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Imagine Imaging in the New world Jay Srini [email protected] 412 760 9593

CHIME Lead Forum 2015 - NYC

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Page 1: CHIME Lead Forum 2015 - NYC

Imagine Imaging in the

New world Jay Srini

[email protected]

412 760 9593

Page 2: CHIME Lead Forum 2015 - NYC

MU and Imaging

• Stage 2 MU requirements call for remote viewing systems to allow referring physicians or others access a patient’s EMR to view images and reports from various departments.

• It calls for the integration of patient access to health information and images via patient portals to increase patient engagement. This may play a larger role in the future, as patients with chronic conditions like diabetes and heart failure will be asked to take a more active role in their healthcare with remote monitoring programs. C

• Clinical decision support and computerized physician order entry (CPOE) is now being required to improve patient safety, eliminate illegible written orders, record all orders in one location, reduce redundant tests and to justify use of expensive tests or imaging exams.

• VNAs also can help enable remote access to patient data using mobile devices, such as tablets by physicians on rounds, anywhere in the hospital, on the road or at home. This may lead to a reduced reliance on workstations in fixed locations, allowing greater workflow efficiency and improved patient communication and education.

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The world is changing as

we see it

• The Past The future

• Hospital Centric Patient Centric

• Episodic Continuous

• Fee for Service Value Based

• Sick Care Well + Sick

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Collaborative Care

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http://www.graycons.com/wp-

content/uploads/2013/03/eHealth-

Technologies-Unified-Approach-to-

Sharing_White-Paper.pdf

Page 11: CHIME Lead Forum 2015 - NYC

What is needed

• No more Data Siloes

• Enterprise – Community View

• Universally Acessable

• Break the Glass model

• Do not ignore Privacy Rules

• Respect the patient- Epatient Dave

• Data by itself is useless unless converted to actionable information.

Page 12: CHIME Lead Forum 2015 - NYC

Data Liquidity

• In 2001 the IOM report "Crossing the Quality

Chasm" and the NCVHS report "Information for

Health" were released and they provided the context

for the development of information systems used to

support health-supporting processes. Both had as

their goals, implicit or explicit, to ensure the right

data is provided to the right person at the right time,

which is one definition of "Data Liquidity

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Data liquidity is not just about

Technology

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Culture Trumps technology

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Data is King

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Data Liquidity does not mean

Chaos

• Data Management

Image Life cycle Management

Storage Tiers

Prefetch

Compliance and Auditing cannot be Ignored!!

Authentication Rules are not a matter of choice!

Page 17: CHIME Lead Forum 2015 - NYC

Key Considerations

• Regulatory Compliance

• Risk Management

• Data Trustee/Stewardship

• Centralized Data management

Page 18: CHIME Lead Forum 2015 - NYC

XDS-Technology is not the

real issue

• Cross-Enterprise Document Sharing (XDS)

facilitates the registration, distribution and access

across health enterprises of patient electronic health

records.

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DouG Laney

VALUE

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Beyond Volume Variety and Velocity

https://datafloq.com/read/3

vs-sufficient-describe-big-

data/166

https://datafloq.com/read/3vs-sufficient-

describe-big-data/166

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Just not radiology

• A fully integrated cardiovascular department with a CVIS enables staff to remain in one area and have complete visibility of a patient’s prior history along with current procedural data/imaging. Most of the market-available solutions have structured reporting modules that have been optimized to improve cardiologists’ reporting workflow with reduced steps of data entry and conventional dictations.

• Structured templates for echo, pediatrics, peripheral vascular, cath lab and several others are offered by many solutions in the market, and this has truly become a standard practice for increased performance. -

• See more at: http://www.dicardiology.com/article/essential-elements-new-cardiovascular-information-systems#sthash.GvwkY3u0.dpuf

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Figure 1. A logic diagram of an example of the field of radiogenomics for breast cancer using digital mammography and DCE MRI.

