Opportunity Analysis & Strategy Development for Medical Mobile Device Applications

Value Chain Models

Medical Technicians

App Developers

Network Providers OEMs Retailers Healthcare

Providers Patients

App Developers Network Providers OEMs Retailers Patients

Medicine based

Software based

Job Map with Outcomes

Define

• Increase amount of patient specific data

Locate

• Increase number of data connected devices.• Increase number of remotely controlled systems

Prepare

• Minimize time to connect devices

Confirm

• Increase display measurements

Execute

• Increase computational power• Minimize frequency of failure

Monitor

• Increase amount of real time tracking data

Modify

• Increase amount of remote setting changes

Conclude

• Minimize time to communicate with patient results

Why EMR Platform

• Developed countries moving to common EMR platform

• Productivity improvements could decrease healthcare spending by $300-800 billion annually

• More efficient information sharing of records results in higher quality of care

• Could prove life saving to individuals traveling without access to their records

Changing Needs

• Mobile Health Monitoring #5 in Gartner, Inc. top 10 trends

• Telemedical devices facilitating mobile health monitoring

• Estimated 81% of physicians using smartphones within few years

• “We're no longer using it as a reference device, we're using it as a computer replacement”

- Henry Feldman, MD, Chief of Information Architect at Beth Israel Deaconess Medical Center in Boston

Opportunity Landscape

Trends (Drivers) Problems (Jobs) Solutions (Products/Services)

Data Networks • Faster networks – 4G, LTE

• Medical record data size is too large to transfer quickly and costly

• Compression algorithm • Cache information in device

Simple Diagnostics Tools

• Consolidation of tools into single device

• Special training • Bluetooth tools• Multi-tool type diagnostic tool

EMR • Accessible medical records

• Integration with providers

• Secure sharing of info• Incompatible systems

• Single platform to broker medical data cross platform

• Data mapping software

Sensors • Smaller, faster, more accurate

• Single function sensors • Accuracy of data

• Multi-functional sensors• Algorithms to filter out

interference

Software • New languages• Lots of applications• Cloud computing• Open source on the rise

• Not all medical diagnostics available in software

• Lack of field expertise

• Partner with university to develop medical algorithms

Issue Analysis

What is the best way to drive broad adoption of a

single EMR data exchange system?

Develop the system to integrate with the top 10

EMR systems and applications

Drive partnerships with the top EMR ISV's

Seek investments from EMR vendors to gain their

commitment

Ensure the system is engineered exceeding

security and compliance requirements

Adopt security and legal requirements by providers

Strike key partnerships with the largest and most

influencial provider networks

Offer reducing or free pricing with key providers

to gain adoption

Hypothesis Analysis

Partnerships and adoption with top provider networks

Drives adoption across payer/provider

ecosystem

Revenue model is viable

Exchange of EMR data leads to other

uses

Development coordination drives universal standards

and protocols of system

Enures system satisfies security and

legal compliance requirements

Flexible network integrating with

majority of platforms

Launch Strategy

• Partner with largest healthcare networks

• Joint standards development

• Hire expertise

• Free integration consulting resources

• Partner with largest EMR ISV’s

Company Installations Installation %Meditech 1,185 26.60%McKesson Provider Tech 630 14.10%Cerner 560 12.60%Siemens Medical 425 9.50%Self-developed 357 8.00%CPSI 353 7.90%Epic Systems 265 6.00%Eclipsys 243 5.50%

Integrated Health Network HospitalsCatholic Health Initiatives 78Ascension Health 67Trinity Health 44Catholic Healthcare West 41Adventist Health System 37Kaiser Foundation Hospitals 36Catholic Health East 34Catholic Healthcare Partners 33Iowa Health System 26Providence Health & Services 26Sutter Health 25

Situation Analysis

• Context : Health Care Stimulus• Customer

• Competition: Epic Systems

Big Hospitals Small Hospitals and

Practices

Physicians and nurses

End Customer - Patients

Virginia Mason, Swedish Medical (large no of records)

Smaller number of medical records

Fall into big/small hospitals they work for

Don’t offer directly to end customer (legal issues)

Define

• Increase likelihood of correctly sharing data.

Locate

• Minimize time to locate and use cross-share feature

Prepare

• Increase likelihood of capturing all data• Minimize time to enter data

Confirm

• Minimize likelihood of entering inaccurate data

Execute

• Minimize time to process, store and cross-share data• Minimize likelihood of loss of data

Monito

r

• Increase likelihood of data sharing• Minimize time to confirm data cross-shared

Modify

• Minimize time to correct data• Minimize number of times data has to be entered

Conclude

• Minimize time to confirm and close• Increase likelihood of successful save and share

Future Job Map

Launch Plan

Jan 2012

Agreement with clients access

Sharing Pricing

June 2013

Requirements Specifications

Captured

Nov 2012

Product Delivered for 2 Big Hospitals to share

Common platform built.

Oct 2013

Build extra jobs Get new clients

Bootstrap, build teams

Identify clients Build software Legal Project

management teams

Jun 2012

Optimize on Prepare And Execute

Q & A