![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.
13](https://image.slidesharecdn.com/ehr-thekillerapp-120622034545-phpapp02/75/EHR-The-Killer-App-12-2048.jpg)
![A killer app delivers …
• Practice of medicine that is predictive, personalized,
pre-emptive, and participatory [the 4Ps]
• Accommodating increasing limitations of resources:
– 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
20](https://image.slidesharecdn.com/ehr-thekillerapp-120622034545-phpapp02/75/EHR-The-Killer-App-19-2048.jpg)
Uploaded byHealth Informatics New Zealand
EHR - The Killer App ?
The document discusses making the electronic health record (EHR) a "killer app" that accelerates widespread adoption. It argues that a paradigm shift is needed in EHR concepts, stakeholders, integration across domains, and faster adoption of technology. For the EHR to be a killer app, it must provide patient safety, efficient care, data management, knowledge management, and adaptive workflows. Overcoming challenges like standards, data sharing, and usability will help realize the promise of informatics to improve health globally.
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EHR - The Killer App ?
- 1. EHR – TheKiller App? HINZ Bringing the Electronic Health Record to Life 21 June 2012 W. Ed Hammond. Ph.D., FACMI, FAIMBE, FIMIA, FHL7 Director, Duke Center for Health Informatics Director, Applied Informatics Research, DHTS Associate Director, Biomedical Informatics Core, DTMI Professor, Department of Community and Family Medicine Professor Emeritus, Department of Biomedical Engineering Adjunct Professor, Fuqua School of Business Duke University Chair Emeritus, HL7 2
- 2. What is akiller app? An application that accelerates the adoption and ubiquitous use of the application. 3
- 3. Killer apps • Personal computer • World-wide web • Wireless networks • Google, Facebook, Social Networking 4
- 4. What needs tohappen to make the EHR a killer app? • Paradigm shift required in – Concept of EHR/EHRS – Recognition of all the stakeholders – Roles of stakeholders – Integration across all domains relating to health and healthcare – Creating common language – Relationship between venders and users 5
- 5. What needs tohappen … • Greater, quicker and appropriate use of available technology • Adopting more quickly to change • Faster creation and more effective use of required resources: applications, standards, workforce • Sharing data, knowledge, and processes – Cooperative competition • Stitch together current silos 6
- 6. Technology Advances • Mobiledevices – iPad and similar devices – Personal health devices • Ubiquitous wireless • Voice recognition – still coming but useful • Virtual reality – IBM’s Watson • Cloud computing • RFID 7
- 7. From molecules topopulation Molecular Clinical Patient Public Population Biology Research Care Health Health Individual, Family, Community, Societies Site of Care: Intensive care, inpatient, ambulatory, emergency department, long term care, home care Clinical Specialties Global 8
- 8. Components of communication •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 9
- 9. Application of HIT Understand Outcome Understand the Understand measurements Implement problem to be causes, factors, and data proposed solved. issues required to solution. monitor & solve Evaluate outcome Feedback Loop Articulate health IT problems with the precision of a scientific hypothesis. 10
- 10. The Spectrum ofProblem Solving • Science base of biology and medicine • Collection and interpretation of signals • Multiple (re-use) of data • Application of science and data in clinical care • Extension of clinical care to populations 11
- 11. Application Areas • Genetics – Genomics, proteomics, metabolomics, biomarkers, biomedical modeling… • Clinical Research • Clinical systems (HIS, CPOE, ePrescribing, CDW, …) – Clinical domain systems (cardiology, oncology, ,,,) – Electronic Health Records • EHR, EMR, PHR, Regional, National, Population • Public Health • Telemedicine – Mobile and personal medical devices • Educational Tools 12
- 12. Genetics • Gene mutationwill 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. 13
- 13. New Associations • EHRmust include genetic information – Biomarkers need to be included in EHR with meaning and actions included in an accompanying knowledge base – Gene mutations need to be included with links to meaning and actions including in an accompanying knowledge base – Phenotype sets need to be linked to a disease 14
- 14. Resulting Behavior Changes •Physicians need not become geneticists. Computers will use associated knowledge to suggest actions based on biomarkers, gene data, and phenotypes • Physicians will become the “action arm” with computers being the “thinking arm” • Physicians role is as a participating service 15
- 15. Changing demands • Agingpopulation, world wide. In U.S., a citizen becomes 65 years old every 6 seconds. Over the next 30 years, we will add 20 million persons to the over 65 category. • Current health care systems cannot handle this volume. • The role of primary care giver role will be shared with less trained persons. 16
