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The Magic of Informatics 8 th International Symposium on Health Informatics and Bioinformatics September 25, 2013 W. Ed Hammond, PhD, FACMI, FAIMBE, FHL7,

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Presentation on theme: "The Magic of Informatics 8 th International Symposium on Health Informatics and Bioinformatics September 25, 2013 W. Ed Hammond, PhD, FACMI, FAIMBE, FHL7,"— Presentation transcript:

1 The Magic of Informatics 8 th International Symposium on Health Informatics and Bioinformatics September 25, 2013 W. Ed Hammond, PhD, FACMI, FAIMBE, FHL7, FIMIA Director, Duke Center for Health Informatics Director, Applied Informatics Research Duke University Medical Center

2 Presentation This talk is about the magic of informatics, a field that has grown from a newborn to a mature adult. Informatics is the life blood of all of health and health care; it bridges the silos of the current systems; it has the potential to enable a better and longer life for all classes of people. HIBIT 20132

3 Information is what our world runs on. Man has evolved from the food-gatherer to the information gatherer. Information pervades science from top to bottom, transforming every branch of knowledge. Marshall McLuhan, 1967 HIBIT 2013 3

4 Our age is the Information Age – younger than some of us. Claude Shannon created that age in 1948 when he made information a science; he gave it a definition; he gave it units of measurement – the bit. Shannon estimated the digital information in a text, a photograph, a record, and even in the Library of Congress. HIBIT 2013 4

5 Information connotes a cosmic principal of organization and order, and it provides an exact measure of that. - Werner Loewenstein Information is a measure of uncertainty. Information is entropy – a measure of disorder. Information is surprise. 5HIBIT 2013

6 Who uses information? Patient care Clinical research Computer Science Engineering Business Law English Economics Academics The ‘Omics World Public Policy Entertainment Marketing Public health Biology Pharmacy Governments Banks Travel Armies Who doesn’t? HIBIT 2013 6

7 Components of informatics Data –Semantically interoperable, high quality, timely Knowledge –Appropriate, accessible, comprehensive Information –Actionable, focused, clear, reduces uncertainty Judgment –Human input based on experience and observation; an intangible component Wisdom –Individuals trained in how to use data, knowledge, and information HIBIT 20137

8 Why data? –Patient care –Research: Clinical Trials –Analytics: Health and Business –Behavior modification –Health Information Exchange –Knowledge acquisition –Learning health –Evidenced-based medicine –Clinical Effectiveness Research –Patient education –Health surveillance –Disease management Almost every initiative in health and health care involves the use of data. HIBIT 20138

9 Technology Technology has made the most explosive gain in contribution to the field of informatics From main frame to minicomputers to personal computers to laptops to mobile devices to smart phones, technology has far outdriven the capability of applications to exploit. 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. 9HIBIT 2013

10 What has technology added? Moore’s Law – faster, bigger, cheaper computers and communications than ever Wireless, global communication that instantly connects the world Small, mobile devices that are ubiquitous More knowledge than we know how to use The ability to aggregate all data about a person from all sources A rich mixture of media to enhance our understanding of disease and its cure HIBIT 201310

11 Value of HIT Efficiency in data capture Continuity of care – aggregation of data from all sites of care 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 11HIBIT 2013

12 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 Identification of all factors involved in impacting disease and quality of life 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 12HIBIT 2013

13 A Bit of History After almost 50 years of development of the electronic medical record, we seem to be struggling with many of the same problems today. During that same period, technology has made unbelievable progress – new drugs, new treatments, new tests, communication satellites with almost instant world communication, transportation advances with rapid and easy world travel, creation of a global community. Applications in healthcare have not kept pace with the technology. 13HIBIT 2013

14 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 14HIBIT 2013

15 From molecules to population Molecular Biology Clinical Research Patient Care Public Health Population Health Individual, Family, Community, Societies Site of Care: Intensive care, inpatient, ambulatory, intensive care, emergency department, long term care, home care Site of Care: Intensive care, inpatient, ambulatory, intensive care, emergency department, long term care, home care Clinical Specialties Global HIBIT 201315

16 Biomolecular Informatics Genomics, proteomics, metabolomics, pharmacogenomics, computational biology, basic science Understanding the genetic basis of disease; establishing role of genetics in treatment Within domain – registries, data sharing, analytic tools, indices, provenance, query tools, data capture tools, other Clinical research – requirements, targeted diseases, clinical trials, biobanks HIBIT 201316

17 Informatics role Two persons can have the same gene mutation but react differently. Informatics enables the exchange of data between genetic research and personal health data, including environmental and demographic data may help identify the difference. Clinical research is involved to conduct the clinical trials that lead to the answer HIBIT 201317

18 Clinical Research Informatics Registries, controlled data exchange among researchers, provenance, data capture tools such as REDCap, query tools such as i2b2, analytics tools, management of clinical trials Patient care – continuing use of patient care data, shared collection of data, cohort identification, discovery of target drug requirements, early translation of research into routine patient care Population Health – understanding of prevalence of disease, identification of new drug targets 18HIBIT 2013

