Health Information Technology and Informatics: A Significant Evolution

1. John Glaser, PhD, CEO, Health Services, Siemens Healthcare Health Information Technology and Informatics: A Significant Evolution

2. Disclosure • Speaker discloses that he has financial interests in and receives compensation from Siemens Healthcare.

3. Learning Objectives • At the conclusion of this activity, the learner should be better able to: • Understand the shift from a transaction-oriented to an intelligence-based electronic healthcare record • Understand the HIT system capabilities required to support accountable care processes • Understand the influence of the next IT revolution

4. The Challenge: Recent Slowdown but Healthcare Costs Are Projected to Grow in 2014 and Beyond • Acceleration in health spending growth expected to be 6.1% in 2014 with annual growth of 6.2% in 2015 and beyond • Improving economy, ACA coverage expansion, and demographics contribute to increasing growth rate • Total healthcare spending will reach $2.9 trillion in 2013 • By 2022, numbers of uninsured people will drop by 30 million • Will increase cumulative health spending by approx. $621 billion • Demographic trends contribute to increasing costs. Americans ages 65 or older will comprise 19.3% of population by 2030, up from 13% in 2010 ^ 7.5 million Source Centers for Medicare and Medicaid Services (CMS): http://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/NationalHealthExpendData/downloads/highlights.pdf Administration on Aging (AoA): http://www.aoa.gov/Aging_Statistics/Profile/2011/4.aspx

5. The Majority of an Average Provider’s Revenue Will likely Be Risk-Based in 10 Years Source: The Advisory Board Company, Jan. 2014 Page 5

6. A Significant Shift in the Healthcare Business Model Is Underway Individual care providers Collaborative teams of providers Treating individuals when they get sick Keeping groups of people healthy Emphasizing outcomes Emphasizing volumes Applying appropriate levels of care at the right place Maximizing the use of resources & assets Offering care at sites convenient to patients Offering care at centralized facilities Treating all patients the same Customizing healthcare for each patients Avoiding the sickest chronic patients Creating venues to provide special chronic care services Being responsible for those who seek our services Being responsible for the needs of the community Best efforts High reliability organizations Page 6

7. Payment Changes Will Lead to Different Care Emphases and Organizational Models

8. Providers will need to Manage and Improve Multiple Disease-Invariant Care Processes 1 out of 5elderly patients arereadmitted within 30 days Every year, the averageelderly patientsees7 doctorsacross 4 practices RNs MDs Less than 50% of elderly patients are up to date on clinical preventive services Allied Health Less than halfof non-surgical patients follow-upwith their primary care provider after discharge Elderly patients with co-morbidities require up to 19 medication doses daily Specialties Average surgery patient is seen by 27 different health care providers Primary Care Preventive Self Management Outpatient Care Hospital Follow-up Source: Best Care at Lower Cost, September 2012 Institute of Medicine; Smith, M Study Chair Page 8

9. It Is Not Possible to Address these Challenges without a Foundation of Sophisticated IT Today’s providers are taking on risk arrangements and need to proactively manage the care and wellness of their patient population by: • Managing care over a continuum • Managing the health of populations and individuals • Supporting care teams with evidence-based processes and advanced analytics • Engaging patients (and their families) to take the necessary steps to improve their health • Improving the efficiency and effectiveness of core operations And providers must accomplish all of this across an ecosystem with multiple IT systems.

10. Core Technology Components Will Be Required An electronic health record that spans the continuum of care A revenue cycle and contracts management application that spans the continuum of care Sophisticated business intelligence and analytics Systems that enable interoperability between closely affiliated providers Technologies that support the engagement of patients Services that enable maximum leverage of healthcare IT investment Page 10

11. Material Changes in Business Models, Technologies and/or Environment Lead to Significant Changes in and Industry’s Core IT Platforms Page 11

12. Three Categories of Fundamental Change in Information Technology Will Be Experienced Ability to Manage Accountable Care Processes Move from Transaction-based to Intelligence-based EHR Learn to Leverage “Fifth IT Revolution” Page 12

13. For many Years, the Core Focus of the Electronic Health Record Has Been the Transaction • Transactions include: • Writing a prescription • Retrieving results • Documenting a visit • This focus addressed the core challenges: • The serial treatment of patients (outpatient) • The coordination of diagnostic and treatment activities (inpatient care) Page 13

14. For many Years, the Core Focus of the Electronic Health Record Has Been the Transaction The care setting emphasized: Transaction speed and efficiency Ease of use Good coverage of care diversity The benefits were the reduction in transaction problems: Legibility Medication errors Documentation completeness Page 14

15. The Challenge: Quality Remains Uneven “ Last September, in its report on “Best Care at Lower Costs: The Path to Continuously Learning Health Care in America,” the IOM noted that patients get effective care only about half the time, that gaps in coordination remain widespread, that serious preventable medical errors are common, and that perhaps more than 30 percent of healthcare costs could be avoided as a result of improving quality and efficiency. ” U.S. Senate Committee on Finance Testimony, June 26, 2013 Improving Health Care Quality: The Path Forward, McClellan, Mark B Page 15

