Beyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Scalable Data Computing for Healthcare and Life Sciences Industry
1. Scalable Data computing for
Healthcare & Life Sciences
Industry
Prashant Avashia
Senior Architect,
Storage & Software Defined Architectures
May 2017
2. Engaging the Healthcare
Consumer
of patients want to interact with doctors on mobile
devices80%
Enhance the Healthcare
Consumer
90% of patients say they would use an app “prescribed” by their
doctor
The industry is facing real
challenges
• Aging populations
• Increased incidence of chronic disease
• Empowered patients and consumers
• Unsustainable cost pressure
• Government policy, regulation and
mandates
• Security & Data Privacy
What’s driving your strategy?
of patients want to become engaged in their own health
and wellness88%
90%
Encourage the Healthcare
Consumer
of patients would use an app prescribed by their
doctor
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Observations:
1. Existing IT infrastructures not designed to support aggressive patient data growth due to burden of chronic diseases on ageing populations,
unsustainable rise in demand for healthcare services, and significant increases in cost of services.
2. Existing IT infrastructures not designed to drive performance for systems that are continuously streaming data, finding correlations, creating
hypotheses, learning through experience and, ultimately, driving better decisions.
2015 Actuals Published
CAGR
2019 Projections
16 Hospitals 8.1% 20 Hospitals
5,500+ Physicians 9% 7,480+ Physicians
3,800 Beds 8% 5,000 Beds
1.9 Million Patient visits 8% 2.5 Million Patient visits
131,000+ in-patient surgeries 2.6% 143,000+ in-patient surgeries
24,800+ babies delivered. 3.3% 28,100+ babies delivered
564,000+ Emergency Room visits. 6.8% 717,500 Emergency Room visits
154,000 inpatient admissions 3.3% 174,400 inpatient admissions
1.2 Million lab tests, and diagnostic procedures 10.3% 1.7 Million lab tests, and diagnostic procedures
1800 Research studies, and published results 9% 2,400 Research studies, and published results
Data Source: 2015 Annual Report for a US based Healthcare Institution.
Patient Data Volumes: Aggressive Growth compels New Analytics
approaches
4. Welcome to the era of Cognitive Health
|
The Data Explosion
Medical data is expected to
double every 73 days by 2020.
The Great Unknown
80% of health data is invisible to current systems
because it’s unstructured. Watson and IBM
Storage can “see it.”
Protecting Images
Hospitals are required by law to
keep images for 7 years, but many
keep them longer.
Broad Consensus
81% of healthcare executives familiar with Watson
Health believe it will positively impact their
business.
Source: http://www.ibm.com/smarterplanet/us/en/ibmwatson/health/
5. IBM Bluemix Garage 5
Data is the new basis for value creation.
Less than 10% can deploy digital intelligence at the pace needed
Source: FROM DATA TO DISRUPTION: INNOVATION THROUGH DIGITAL INTELLIGENCE
IBM-sponsored report by Harvard Business Review Analytic Services, 2016
say data
fragmentation
gets in the way84%
require faster
data & analytics
to compete90%
Drive Business
Outcomes
Capture the Time Value
of Data
Change the Game
DATA-DRIVEN VALUE
are unable to
collaborate on
common data80%
6. New Era Workloads
Demand Next Generation Automation
Continuous Optimization
Policy
PolicyPolicy
Policy
Adaptive approaches to
infrastructure automation
Static and manual assignment
of IT resources
Software Defined Environment
Application Aware Policy
OLD NEW
Defined by Software for the Cloud
Move to more “Automation and Analytics” – IBM Strengths!
Infrastructure Level Services
7. Store everywhere. Run anywhere
Ensure data availability, integrity and security
Client Challenge
Phenomenal data growth. Data Management Challenges.
Growth of on-premise data is challenging to manage
Need the ability to store secure data offsite
Need reliable, secure, cost-effective solution
8. Distilling the Client Requirements
Client Challenges
High Speed for Big Data – Architectures to ingest high volume data at high speeds.
Data Sharing for Global Collaboration
Genomic Data is doubling every 12 months – budgets are not!
