health information technology and informatics: a significant evolution

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Answers for life. Restricted © Siemens AG 2014 All rights reserved. Health Information Technology and Informatics: A Significant Evolution John Glaser, PhD, CEO, Health Services, Siemens Healthcare

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John Glaser, PhD, CEO, Health Services, Siemens Healthcare . Health Information Technology and Informatics: A Significant Evolution. Disclosure. Speaker discloses that he has financial interests in and receives compensation from Siemens Healthcare. . Learning Objectives. - PowerPoint PPT Presentation

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Page 1: Health Information Technology and Informatics: A Significant Evolution

Answers for life.Restricted © Siemens AG 2014 All rights reserved.

Health Information Technology and Informatics: A Significant Evolution

John Glaser, PhD, CEO, Health Services, Siemens Healthcare

Page 2: Health Information Technology and Informatics: A Significant Evolution

Page 2

Disclosure

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

Page 3: Health Information Technology and Informatics: A Significant Evolution

Page 3

Learning Objectives

• At the conclusion of this activity, the learner should be better able to:

1. Understand the shift from a transaction-oriented to an intelligence-based electronic healthcare record

2. Understand the HIT system capabilities required to support accountable care processes

3. Understand the influence of the next IT revolution

Page 4: Health Information Technology and Informatics: A Significant Evolution

The Challenge: Recent Slowdown but Healthcare Costs Are Projected to Grow in 2014 and Beyond

Source Centers for Medicare and Medicaid Services (CMS): http://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/NationalHealthExpendData/downloads/highlights.pdfAdministration on Aging (AoA): http://www.aoa.gov/Aging_Statistics/Profile/2011/4.aspx

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^

Page 5: Health Information Technology and Informatics: A Significant Evolution

The Majority of an Average Provider’s Revenue Will likely Be Risk-Based in 10 Years

Source: The Advisory Board Company, Jan. 2014Page 5

Page 6: Health Information Technology and Informatics: A Significant Evolution

A Significant Shift in the Healthcare Business Model Is Underway

Being responsible for those who seek our services

Avoiding the sickest chronic patients

Treating all patients the same

Offering care at centralized facilities

Maximizing the use of resources & assets

Emphasizing volumes

Treating individuals when they get sick

Individual care providers

Best efforts

Being responsible for the needs of the community

Keeping groups of people healthy

Emphasizing outcomes

Applying appropriate levels of care at the right place

Offering care at sites convenient to patients

Customizing healthcare for each patients

Creating venues to provide special chronic care services

Collaborative teams of providers

High reliability organizations

Page 6

Page 7: Health Information Technology and Informatics: A Significant Evolution

Page 7

Payment Changes Will Lead to Different Care Emphases and Organizational Models

Page 8: Health Information Technology and Informatics: A Significant Evolution

Page 8

Providers will need to Manage and Improve Multiple Disease-Invariant Care Processes

Source: Best Care at Lower Cost, September 2012 Institute of Medicine; Smith, M Study Chair

Less than 50% of elderly patients are up to date on clinical preventive services Elderly patients with

co-morbidities require up to

19 medication doses daily

Every year, the average elderly patient sees 7 doctors across 4 practices

Specialties

Primary Care

Average surgery patient is seen by 27 different health care providers

RNs

MDs

Allied Health Less than half of non-

surgical patients follow-up with their primary care provider after discharge

1 out of 5 elderly patients are readmitted within 30 days

Preventive Self Management Outpatient Care Hospital Follow-up

Page 8

Page 9: Health Information Technology and Informatics: A Significant Evolution

Page 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.

Page 10: Health Information Technology and Informatics: A Significant Evolution

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

Page 11: Health Information Technology and Informatics: A Significant Evolution

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

Page 11

Retail World Wide Web Web-based product review, comparison and ordering

Banking Deregulation Funds Management

Content Distribution World Wide Web Music ecosystems; Free news; Craigslist

Health insurance ACA; CDHP Exchanges; Provider comparisons

Page 12: Health Information Technology and Informatics: A Significant Evolution

Three Categories of Fundamental Change in Information Technology Will Be Experienced

Move from Transaction-

based to Intelligence-based EHR

Learn to Leverage “Fifth IT

Revolution”

Ability toManage

AccountableCare

Processes

Page 12

Page 13: Health Information Technology and Informatics: A Significant Evolution

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

Page 14: Health Information Technology and Informatics: A Significant Evolution

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

Page 15: Health Information Technology and Informatics: A Significant Evolution

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

Page 16: Health Information Technology and Informatics: A Significant Evolution

Page 16

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

Page 17: Health Information Technology and Informatics: A Significant Evolution

Care Process Problems Will Become Intolerable

Extrapolated from various studies conducted by Partners Healthcare.