19 Patient Care Informatics Meaningful use of data, EHR systems, data exchange, decision support, supporting safe and high quality health care effectively and efficiently at best cost, interoperability among all sites of care, embracing preventive and personalized care, clinical data warehouses, creation of new knowledge, supporting patient-centric EHRs Adverse events fed back to clinical research and ‘omics research 19HIBIT 2013

20 Public Health Informatics Acquisition of data and structured reports, tracking of disease outbreaks, control of epidemics, insuring appropriate immunization and vaccinations, analytics, infectious disease control, disaster management Patient care – source of data from health surveillance and disease management 20HIBIT 2013

21 Population Health Within domain – understand disease prevalence, understanding environmental factors through use of geospatial coding and impact on health, insuring adequate resource funding by governments; help determine priorities in health HIBIT 201321

22 The Individual Personal Health Records Patient Reported Outcomes New models of care –Personalized, predictive, preventive, participatory –Self care –Medical home –Behavior modification Social networks HIBIT 201322

23 Global Health Shared knowledge, resources Control of epidemics Support in natural disasters Shared outcomes, evidence HIBIT 201323

24 The Enablement EHR Patient Care Personalized Care Community Care Public Health EHR – The Centerpiece of HIT 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 24

25 EHR Trends … Evolving data Biomarker data ‘Omics data Imaging data Environmental data Geospatial data Video data Person-generated data Behavioral 25 Content of EHR will change significantly to include these types of data. Within the next 5 years over 50% data contained in patient’s EHR will be non-clinical.

26 EHR Trends - Access The real value of data is not in the collection as much as it is in the access. Query should be the service product of our IT systems. Navigation of databases is a large challenge but an essential component of a functional system. 26

27 EHR Trends … Creation of knowledge Data mining – uses data to create knowledge Compliance and performance measures Patient care/safety Research –Provides evidence for EBM –Outcomes monitoring shows effectiveness of treatment –New knowledge is translated quickly into practice –Clinical trials Integrity Sharing 27

28 EHR Trends – Use of knowledge 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 28HIBIT 2013

29 EHR Trends … Decision Support All decision support is data driven. Decision support algorithms are shared in a global registry. Sharing of rules and algorithms demands interoperable data. Every new input of data triggers decision support algorithms that reevaluate the status of a patient. Effectiveness of treatment is evaluated by decision support. Evaluation of decision support algorithms is continuously driven by data analytics. 29

30 EHR Trends … Workflow Driven by collection and use of data Involves many persons serving in different roles Collection process is distributed across stakeholders Transition of care is a critical time: effective data exchange is key. 30HIBIT 2013

31 The Growth of Big Data Global data is growing at rate of 59% per year Source: Wall Street Journal, 2013 31HIBIT 2013

32 Big data EHR growth –from bytes to kilobytes to megabytes to gigabytes to terabytes to petabytes to exabytes to zettabytes to yettabytes to … Less is more Filters that are purpose and event driven New methods of presentation Overload and fatigue Awareness HIBIT 201332

33 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. 33HIBIT 2013

34 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. 34HIBIT 2013

35 Health Analytics Learning Health System EHR Clinical Trials Genomic Biomarkers Clinical GIS Environmental Images Shared Data Big Data Interoperability Meaningful Use Continuous Use of Data Aggregated Patient-centric Patient Reported Outcomes 35HIBIT 2013

36 How do we make all of this fit together? Institutional Data Repository Data Clinical Data Warehouse Service Applications (CPOE, ePrescribing, etc.) Filter The Patient-centric Essential EHR Data Mining Other systems National Linkage Push, pull or query based Knowledge Database Contained in Regional HIE 36HIBIT 2013

37 Health Intelligence Team: Future Possibilities 37HIBIT 2013

38 Systems Approach to Care Evidence-based Medicine Consistent Process Visualization of Results vs. Plan Iterative Improvement Outcomes Evidence-based Medicine Consistent Process Visualization of Results vs. Plan Iterative Improvement Outcomes Source: W.W. Stead

39 What is GIS?  A geographic information system (GIS) integrates hardware, software, and data for capturing, managing, analyzing, and displaying all forms of geographically referenced information.  GIS allows us to view, understand, question, interpret, and visualize data in many ways that reveal relationships, patterns, and trends in the form of maps, reports, and charts.  Ultimately helps answer questions and solve problems by allowing us to look at our data in a way that is quickly understood and easily shared. Source: Sohayla Pruitt 39HIBIT 2013

40 GIS Core Capabilities: Visualization 40HIBIT 2013

41 The Health Star Source: David Borland Visualization HIBIT 201341

42 Virtual Reality Duke School of Nursing HIBIT 201342

43 What’s Coming We are discovering a genetic linkage to most diseases. Early discovery of disease-causing mutations will influence care with better outcomes. Cost of DNA sequencing will drop to $300 or less. Children will have their DNA sequenced at birth. Most adults will have their DNA sequenced and the data contained in their EHR. Genomic data coupled with personal health data has had a strong impact on the pharmaceutical industry. Drugs will be more targeted to the individual. Dosing is becoming driven by genetic data. 43HIBIT 2013

44 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. 44HIBIT 2013

45 Thank you!

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