Big Data in Healthcare

Raj DalalPrincipal – CC&C Solutions

Founder - BigInsights

.• A Consulting company, established in 2002 with primary focus on Enterprise

and Solution Architectures.• Providing thought leadership in as a Gold member• Operating globally through dedicated professional teams

• Drawing on international best practices from TOGAF ® & Other standards • Providing Professional Services to numerous enterprises with a primary focus

on:– Health services– Public Sector– Financial Services & Insurance– Supply Chain & Distribution– Education– IT service providers

Some of our worldwide customers

.

Fortune 500 Corporations, Leading Government Agencies, Global Service Providers, Universities

New era of accelerated transformation

Big Data

Primary data pools are at the heart of the big data revolution in healthcare

Source: McKinsey Global Institute

Big Data: Foundation for evolution of healthcare

Source: Hewlett Packard

Empowering the Individual/Patient

Personalised consumer healthcare

Source: Hewlett Packard

Big Data is changing the paradigm: New value pathways in healthcare

Source: McKinsey Global Institute

Application of early successes at scale could reduce US healthcare costs by $300-450Billion

Big Data Use Cases

Source: Flutura

Key word Analysis - Keyword mining of doctor’s/Lab transcripts using text mining and co-relations to patient outcomes

Source: Flutura

Source: Flutura

Telemedicine Analytics

Source: Flutura

Apriori sequence analysis to define new clinical pathways

Source: Flutura

Source: Flutura

Predictive Analytics• Improve patient experiences through continuum of care by

examining referral patterns across providers

• Track spread of infection inside hospitals through well-placed sensors; predict risk of outbreaks through monitoring of multiple data sources

• Clinical revolution: predictive analytics for diagnosis, risk assessment, prognosis, therapeutic management

• Learn best ways of contacting patients to ensure that they follow treatments, nutrition guidelines, and can recognize symptoms

Healthcare providers must develop a range of big data analytics capabilities

Case StudyUS Depart of Veterans Affairs

Overview of Project

• US Veterans are committing suicide at an alarming rate• Some disturbing statistics:

– 22 US veterans per day commit suicide– Suicide rates are roughly double those of general US population– 21% of overall suicides in USA are veterans– 12,500 calls per month to veterans crisis line (30% are related

of suicide)

• Durkeim project aims to proactively predict negative events such as suicide in the US veterans population and prevent it.

Outcomes

• Dedicated to applied research on predictive suicide risk:– Multidisciplinary team of psychiatrists, US Veterans

Administration and AI (Machine learning)

• Phase 1:– Developed linguistic-driven prediction models to estimate

the risk of suicide. (from VA medical records).– Generated Datasets of single keywords and multi-word

phrases and constructed prediction models using machine learning algorithms

Outcomes – Phase 2

• Sucidality prediction at scale

• Expand the data available for VA physicians with real time social media feeds from 100,000+ US Veterans to medical database

• Clinicians get a dashboard to monitor risks based on this realtime data

• Can provide real-time triage upon detection of critical event

Durkheim Project (Phase 2) - ProactiveOpt-In Signup•Enabled privacy controls for user•Both ‘opt-in’ and ‘opt-out’ options are supported•Users are informed of the social networks that are enabled

Realtime monitoring of SocialMedia:•Facebook post and statusUpdates•Twitter •Google+ (coming soon)

Clinician dashboard•Patients are listed by with overall risk rating/statistics and clinical notes•Patients flagged for risk ie Green (Low) to Red (High)•Status updated every 1 minute

Drill Down:- Suicide Ideation Rating- Time Series/Trend (Mental health ticker) -- Risk against other patients

Clinician dashboard

Source content:Can view the social media updates

Clinician notes:Combined analysis of patients self-reported text as well as observations

TechnologyMedical Database residing behind the medical firewall at Geisel School of Medicine where participant data is stored for analysis by medical professionals according to Human Subject Study/ HIPAA privacy rules

Information technology:• Hadoop technology use to store potentially massive datasets• Attivio used for unstructured search • Cloudera Search and Cloudera Impala being introduced into their machine learning framework to simplify the environment and reduce data movement

Statistical tools• Bayesian counters (B-counts) used for on-line near realtime model building and prediction. Underlying technology for B-counts is HBase.

• Initial prediction algorithm is Naïve Bayes (NB). The framework is currently being extended to incorporate Nearest Neighbours (NN) and Bayesian Network (BN) learning algorithms.

Benefits/Metrics

• Phase 1 - Data model’s predictive accuracy was statistically significant (at least 65% accurate)

• Proactive platform for refining predictive models and suicide prevention at scale

Summary

OutcomesReduction in number of

Veterans committing suicide

MetricsData model’s predictive

accuracy was statistically significant (at least 65%

accurate)

New Style of IT in healthcareShaped by cloud, Big Data, security and mobility

EA in Healthcare transformationNational Health vision, strategy and blue print for Healthy Nation

Users portal- 720 degree view

Business LayerTraditional | Collaborative | Outcome and Data Driven

Application LayerAdministration | Drug control | Tele Medicine | Real time and Continuous

Monitoring (Internet Of Things) (Services - based Models)

Data LayerStructured | Un-Structured | Real-Time | Bigdata

Technology LayerOn Premises -> Service-based Models (Cloud) | Hadoop | NoSQL

CC&C Solutions Focus

• Big Data integral in Enterprise Architecture transformation

• Leadership in Open Group – standardisation (Platform 3.0)

• EA / TOGAF / Archimate training and consultation• Experiences in HealthCare domain– F100 customer (Johnson & Johnson)– E-health in various Asian countries and NSW Health

Thank You / Questions

Contact : Raj Dalal / raj@ccandcsolutions.com / @BigInsights