1,000 patientswho qualified for secondary prevention of high cholesterol

1,000 womenwith a marginally abnormal mammogram

360 who will not receive appropriate follow-up care

1,000 referrals 250 referring physicianswho have not received follow-up information four weeks later

1,000 patientscoming in for outpatient care

14 patientswith life threatening or serious ADEs

There Appear to Be:For Every:

380 will not have a LDL-C, within three years, on record

1,000 patientswho qualified for secondary prevention of high cholesterol

1,000 womenwith a marginally abnormal mammogram

360 who will not receive appropriate follow-up care

1,000 referrals 250 referring physicianswho have not received follow-up information four weeks later

1,000 patientscoming in for outpatient care

14 patientswith life threatening or serious ADEs

There Appear to Be:For Every:

380 will not have a LDL-C, within three years, on record

Page 17

Page 18: Health Information Technology and Informatics: A Significant Evolution

Page 18

Machine Reconciliation of Data Inconsistencies

Page 19: Health Information Technology and Informatics: A Significant Evolution

Page 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

Page 20: Health Information Technology and Informatics: A Significant Evolution

Three Categories of Fundamental Change in Information Technology Will Be Experienced

Move from Transaction-

based to Intelligence-based EHR

Learn to Leverage “Fifth IT

Revolution”

Ability toManage

Accountable Care

Processes

Page 20

Page 21: Health Information Technology and Informatics: A Significant Evolution

Accountable Care Management Processes

Page 21

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

Page 22: Health Information Technology and Informatics: A Significant Evolution

Page 22

Determine Variation from Plan: Readmissions Dashboard

Page 23: Health Information Technology and Informatics: A Significant Evolution

Concurrent Quality Intelligence: Cohort Monitoring

Page 23

Page 24: Health Information Technology and Informatics: A Significant Evolution

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

Page 24

Page 25: Health Information Technology and Informatics: A Significant Evolution

Three Categories of Fundamental Change in Information Technology Will Be Experienced

Move from Transaction-

based to Intelligence-based EHR

Ability toManage

AccountableCare

ProcessesLearn to Leverage “Fifth IT

Revolution”

Page 25

Page 26: Health Information Technology and Informatics: A Significant Evolution

Page 26

The “Quantified Self”

Page 27: Health Information Technology and Informatics: A Significant Evolution

Page 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

Page 28: Health Information Technology and Informatics: A Significant Evolution

Page 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.

Page 29: Health Information Technology and Informatics: A Significant Evolution

Tailoring Cancer Therapy

Cel

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Multi-parametric MRIPET/CT

Tissue Biomechanics (Elastography, Fibrosis)

Biologically Guided Radiotherapy

Chemo Therapy

Spectroscopy, CEUS

H&E stained, AMACR, CK903

Shape and Appearance

Circulating Tumor Cells

Ablative Therapy

Mol

ecul

ar L

evel

PhaseContrast

SNP, mRNA, Proteomics…

Cell/TissueSelf-Organization

Apoptosis

Immuno and Gene TherapyMolecular Networks

Patient Observations Computational Models Individualized Treatment

Tiss

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Histopathology

Imag

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and

Sens

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Mod

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nPage 29

Page 30: Health Information Technology and Informatics: A Significant Evolution

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

Page 31: Health Information Technology and Informatics: A Significant Evolution

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The EHR Must Be Designed for the Future; Not the Past

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

Manage populations Disease registries Referral management

Provides introspection Guideline adherence

assessment Quality measures capture

and real time display Financial optimization analyses

Page 32: Health Information Technology and Informatics: A Significant Evolution

Questions?Page 32