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Demand connected medical devices to improve military EHRs
Change procurement of medical devices to help fill EHRs with clinically useful data for comparative effectiveness
research and data interoperability
www.netspective.com 2
This and many of my other presentations are available at
http://www.SpeakerDeck.com/shah
www.netspective.com 3
@ShahidNShah
Who is Shahid?
• 25+ years of software engineering and multi-site healthcare system deployment experience
• 20+ years of technology management experience (government, non-profit, commercial)
• 15+ years of digital health, healthcare IT and medical devices experience (blog at http://healthcareguy.com) Author of Chapter 13,
“You’re the CIO of your Own Office”
@ShahidNShah
www.netspective.com 4
What’s this talk about?
Miliary Health IT / MedTech Landscape
• Data has potential to solve some hard healthcare problems and change how medical science is done.
• The government & military are paying for the manual collection and clerk-like entry of clinical data.
• Current data collection is unreliable, slow, and error prone.
Key Takeaways
• Medical devices are the best sources of quantifiable, analyzable, and reportable clinical data.
• New devices must be designed and deployed to support inherent connectivity.
• Government and military buyers have the procurement muscle to force vendors to become more connected.
www.netspective.com 5
@ShahidNShah
What problems can data help solve?
Cost per patient per procedure /
treatment going up but without ability to
explain why
Cost for same procedure /
treatment plan highly variable across localities
Unable to compare drug efficacy across patient populations
Unable to compare health treatment
effectiveness across patients
@ShahidNShah
www.netspective.com 6
Patient populations need different solutions
• Obesity Management• Wellness
Management
• Assessment – HRA• Stratification• Dietary• Physical Activity• Physician
Coordination• Social Network• Behavior Modification
• Education
• Health Promotions
• Healthy Lifestyle Choices
• Health Risk Assessment
• Diabetes• COPD• CHF
• Stratification & Enrollment
• Disease Management• Care Coordination• MD Pay-for-
Performance• Patient Coaching
• Physicians Office• Hospital• Other sites• Pharmacology
• Catastrophic Case Management
• Utilization Management
• Care Coordination• Co-morbidities
Well Patient At Risk Chronic Care Acute Treatment
Prevention Management
26 % of Population
4 % of Medical Costs
35 % of Population
22 % of Medical Costs
35 % of Population
37 % of Medical Costs
4% of Population
36 % of Medical Costs
Source: Amir Jafri, PrescribeWell
www.netspective.com 7
The digital enterprise is revolving rapidly based on key trends, health systems’ evolution, and IT’s evolution
Key
Ind
ustr
y
Tren
ds
.
Healt
h
Syste
m
Evolu
tion
IT
Syste
ms
Evolu
tion
IT R
ole
Evolu
tio
n
Fee For Service, Shared Risk, Bundled Payments,
etc.Value, Care Management, Population Management
PRESENT
Full Risk, Integrated Health Plan & Care Delivery System
Personalized Medicine, Wellness Management
FUTURE
Fee For Service
Volume/Episodic Care
PAST
Integrated EHR
Health Information
Exchange (HIE)
Enterprise Data Warehouse
(EDW)Patient
Engagement
Mobile Health
Connected Care
Wellness Manageme
nt
Advanced Informatics
Personalized Medicine
Ancillary Systems (Lab/Rad/Pharmacy,
etc.)
Enterprise Resource Planning (HR, GL,
SCM)
Revenue Cycle
Ambulatory EHR
Hospital EHR
Patient Access
Enabler InnovatorInstaller Integrator
Integrated Healthcare Network
Integrated Healthcare Ecosystem
Multi-Specialty Care Clinic & Hospital
Integrated Healthcare System
Source: Bruce Metz, CIO, Lahey Health
@ShahidNShah
www.netspective.com 8
We’ve seemingly accepted lack of cures…
The Shift
The clinical model is shifting away from treatment of chronic conditions and focusing more on prevention, wellness, obesity intervention, behavior and lifestyle modification.
Objectives
• Keep people out of the hospital ($$$)
• Keep people from their docs ($$)• Keep people off drugs ($)• Keep people at home
ImplicationsClinical operations are shifting to hospital and physician ‘centered’ services that will rely heavily on health information technologies to monitor, coordinate, and manage care.
• Successful Transition in Care resulting in Reduced Hospital Readmission Rates
• Proactive population management• Patient engagement and collaboration• Disease prevention through wellness and
obesity management• Chronic disease management• Care coordination and collaboration• Metrics and analytics
@ShahidNShah
www.netspective.com 9
Data changes the questions we ask
Simple visual facts Complex visual facts Complex computablefacts
@ShahidNShah
www.netspective.com 10
Data can change medical science
The old way
Identify problem
Ask questions
Collect data
Answer questions
The new way
Identify data
Generate questions
Mine data
Answer questions
OldNew
www.netspective.com 11
@ShahidNShah
Data Comprehension is hard
• Must be continuously recomputed
• Difficult today, easier tomorrow
• Super-personalized• Prospective• Predictive
What does it mean?
How do I use it?
