizations working together to connect healthcare communities with the goal of improving quality of care, safety and efficiency • Typical objectives – Develop community-wide health information exchange – Create healthcare portal with interoperable applications – Create a training and support infrastructure to ensure adoption of applications – Engaging payers in programs that align incentives appropriately
  106. 106. 106 National Healthcare Information Networks (NHIN) • To provide a secure, nationwide, interoperable health information infrastructure that will connect providers, consumers, and others involved in supporting health and healthcare. • E-health information to follow the consumer, be available for clinical decision making, and support appropriate use of healthcare information beyond direct patient care so as to improve health • De-identified regional data can be analyzed nationally in aggregate. There is a national MPI which permits authenticated and authorized access to RHIOs for legal health-related purposes. • Security and privacy are top priorities.
  107. 107. Why Global? • Maximize use of available resources; common effort and share; amplification of productivity • Enhances understanding of the problems • Share in creation and use of knowledge; clinical trials should be ubiquitous • Funding for research should be global and shared; cost should not limit availability • Mobility of disease; disease knows no borders • Mobility of people • Preserve culture • It just makes sense – the world is one! 107
  108. 108. Seamless Care Environment • What is it? • What is its value? • How do we get it? • When might we get it? • The art of the possible • Redefine possible 108
  109. 109. 109 Interoperability Gap Siloed Efforts Federal AgenciesSome progress
  110. 110. The final word • The ultimate criteria for success is not the number of patient records, is not the response time, and is not any technical characteristic. • The real criteria should be is it affordable, is it accessible, is it convenient, and is my life better. I want a high quality of life and then, I’d like a long, comfortable life. 110

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