The Wonderful World of Informatics

Transcription

1 The Wonderful World of Informatics VI Jornadas Universitarias de Sistemas de Informción en Salud 31 de octubre, 1 y 2 de noviembre 2011 W. Ed Hammond, PhD, FACMI, FAIMI, FAIMBE, FHL7 Director, Duke Center for Health Informatics Professor, Community and Family Medicine Professor Emeritus, Biomedical Engineering Adjunct Professor, Fuqua School of Business Chair Emeritus HL7 and Chair HL7 USA Nothing to disclose

2 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,

3 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 - the atom of information. Shannon estimated the digital information in a text, a photograph, a record, and even in the Library of Congress. 3

4 Information connotes a cosmic principal of organization and order, and it provides an exact measure of that.* Information is a measure of uncertainty. Information is entropy a measure of disorder. Information is surprise. * Werner Loewenstein 4

5 Who uses information? People Patient care Clinical research Computer Science Engineering Business Law English Economics The Omics World Public Policy Entertainment Marketing Public health Biology Pharmacy Governments Banks Travel Armies 5

6 Presentation This talk is about the wonderful world of informatics; how information is the life blood of all of health and health care; how informatics bridges the silos of the current systems; how informatics eliminates redundancy and conflicts; and how informatics reduces chaos in the health care process. 6

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

8 What is? Bio Biomolecular Biomedical Medical Clinical Health Nursing Translational Genomic Veterinary Dental Imaging Radiology Consumer Behavioral Informatics 8

9 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 Clinical Specialties Global 9

10 Predictions for the next decade We will discover 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 $500 or less Children will have their DNA sequenced at birth Most adults will have their DNA sequenced Genomic data coupled with personal health data will have a strong impact on the pharmaceutical industry. Drugs will be more targeted. Health care model will change as will the role of the provider 10

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12 Genetics Gene mutation will identify many treatable genes such as Hirschsprung s disease, muscular dystrophy, and cystic fibrosis Drug treatments are already influenced by genomic information The anticoagulant drug warfarin has a narrow therapeutic window - too high a dose, patient can bleed to death; too low a dose, clots remain unclotted. Genetic information [certain versions of two genes CYP2C9 and VKORC1] are highly predictive of rate of metabolizing warfarin. 12

13 Informatics Genetics and informatics can lead to health care that is Personalized Predictive Preventive Participatory 13

14 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 14

15 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 15

16 Biomolecular Informatics Patient care target disease identification (rare diseases), knowledge requirements, genetic information to influence treatment and to enable personalized care Population Health research in understanding genetic disease factors related to ethnicity, geographic, cultural, and environmental factors 16

17 Clinical Research Informatics Within domain 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 reuse 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 17

18 Patient Care Within domain 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 18

19 Patient Care Public Health - addressing community needs, accepting responsibility for promoting good health behavior Population Health accepting responsibility for populations in their areas of responsibility, understanding prevalence of disease, characteristics of their population, addressing society needs including disabled, aging and underserved 19

20 Public Health Within domain 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 20

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 21

22 Global Health Shared knowledge, resources Control of epidemics Support in natural disasters Shared outcomes, evidence 22

23 The Individual Personal Health Records loaded from each and all sites plus individual entries New models Self care Medical home Behavior modification Social networks 23

24 EHR New types of data Genomic Image Waveform Patient-generated Video Within the next 5 years, over 50% of the data contained in a patient s EHR will be nonclinical 24

25 Patient issues Complete and accurate medications list Lack of patient identifier limits ability to do medications reconciliation. Error rates are between 30 and 75%; error rate should be 0%. Maintenance of allergy lists Failure to treat and control chronic diseases Failure to deliver appropriate care Patient-centric care is holistic care 25

26 Other functions enabled by informatics Patient-centric problem lists Clinical data warehouse Dashboards Decision support Geospatial coding 26

27 Virtual Reality Duke School of Nursing 27

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29 The virtual doctor Purpose is to answer any question a person might have What do these numbers mean to me in terms of what can I do and what can t I do? What is the impact on my life? Use avatars for both doctor and patient Marcus Welby? My avatar looks like me 29

30 Challenges Acceptance that cooperation and sharing is a win-win situation Single ontology that links all domains; that is an open process; that uses a common process in which expertise is the dominant factor; identifies stewardship of each ontological term Ontology removes all ambiguity in associated attributes; ontology matches terms that are used in the process of research and care 30

31 Challenges Solves privacy issues; recognizes that personal control of data may harm creation of new knowledge and seamlessly connecting the contributing domains for the most effective care Identification and implementation of standards for data and data exchange Controlled and purposeful exchange of data Quality of data is insured through process, algorithms, and certainty factor 31

32 Return on Investment How much will enablement of this vision cost? What is the cost of good health care? What is the cost of bad health? Faster, less expensive, more honest research through informatics 32

33 Informatics Within Informatics is the power to bridge these silos and significantly advance health, longevity and quality of life for all citizens of the world. This achievement can only happen through the global community acting together, sharing costs and responsibility. The inequalities of the world, the globally growing aging population, and economics demand this action be taken. 33

34 Conclusion / Summary The pace of technology has been paced by Moore s law: roughly, computational power doubles approximately every two years Use of technology informatics has not kept pace. The future of health care depends on our getting ahead of the curve That step demands a step change revolution, not evolution! 34