Date post: | 03-Nov-2014 |
Category: |
Health & Medicine |
Upload: | damon-gjording |
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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