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PREDICTIVE ANALYTICS

LPCA Annual Educational Conference

Baton Rouge, LA

October 7-10, 2015

We Know What You’ll Do Next Summer

9/30/2015

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Predictive Analytics…defined

• Area of data mining that deals with extracting information from data and using it to predict trends and behavior patterns. Wikipedia

• “…helps connect data to effective action by drawing reliable conclusions about current conditions and future events.” Gartner Research Director Gareth Herschel

• “Using data and software to better your odds.” Jonathan

• “I skate to where the puck will be.” Wayne Gretzky

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www.ameri100.com

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Predictive Analytics…Context

http://visual.ly/look-history-and-future-predictive-analytics-and-big-data

• 1930s-1940s: decoding messages, Manhattan Project

• 1950s-1960s: weather forecasts, FICO applies predictive modeling to risk, SAS Institute starts as US Ag project

• 1970s-1990s: pricing for stock options, FICO, Amazon and eBay go live (1995) , Google applies algorithms to web searches (1998), ‘moneyball’ utilized in baseball (1998)

• 2000-Present: Natural language processing, traffic, consumer pricing, social media, low cost server farms, 2.5 quintillion bytes of data each day, growing demand

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BIG Data

BIG Data

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Big Data at Work: Dispelling the Myths, Uncovering the Opportunities. Thomas Davenport. 2014

Really BIG DATAHealthcare data is expected to exponentially grow from 500 petabytes in 2012 to 25,000 petabytes in 2020 (AMIA).

That’s the equivalent of 500 billion four-drawer filing cabinets.

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Examples

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Examples

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Examples

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Examples

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Examples

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Examples in Health Care

• BYU/Utah University – predicts premature and full term births based upon blood sample at 24 weeks

• Washington State Hospitals – detected billing errors to realize $2 million in missed charges

• BCBS of Tennessee – predicts from claims data what resources individual members will need

• FICO – predicts patient compliance to drug prescriptions

• http://www.riskprediction.org.uk/ – predicts risk of death in surgery based upon aspects of you and your condition

• Insurance Companies – predicts elderly customers’ deaths within 18 months in order to offer appropriate services

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• PA tools are able to predict which customers are likely to be unhappy before they actually contact company

• Reducing the rate of post-surgical infections

• Wearable technology

• “Deadline” app for Apple’s wellness center, HealthKit

• Developing workforce numbers and specialties

• New types of data being used to support accountable care include information from mobile devices (42 percent of respondents), social media (32 percent) and unstructured clinical data (29 percent) Health Data Management

• Personalized Population Health

Examples in Health Care

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• Louisiana Medicaid is utilizing analytics to identifymisdiagnoses and inappropriate pharmaceutical prescribing

• Track Patient Flow/Observation Bed Management

• Kaiser Permanente used analytics to identify ways to improveoutcomes in cardiovascular disease. The discoveries resulted in fewer lab tests and office visits, saving $1 billion annually

• Daily care coordination

• Duke Medical School used analytics to determine ideal neonatal stays

• HRSA is working with IBM to explore predictive possibilities based upon UDS…Financial, Operational and Leadership

Examples in Health Care

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Priorities for Providers1. Ensuring consistent and comprehensive data capture,

and reinforcing the culture of data sharing

2. Improving technology and governance strategies for clinical and operational data

3. Putting the data to use and focusing on quality and outcomes-based protocols to improve patient care

The ‘big data’ revolution in healthcare. Center for US Health System Reform, Business Technology Office. McKinsey & Company. January 2013

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Limitations

1. More data does not equate to more insight

2. Insight and value are not the same

3. Ability to interpret data varies based on the data itself

4. Implementation itself may prove a challenge

• Google Flu Trends (GFT) – over predicted

• Arab Spring – did not predict

• Netflix $1 million model – did not implement

• Workforce recruitment down to one question?

4 Essential Lessons for Adopting Predictive Analytics in Healthcare. David Crockett, Ph.D. Health Catayst. 2013

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Nat’l Association of Medicaid Directors (NAMD) Data Analytics for Effective Reform, April 2014

• Arizona, Colorado, New Jersey, Tennessee, Texas, and Wisconsin

• No two states store/use/structured the same

• Developing capacity

• System upgrades

• Conflicting roles/resources

• Senior management buy in/support

• Multiple/outside data sources

• What data to use? Medicare complimentary?

• Realign payment incentives

• CMS Office of Information Products and Data Analytics (OIPDA)

http://medicaiddirectors.org/

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Return on Investment?

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Methodology"Most people use statistics the way a

drunkard uses a lamp post,

more for support than illumination."

• SAS, SAP, IBM, Oracle, etc

• R, Orange, Weka, Hive, Python, etc

• RapidMiner, STATISTICA, Mathematica

• Microsoft Office 365, Google Predictive API

• Electronic Medical Records

• Hadoop, Spark

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http://visual.ly/look-history-and-future-predictive-analytics-and-big-data

Expectations…

• Cloud based exchanges

• Analytics for everyday decisions

• Curing rare diseases

• Policing

• Anticipatory analytics

• Mass marketing campaigns are dead

• Data licensing over purchasing

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What are you thinking about?

• MIT/Sloan search produced 131 results

• Google search produced over 3,400,000 results

• Certified Analytics Professional

• Web list of 49 PA educational options

• PA job ads up 1500%

• NSF funding 17 big data research projects worth $31M

• North American PA industry in 2013 was $697 million;

in 2019, expected to be $2.3 billion

• By 2018, expected 2 million workers short with required knowledge and expertise

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Predicting Analytics

“The future ain’t what it used to be.” Yogi Berra

•http://healthdatapalooza.org/ – summers in D.C

•Big Data in Pharma – Sept 2015 in Boston

•Predictive Analytics World: Health Care – Nov 2015 in Boston

•Data 360 for Health Care Executive – Dec 2015 in Michigan

•23 global events in October 2015 http://www.kdnuggets.com

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Additional References• When a Health Plan Knows How You Shop: New York Times, June

28, 2014 http://www.nytimes.com/2014/06/29/technology/when-a-health-plan-knows-how-you-shop.html?_r=0

• Preparing Analytics for a Strategic Role: Behind WellPoint’s Shift to a New Provider Payment System. Michael Fitzgerald. MIT/Sloan. April 2014

• The Analytics Mandate. Findings from 2014 Data and Analytics Global Executive Study and Research Report. David Kiron, Pamela Kirk Prentice, Renee Boucher Ferguson. MIT/Sloan. May 2014

• Why is predictive analytics important? Eric Siegel, Ph.D. Prediction https://www.youtube.com/watch?v=CH8pMZMaIC8&authuser=0

• Why Data Matters: Moving Beyond Prediction. Jai Menon https://www.youtube.com/watch?v=VtETirgVn9c&authuser=0

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“So how did this guy get in front of us?”• 2003…Moneyball (Lewis)

• 2005…Freakonomics (Levitt and Dubner)

• 2007…Blink (Gladwell)

• 2009…Superfreakonomics (Levitt and Dubner)

• 2013…Predictive Analytics (Siegel)

• 2014…Think Like a Freak (Levitt and Dubner)

• 2015…When to Rob a Bank (Levitt and Dubner)

Movies: Moneyball, The Minority Report, Gattaca, Margin Call, Captain America: The Winter’s Soldier

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Jonathan Chapman

Louisiana Primary Care Association

jchapman@lpca.net

We Know What You’ll Do Next Summer

PREDICTIVE ANALYTICS