Course support for Analytics in Action

1. Health Analytics
February 2018
Analytics in Action
http://DSign4.education

2. Introduction
©2016 L. SCHLENKER
Agenda
Introduction
Definitions
Infrastructure
Use Scenarios
Limits

3. Introduction
• Place - changes in geography, time, physical
resources and budget
• Platform – enriching how information is produced
and consumed
• People – modifying the frame of reference
• Practice - impacting the reality of management
Schlenker (2015)

4. • The use of data, analysis, and predictive
modeling to improve teaching and
learning
• Analytics models aggregate data in new
ways
• Help students and institutions
understand past, present and future
academic performance
• Impact on personalized learning,
pedagogical practices, curriculum
development, institutional planning, and
research
Health Analytics
Technology

5. • Health care analytics arims to improve
clinical care while limiting excessive
spending
• Healthcare Activities that can be
undertaken as a result of data collected
from four areas within healthcare;
 Claims and cost data,
 Research and development (R&D)
data,
 Clinical data (collected from electronic
medical records (EHRs)),
 Patient behavior and sentiment data
Context
Technology

6. • The journey from fee-for-service to value-
based contracts
• Understanding the wants and needs of health
care consumers
• Defining the role of patient experience in
marketing
• Embracing transparency
• Creating patient loyalty in health care
organizations
Market Challenges
Technology
NRC Health

7. • Capital One Labs – uses data science
algorithms to develop next generation of
financial products and services.
• Citi Latin America Innovation Lab offers its
commercial customers transactional datato
help clients identify novel trade patterns
• Bank of America runs BankAmeriDeals with
various cashback offers for debit and credit
card holders based on the analytics
• Credit Suisse’s Data scientists find novel
opportunities to create revenue streams; retain
customers and reduce expenses
Whose doing it?
Technology

8. • Using collaborative analytics to personalize
treatment plans
• Analytics can help derive meaningful insights
to attract customers, as well as manage costs
and risk of health plans
• Detect fraud based on analysis of anomalies in
patient records
• Open up new diagnostic landscapes for the
automated interpretation of x-rays, CAT scans,
and MRIs
Use Scenarios
Technology

9.  Cutting down administrative costs
 Clinical decision support
 Reducing fraud and abuse
 Better care coordination
 Improving patient wellbeing
Value Levers
Technology
HealthFore Technologies

10. • Customer life event analysis
• Real time allocation based offerings
• Quality of lead analytics
• Micro-segmentation
• Customer Gamification
• DIsclosure reporting
• Anti-money laundering
• IVR analysis
• B2B merchant insights
• Real time capital calculations
• Log analytics
Data Science Techniques
Technology

11. • Creating an interoperability roadmap
• Protecting privacy and security
• Establishing common technical standards
• Increasing confidence in safety and safe use of
health IT
• Developing an international communications
structure
• Stakeholder collaboration
What are the risks?
Technology

12. • Adoption of cloud solutions
• KYC complicance to prevent fraud and
financial crimes
• Converged applications will integrate historical
and real-time financial data
• Increasing use of IoT and streaming
• Widespread implementation of Big data and
blockchain technlogies
Future trends
Technology

13. • Huffington Post, How Big Data Could Transform The
Health Care Industry, (video)
• Heusch, M., (2017), Using It or Losing It? The Case
for Data Scientists Inside Health Care
• Montgomery, M., (2016), The Future Of Health Care Is
In Data Analytics
• Rao, V., (2015), Healthcare Data Analytics
• Raghupathi, W. (2014), An Overview of Health
Analytics
Bibliography
Next Steps

14. • What is the organization’s business
model?
• Why does the organization focus on
data?
• How is the Data Science team
organized?
• Which data science techniques does
the organization favor ?
• What is the link between data science
and decision making?
• How does the organization use Data
Science to propel growth
Case Study Questions
Technology