Software Defined Solution Features
Universal data access
A single authentication scheme
Data dispersal and erasure code for faster rebuild times
End-to-end checksum to catch errors
Data protection through Snapshots, Replication, Backup, and/or Disaster Recovery
Data encryption and cryptographically secure erase
Integration to Spectrum Family
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A scalable, high-performance data and file management solution,
which optimizes heterogeneous storage resource utilization, while
helping to reduce hardware and software costs as well as
providing ease of administration through a single global
namespace”
Virtualized Access to Data
Spectrum Scale Software
Virtualized, unstructured data, Centrally
deployed and managed
Clients access data in parallel .
Heterogeneous fiber channel/block
storage with different capacity and
performance attributes
Spectrum Scale is software:
• implementing a highly scalable distributed
parallel POSIX (e.g Linux+Windows+AIX) file
system,
• and building upon any block storage (from
local disk to SAN-attached, not necessarily
from IBM),
• with advanced data management features
built in to it that go well beyond the
capabilities of traditional file systems
• and with features layered on top of it to
make that storage accessible through NFS,
CIFS, Hadoop and Object protocols.
Spectrum Scale: What is it?
IBM Spectrum Scale is the Software defined
Infrastructure for Global Data Management
10. Leveraging IBM Software Defined Infrastructure
Modality
Instruments
Hadoop/
Big Data
Electronic
Health Records
Genome
Sequencers Non Dicom
On / Off premises – Hybrid Cloud
New
Workloads
Optimized
Data
Flash Hybrid Tape Object
IBM Software
Defined
Infrastructure Data placement on-demand & by policy
Resource Management
Protect investment in existing resources
Genomic Tools capture and control all clinical, genomic & Radiological Imaging data including DICOM images and unstructured data
Data access via global namespace that pools and optimizes storage resources
Data Where it Needs to Be When it Needs to Be there
Embrace New Workloads to gain new insights that create innovation
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11. IBM Cloud Object Storage
Redefines availability, security and economics of data storage
Always-on
Availability
Tolerates even a catastrophic regional outage without down time or intervention.
Continuous availability architecture.
Legacy cloud providers place the burden of data management and cost for creating and maintaining an out of
region second copy on the client.
Built-in
Security
Protects against digital and physical breeches
Provides strong data-at-rest confidentiality by combining encryption and information dispersal.
Better Cloud Storage
Economics
More cost-efficient than competitors.
Includes Enterprise class support, at no additional cost.
Simplicity
Immediate consistency (v. eventual consistency) makes application development simpler.
Integrated with other cloud services in the IBM Cloud, IBM Bluemix, IBM Watson, IBM Video Services
More flexible, open interfaces: Supporting both S3 and OpenStack Swift
No “black boxes”: Full transparency of how the technology delivers durability, availability, security and more
12. IBM Spectrum Scale & IBM Cloud Object Storage Solution
--Delivered in an Enterprise Imaging Environment
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Scientific Computing in Biomedical ResearchReference Architecture: For Personalized Medicine...
With Imaging, Sequencing, Analytics
14. We are on a Transformative Journey to Cognitive Health
Environment
Variables
Traditional Departmental
Deployments
(Unstructured Data)
Enterprise Data Lakes delivering
Analytic Insights
(by IBM Spectrum Scale)
Cognitive Information
Architecture
(by IBM Watson)
Clinical Example Clinical Advice
Tumor Mass suspected in the X-Ray
Clinical Informatics Guidance
How many tumors/cancers of certain kind &
size were treated in last six months?
Evidence based Medicine
Is the cancer shrinking faster than other
patient histories? Tailor clinical services
if shrinkage is (or is not) occurring at the
expected rate.
Architectural Topology Traditional Architecture
Enterprise Imaging Archives to store
unstructured data.
Software Defined Architecture
Data Lakes supporting Analytic Applications.
Cognitive Solutions Architecture
Leverages SDI as a foundation with
flexible services – based on Natural
language, Algorithms, Machine Learning
& Analytical Reasoning capabilities
based on learned experience
Results Busy work
Unpredictable outcomes
Improved process & workflow efficiencies
Higher quality of care & minimized capital
expenditures.
Healthier, happier Populations
Longer, more productive lives.
17. Notices and disclaimers
continued
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