16. Our Understanding of the Complexities of Disease is Accelerating – There Is too much to Know

17. Care Process Problems Will Become Intolerable For Every: For Every: There Appear to Be: There Appear to Be: 1,000 patients 1,000 patients coming in for coming in for 14 patients 14 patients with life threatening or serious ADEs with life threatening or serious ADEs outpatient care outpatient care 360 360 1,000 women 1,000 women who will not receive appropriate who will not receive appropriate with a marginally with a marginally follow follow - - up care up care abnormal mammogram abnormal mammogram 250 referring physicians 250 referring physicians who have not received who have not received 1,000 1,000 referrals referrals follow follow - - up information four weeks later up information four weeks later 1,000 patients 1,000 patients 380 380 who qualified for who qualified for will not have a LDL will not have a LDL - - C, within three years, C, within three years, secondary prevention of high cholesterol secondary prevention of high cholesterol on record on record Extrapolated from various studies conducted by Partners Healthcare. Page 17

18. Machine Reconciliation of Data Inconsistencies

19. The Emphasis Will Shift from Transaction Support to Include Intelligence Support – Core Objectives • Guide clinical diagnostic and therapeutic decisions • Ensure sequence of care activities conform to the evidence and performance contract requirements • Monitor the execution of core clinical processes • Capture, report and integrate into EHRs quality and performance measures • Support the interactions of the care team

20. Three Categories of Fundamental Change in Information Technology Will Be Experienced Ability to Manage Accountable Care Processes Move from Transaction-based to Intelligence-based EHR Learn to Leverage “Fifth IT Revolution” Page 20

21. Accountable Care Management Processes The key is managing the care plan of the individual and stepping back and looking at the population in aggregate. Populations will include those that are a readmission risk, are undergoing a procedure bundle or have a chronic disease

22. Determine Variation from Plan: Readmissions Dashboard

23. Concurrent Quality Intelligence: Cohort Monitoring Page 23

24. Creating Approaches to Moving Population Management Applications to the Next Generation A shift from a generation characterized by: Management of only the sickest/high risk patients Static risk categorization Single disease/condition focus based on simple data values and events “List” generation with significant manual work Retrospective To a generation characterized by: Management of all patients Risk categorization that follows a patient’s evolving risk Multi-disease/condition focus using evidence-based care plans Significant process automation and leverage of the care team including the patient Concurrent

25. Three Categories of Fundamental Change in Information Technology Will Be Experienced Ability to Manage Accountable Care Processes Move from Transaction-based to Intelligence-based EHR Learn to Leverage “Fifth IT Revolution” Page 25

26. The “Quantified Self”

27. Characteristics of this Era The era is characterized by: • Networked, powerful processors almost everywhere and on almost anything • Diverse array of sensitive and specific “sensors” • Massive amounts of data and novel methods for analyzing it • Software delivered as a service • A wide variety of collaboration, community and knowledge resources This era will enable us to: • Use large data volumes to perform “real world” analysis and experiments • Orchestrate complex processes • Deliver new services, e.g., location aware and location invariant services • Extend and enrich fundamental human activities such as being a member of a community and searching for information

28. Comparison of Relative Risk of Medications Using EHR Data Source: Brownstein J, Murphy S, Goldfine A, Grant R, Sordo M, Gainer V, Colecchi J, Dubey A, Nathan, D, Glaser J, Kohane I. Rapid identification of myocardial infarction risk associated with diabetic medications using electronic medical records. Diabetes Care 2010;33(3):526-31.

29. Tailoring Cancer Therapy Patient Observations Computational Models Individualized Treatment Organ Level Shape and Appearance Biologically Guided Radiotherapy Multi-parametric MRI PET/CT Tissue Level Tissue Biomechanics (Elastography, Fibrosis) Spectroscopy, CEUS Ablative Therapy Modeling and Estimation Imaging and Sensing Decision Making, Therapy Selection and Optimization Histopathology Circulating Tumor Cells Cell Level Phase Contrast Apoptosis H&E stained, AMACR, CK903 Cell/Tissue Self-Organization Chemo Therapy Molecular Level Molecular Networks Immuno and Gene Therapy SNP, mRNA, Proteomics… Page 29

30. Who Is this Person and What Are They Trying to Do?

31. The EHR Must Be Designed for the Future; Not the Past Manage populations Disease registries Referral management Provides introspection Guideline adherence assessment Quality measures capture and real time display Financial optimization analyses • Support collaboration • Inter-disciplinary and multi-disciplinary teams • Shared worklists • Enable personalized care • Treatment decision support • Predictive models • Intelligent order sets and documentation templates • Enables reliable processes • Workflow engine • Health information exchange

32. ? Questions Page 32