- 16. Changing role ofpatients • Increased participation and responsibility for one’s own health • Requires new methods of education, monitoring, networking, data access – Personal Health Records and patient portals • Addressing health disparities • Treating social and environment and cultural issues 17
- 17. A killer appdelivers … • Patient safety • Efficient and effective health care delivery • Health surveillance, bio-defense and natural disaster health data management • Real quality, reduced uncertainty, trust • Cost containment in face of increasing costs of healthcare • Accommodation of an aging and mobile population • Effective management of chronic disease • Higher quality of life as well as longevity 18
- 18. A killer appdelivers … • Equal access to care • Consumer sophistication and knowledge in health; mobility • Increasing continuous 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? 19
- 19. A killer appdelivers … • Practice of medicine that is predictive, personalized, pre-emptive, and participatory [the 4Ps] • Accommodating increasing limitations of resources: – 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 20
- 20. A killer appaccommodates … • 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 exabytes to zettabytes to … 21
- 21. A killer appaccommodates … • Sources and amount of knowledge have increased exponentially over the past decades • NLM indexes over 1 million documents each year • 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 22
- 22. Killer app EHRprovides … • 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 23
- 23. Requires paradigm shifts •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 that 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 24
- 24. EHR – TheCenterpiece of HIT Data Creation EHR Data Collection The Enablement Patient Care Data Interchange Data Aggregation Personalized Care Community Care Public Health Includes the service Proactive interpretation Real-time integration of of data to direct behavior functions: knowledge to direct and to enable quality care. HIS, CPOE, CDS, e control collection of data. Prescribing, billing 25
- 25. Enabling Better Health EHR systems must be adaptive. We need to be able to include any new data element (self- defined) without additional programming. Exchange of data should be driven by filters or a defined set of business rules based on data elements. Systems should use Enterprise Architecture (SOA) approach in order to accommodate new functionalities and new technologies. 26
- 26. Possible Scenario Knowledge Database Institutional Clinical Data Data Data Data Mining Repository Warehouse Push, pull or query based Service The Filter Applications National (CPOE, ePres Patient-centric Linkage cribing, etc.) Essential EHR Other Contained systems in Regional HIE 27
- 27. EHR • Architecture ofEHR must support at variety of uses. – Requires independence of data from data collection and application set • Data must be interoperable; it must be automatically reusable, capable of continuous use • 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 28 data enters incorporating old data
- 28. EHR Issues • Usabilityis key – minimize keystrokes for input and query • Every user, regardless of level, must understand the value of the data • Think ahead of user – alert fatigue can be avoided by walking behind when appropriate and alert only what is important • Capture data from least expensive source but maintain quality 29
- 29. EHR Issues • Freetext is necessary as modifiers but attached to structure • Cognitive support provides intelligent interaction with content • Is an active partner with human in awareness, evaluation and decision making • Supports push, pull, interactive queries, packaged queries, event-based queries 30
- 30. Challenges • Privacy issues;recognize 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 • Addresses provenance 31
- 31. Match Computational Approachto Complexity of Data Automation Evidence- based Work lists advisors Decision Connectivity Support Disease Aggregate Stead WW. Electronic Health management EHR Records. In: Rouse WB, Cortese DA, eds. dashboards Engineering the system of healthcare delivery. Tennenbaum Institute Series on Enterprise Systems, Vol. 3. Amsterdam: IOS Press; 2009. Data Mining
- 32. U.S. Focus • HIEand interoperability (probably the #1 discussion issue in the town-hall session) • Usability • Vendor relations and vendor accountability • Need for reimbursement reform before providers will benefit from HIT • Data sharing, as well as privacy, consent, and cases of breach 33
- 33. U.S. Focus • Storiesof successful overhead reduction • Use of more “scientific methods” of research and testing to determine future mandates, such as Meaningful Use, Phase 3 • Patient buy-in and collaboration 34
- 34. Informatics • Within Informaticsis the power to bridge existing 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. 35
- 35. 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! 36
- 36. The Final Word •Informatics and HIT holds the promise for a better world. • Limited resources requires working together and sharing everything. • We must speak the same language with the same meaning. • Connectivity and communication is essential. • Leadership and commitment of governments are a necessity. • Will the EHR become the killer app in our lifetime? 37