Transcript

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

@[email protected]

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.

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@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

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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

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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

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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

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Data changes the questions we ask

Simple visual facts Complex visual facts Complex computablefacts

@ShahidNShah

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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

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@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

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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

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@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

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@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

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@ShahidNShah

Demand medical device integration/connectivity

Data integration

Manageability

Enhance functionality

Most obvious benefit Least attention

Most promisingcapability

This talk focuses on connected devices

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@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

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@ShahidNShah

Demand better manageability in devices

Security• Is the device

authorized?

Inventory• Where is the

device?

Presence• Is a device

connected?

Teaming• Device

grouping

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@ShahidNShah

Demand extensibility

Legacy Devices Future Devices

@ShahidNShah

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Start procuring consumer-grade physiologics

@ShahidNShah

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Invest in digital biology and digital chemistryLabs on chips Personal Genomics

@ShahidNShah

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Start procuring consumer grade monitoring

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@ShahidNShah

Invest in predictive analytics and CEP

@ShahidNShah

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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

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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

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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

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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

Conclusion and Questions

@ShahidNShah [email protected]


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