• Can be collected infrequently
• Personalized• Prospective• Potentially predictive• Digital• Family history is easier
Bio IT and Genomics
Secondary Aggregation
• Continuously collected• Mostly Retrospective• Useful for population
health• Part digital, mostly
analog• Family History is hard
PhenotypicsPrimary Data
Collection
• Business focused data• Retrospective• Built on fee for
service models• Inward looking and
not focused on clinical benefits
Admin Data Collection
Biosensors
Social Interactions
www.netspective.com 12
Data
Medical Hardware
Consumer Hardware
Health Records
Patient IT Social Media Health Literacy Retail purchases Behaviors
IoT Sensors
Hardware Software
Pharma / Clinical Trials
Labs / Imaging
Payments
Bioinformatics
Health Info Exchg
Provider EngagementCare Coordination
Compliance
Marketing ITRetrospectiveProspective
Med Devices
Integration
ComprehensionTools, Storage, Services
Science, Discovery Value
Creation
Research
ConsentDigital Chemistry
Provider Stature
Ratings/reviews
www.netspective.com 13
@ShahidNShah
Unstructured phenotypic patient data sources
Patient Health Professional
Labs & Diagnostics
Medical Devices
Biomarkers / Genetics
Source Self reported by patient
Observations by HCP
Computed from specimens
Computed real-time from patient
Computed from specimens
Errors High Medium Low
Time Slow Slow Medium
Reliability Low Medium High
Data size Megabytes Megabytes Megabytes
Data type PDFs, images PDFs, images
PDFs, images
Availability Common Common Common Uncommon Uncommon
www.netspective.com 14
@ShahidNShah
Structured phenotypic patient data sources
Patient Health Professional
Labs & Diagnostics
Medical Devices
Biomarkers / Genetics
Source Self reported by patient
Observations by HCP
Specimens Real-time from patient
Specimens
Errors High Medium Low Low Low
Time Slow Slow Medium Fast Slow
Reliability Low Medium High High High
Discrete size Kilobytes Kilobytes Kilobytes Megabytes Gigabytes
Streaming size
Gigabytes Gigabytes
Availability Uncommon Common Somewhat Common
Uncommon Uncommon
www.netspective.com 15
@ShahidNShah
Demand medical device integration/connectivity
Data integration
Manageability
Enhance functionality
Most obvious benefit Least attention
Most promisingcapability
This talk focuses on connected devices
www.netspective.com 16
@ShahidNShah
Procure poly-connectable devices
Device
Hospital Network
Corporate Gateway
External Cloud
Hospital Systems
Option 1 (no cellular access or hospital IT integration required)
Device
External Cloud
Option 2 (cellular access and no hospital IT integration required)
DDS
REST
HL7
X.12
DDS REST
MPEG-21
MPEG-21
Could be a Home
Network, too
Wired
WirelessBluetooth, WiFi, Zibee, etc.
Wireless, Cellular
MQTT
MQTT XMPP
XMPP
www.netspective.com 17
@ShahidNShah
Demand better manageability in devices
Security• Is the device
authorized?
Inventory• Where is the
device?
Presence• Is a device
connected?
Teaming• Device
grouping
@ShahidNShah
www.netspective.com 20
Invest in digital biology and digital chemistryLabs on chips Personal Genomics
@ShahidNShah
www.netspective.com 23
Device Components 3rd Party Plugins
App #1
App #2
Security and Management LayerDevice OS(QNX, Linux, Windows)
Sensors Storage Display Plugins
Web Server, IM Client
Connectivity Layer (DDS, HTTP, XMPP)
• Presence• Messaging• Registration• JDBC, Query
CloudServices
ManagementDashboards
Data Transformation (ESB, HL7)
Device Gateway (DDS, ESB)
Healthcare Enterprise
Enterprise Data
Demand Connected Architecture
Plugin Container
Event Architecture
Inventory
Workflow
NotificationsPatient Context
LocationAware
1 23
4
5
6
7
8
9
SSL VPN
@ShahidNShah
www.netspective.com 24
Ultimate Architecture Core
Device Components
Security and Management LayerDevice OS(QNX, Linux, Windows)
Connectivity Layer (DDS, HTTP, XMPP)Plugin Container
Don’t createyour own OS!
Security isn’tadded later
Think aboutPlugins from day 1
Connectivity isbuilt-in, not added
Build onOpen Source
Create code asa last resort
@ShahidNShah
www.netspective.com 25
Connectivity components
Device Components
Security and Management LayerDevice OS(QNX, Linux, Windows)
Web Server, IM Client
Connectivity Layer (DDS, HTTP, XMPP)
• Presence• Messaging• Registration• JDBC, Query
Plugin Container
Surveillance &“remote display” Remote Access
Alarms Event Viewer
Design all functions as plugins
@ShahidNShah
www.netspective.com 26
Demand enterprise integration
CloudServices
ManagementDashboards
Data Transformation (ESB, HL7)
Device Gateway(DDS, XMPP, ESB)
Enterprise Data
Inventory
Cross Device App Workflows
AlarmNotifications
Patient ContextMonitoring
DeviceTeaming
DeviceManagementReport
Generation
HITIntegration
RemoteSurveillance
DeviceData
SSL VPN