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Health Care Analytics

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Page 1: Health Care Analytics
Page 2: Health Care Analytics

The ABCs of ACO – Balance is Tipping Toward New Revenue Models

Page 3: Health Care Analytics

Types of ACOs and some Numbers

Page 4: Health Care Analytics

How We Can Make a Difference

Page 5: Health Care Analytics

We would like to Enable our partners Take Track 2 With our Trusted

Analytical Insights

Page 6: Health Care Analytics

What Does the Regulator Say

A critical foundation of the proposed rule is its

unwavering focus on patients. We envision that

successful ACOs will honor individual preferences and will engage patients in shared decision making about

diagnostic and therapeutic options. Information management — making sure patients and all health

care providers have the right information at the point of care — will be a core competency of ACOs.

Held to rigorous quality standards, ACOs will be expected

to be proactive in their orientation and to regularly reach out to patients to help them meet their needs for

preventive and chronic health care.

Page 7: Health Care Analytics

Two dominant market vectors: 1) Changes in reimbursement and associated risk. 2) Regulatory requirements (MU attestation, quality reporting etc.)

Analytics using clinical data is in its infancy.

Clinical datasets are typically a mess and very difficult to work with.

For foreseeable future, most healthcare organizations will need to rely on claims data to

ascertain risk.

We may be years away from doing true real-time analytics with clinical data.

Most healthcare providers do not have well-trained informatists on staff (particularly problematic for smaller healthcare organizations) and thus “analytic offerings” will have a high service component.

Business intelligence (BI) tools are not well-developed (either too simplistic or too complex for average clinician) and thus clinicians are unable to run their own reports. This has led to IT

departments being completely overwhelmed with clinicians asking for various reports.

Those pretty dashboards that are based on clinical data which you see at trade shows and in PowerPoint presentations can rarely be replicated at a client site – lots of smoke and mirrors.

Most EHR vendors are just getting started in this area and their solutions are rudimentary.

What Do Analysts Say

Page 8: Health Care Analytics

Accountable Care Analytics Solutions/Products (ACS) Focuses on selling Analytics Consulting & technology to support the transition to ACO i.e. Performance/Metric based value proposition for Providers and Patients. The ACO service market is expected to

range from ~$12B to ~$20B in 2016, with ~750 ACOs in

some stage of development by that time.

We would like to partner with Provider Organizations taking the leap and also payers that are taking baby steps in this space

Market Opportunity

Page 9: Health Care Analytics

Our ACO Optimization Tool Kit will encompass the following Analytical Capabilities:

Predicting Revisits

Clustering of High Risk Population for Outreach and monitoring

Care Process Optimization

Clinical Analytics/Epidemiology – Population Health Management

Post Discharge and Acute Care Outreach

Consulting Proposal – Improved Health Outcomes

Opportunity Identification & Selection

Preliminary

Risk and Requireme

nt Manageme

nt

Solution Design Operations

Solution Testing and Deployment

Solution Implementat

ion

Page 10: Health Care Analytics

Our ACO-ASK™ Solution would be a next generation Decision Support System built with following capabilities :

Holds Repository of all Medical Dictionaries/Medical Journals

Data Model can import Claim/Clinical data for any new population

Uses Text Mining and Bayesian Belief Networks

Built with Machine Learning Paradigm

Supports Voice and Text Interface

Product Proposal – Improved Care Outcomes by Decision Support

Page 11: Health Care Analytics

High Level System Design

Page 12: Health Care Analytics

Thin Client Sneak Preview

Page 13: Health Care Analytics

TECHNIQUES to be USED

Consulting - Improved Health Outcomes

ACO-ASK™ - Improved Care Outcomes

Patient Satisfaction

Techniques Error / Measure

KNN Root Mean Square

Neural Net Bench Mark Error

Text Mining Cosine Distance

Bayesian Belief

Network

Neural Net

Decision Tree

Sentiment Analysis

Page 14: Health Care Analytics

$26,500,000.00

$53,000,000.00

$106,000,000.00

$159,000,000.00

$212,000,000.00

-1

0

1

2

3

4

5

6

7

8

9

10

2012 2013 2014 2015 2016 2017 2018

No

. of

clie

nts

Revenue Projections for Consulting Engagement

Revenue Projections

Page 15: Health Care Analytics

$0

$50,000,000

$100,000,000

$150,000,000

$200,000,000

$250,000,000

2013 2014 2015 2016 2017

Re

ven

ue

Year

Revenue Projections (Consulting + ACO ASK™)

Revenue Projections

Page 16: Health Care Analytics

Living Healthy Saving Costs

Page 17: Health Care Analytics

For Individuals: +91-9177585755 or 040-65743991

For Corporates: +91-9618483483

Web: http://www.insofe.edu.in

Facebook: http://www.facebook.com/insofe

Twitter: https://twitter.com/INSOFEedu

YouTube: http://www.youtube.com/InsofeVideos

SlideShare: http://www.slideshare.net/INSOFE

LinkedIn: http://www.linkedin.com/company/international-school-of-engineering

This presentation may contain references to findings of various reports available in the public domain. INSOFE makes no representation as to their accuracy or that the

organization subscribes to those findings.

The best place for students to learn Applied Engineering http://www.insofe.edu.in

International School of Engineering

2-56/2/19, Khanamet, Madhapur, Hyderabad - 500 081

For Individuals: +91-9177585755 or 040-65743991

For Corporates: +91-9618483483

Web: http://www.insofe.edu.in

Facebook: http://www.facebook.com/insofe

Twitter: https://twitter.com/INSOFEedu

YouTube: http://www.youtube.com/InsofeVideos

SlideShare: http://www.slideshare.net/INSOFE

LinkedIn: http://www.linkedin.com/company/international-school-of-engineering

This presentation may contain references to findings of various reports available in the public domain. INSOFE makes no representation as to their accuracy or that the

organization subscribes to those findings.

The best place for students to learn Applied Engineering http://www.insofe.edu.in

International School of Engineering

2-56/2/19, Khanamet, Madhapur, Hyderabad - 500 081