Rivka Colen, Ian Foster, Robert Gatenby, Mary Ellen Giger, Robert Gillies, David Gutman, Matthew Heller, Rajan Jain, Anant

Madabhushi, Subha Madhavan, Sandy Napel, Arvind Rao, Joel Saltz, James Tatum, Roeland Verhaak, Gary Whitman

NCI Workshop Report: Clinical and Computational Requirements for Correlating Imaging Phenotypes with Genomics

Signatures

Translational Oncology, Volume 7, Issue 5, 2014, 556–569

http://dx.doi.org/10.1016/j.tranon.2014.07.007

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Imaging + Genomics

• The early assumption that DNA sequencing alone could explain disease and help define specific therapies has given way to a more nuanced view that epigenetic processes, the cellular matrix, and aspects of the intracellular milieu such as micro RNA and proteomics are elements that modulate gene expression and are the scaffold of the diseased state (4).

• Many in the basic-science community admit, at least in a perfunctory way, that genotype manifests itself as phenotype (here read “imaging”) and that the one may inform the other. Also, there is increasing recognition that there is not only substantial heterogeneity between tumors but also within tumors (5)

• . In one study (6), two-thirds of the mutations found in single biopsy samples were not uniformly detected in all the sampled regions of the same patient’s tumor. Here again, imaging has the potential to help noninvasively characterize the whole tumor, all tumors in the patient, and tumors at multiple time points over the course of treatment. However, there are few investigators who have yet pursued that potential connectivity in the published imaging literature. It is also true that federal program announcements and grant funding review committees have been slow to acknowledge or encourage investigation of that science intersection.

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Figure 2. Radiological and histological feature extraction and correlation to genomic data. Following identification of the contrast

enhancing region (top-left) or cancer nuclei (right) various imaging features can be extracted. Using corresponding genomic dat...

Rivka Colen, Ian Foster, Robert Gatenby, Mary Ellen Giger, Robert Gillies, David Gutman, Matthew Heller, Rajan Jain, Anant

Madabhushi, Subha Madhavan, Sandy Napel, Arvind Rao, Joel Saltz, James Tatum, Roeland Verhaak, Gary Whitman

NCI Workshop Report: Clinical and Computational Requirements for Correlating Imaging Phenotypes with Genomics

Signatures

Translational Oncology, Volume 7, Issue 5, 2014, 556–569

http://dx.doi.org/10.1016/j.tranon.2014.07.007

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Surgical Simulation

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Unlike mammography and breast ultrasound, breast MR imaging assesses the blood

flow to a tumor. The blood flow to cancers is different from the blood flow to normal

tissue, and the radiologist uses this information to determine which lesions need to be

biopsied, and which can be left alone. This is valuable information, but it presents a

slew of data to the radiologist that must be interpreted.

In particular, the radiologist must identify that region of the lesion that has the most

suspicious type of blood flow. This is a tedious process when done by hand, but is

relatively straightforward once the computer has generated an “angiogenesis map.”

The map is a color representation of the kind of blood flow in a given tissue, and is

superimposed on the anatomical images. Much like a weather map is used to indicate

regions with particular temperatures or heavy precipitation, so too can an

angiogenesis map identify tissue associated with malignant-type blood flow. The

angiogenesis map is an intuitive tool that allows the radiologist to quickly identify the

tissue that is most suspicious for a malignancy. - See more at:

http://www.itnonline.com/article/cad-improves-breast-mri-

workflow#sthash.3N7ZFS2n.dpuf

Sophisticated data needs sophisticated manipulation

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Mmodal catalyst- software to bring

images to actionable information

• NLP

• Standard Radlex

• Structured info

• Locked with radiologist narrative

Critical findings

Billing issue

PQRS reporting

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From data to Information

knowledge to wisdom

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Proactive Predictive

Precise care

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It is the Workflow Stupid

• It is not about Dicom Vs non Dicom

• It is not about VNA

• It is not about petabytes or yottabytes

• IT is not about Private cloud or Public Cloud

• It is strictly about

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So the future of Imaging is about

Expect the Unexpected

• Consolidate the VNA

• VNA is beyond the ologies..

• Coordination and Collaboration

• Workflow is key

• Outcomes and quality

• Behavior change

• All leads to the Triple aim objectives of cost quality and Experience

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http://nocamels.com/2013/10/israeli-tech-

puts-3d-holographic-heart-in-the-doctors-

hand-to-save-lives/

A view of things to come