Physiologic Monitoring in the Cloud · Annual Quality Congress Breakout Session, Sunday, October 4, 2015 Physiologic Monitoring in the Cloud Objective: Develop an awareness of Big

Physiologic Monitoring in the Cloud

Carolyn McGregor AM, PhD Canada Research Chair Health Informatics Professor Faculty of Business and IT University of Ontario Institute of Technology Oshawa, Ontario, Canada

Professor Carolyn McGregor is the Canada Research Chair in Health Informatics at the University of Ontario Institute of Technology, Canada. Dr McGregor has led pioneering research in Big Data, analytics, event stream processing, temporal data stream data mining, business process modelling, patient journey modelling and cloud computing. In the 1990s she led two of the earliest business analytics implementations in Australia for one of the largest banks and the largest retailer. In 1999 she commenced research with a neonatologist from a neonatal ICU in Australia and has continued to propose new and innovative approaches for the use of information technology in neonatal intensive care and specifically the application of Big Data techniques to neonatal intensive care. She established and leads the Artemis Project, a Big Data solution for neonatal intensive care to demonstrate new data intensive solutions for conditions such as late onset neonatal sepsis, neonatal apnea and spells, retinopathy of prematurity and anemia of prematurity. Her new work also uses Big Data techniques to assess the impact of morphine on the premature neonate. She now progresses her research within the context of critical care medicine, mental health, astronaut health and military and civilian tactical training. She has been awarded over $10 million in research, consultancy and infrastructure funding. She has led the establishment of two IT start-up companies internationally and has published over 130 research publications and 7 patents internationally. She has extensive collaborative relationships with healthcare organizations, researchers and industry in several countries around the world including Canada, Australia, USA, China and Ireland. In 2013 her Artemis project was awarded the Information Technology Association of Canada (ITAC) Ingenious Award in the Not for Profit Category. In 2014 she was awarded membership in the Order of Australia, general division, for significant service to science and innovation through health care information systems. She is regularly called upon by the media as an international specialist in health informatics and Big Data. Annual Quality Congress Breakout Session, Sunday, October 4, 2015 Physiologic Monitoring in the Cloud Objective: Develop an awareness of Big Data and Cloud Computing and how these technologies can be utilized to enable new approaches for the monitoring and analysis of physiological data in the cloud.


Carolyn McGregor AM, PhD

October 4, 2015 1


Carolyn McGregor AM, PhDCanada Research Chair in Health Informatics, Professor,

University of Ontario Institute of [email protected]

hir.uoit.ca

@UOITHIR@CP_McGregor

Disclosure

• Nothing to disclose

DetectingInfection

Per Hour Data

3,600,000 ECG

3600 HR, SpO2

230,000 Chest Impedence

36,000,000 EEG

7000 Heart Beats

2000 Breaths

Internet of ThingsKnowledge TranslationChallenge

• Retrospective Analysis

• Not implemented in clinical practice

• Not scalable

• Either or combination of:

– Patient centric

– Condition centric

– Stream centric



October 4, 2015 2

Artemis:Big Data Disruptive Innovation

8

Data Integration MgrKnowledge Extraction

Data Miner HIRData Mover

InfoSphere Streams Runtime

Ontology DrivenRule Modifier

Deployment Server

Alert SinkOp

QRS

BP

RR PT

FA

WT

AR

SepsisBPA

EP

WTA

HR Source Op

SpO2 Source Op

BP Source Op

CIS Source Op

PatientStream

SPAD

E ID

E

USE

R IN

TE

RFA

CE

MedicalDataHub

CIS Adapter

ConfigurationServer

CapsuleTechServer

ClinicalInformation

System

Cognos

Data Aquisition

Online Analysis

Knowledge Extraction

(Re)deployment

ResultPresentation

Stream Persistency

Artemis

McGregor, C., Catley, C., James, A., Padbury, J., “Next Generation Neonatal Health Informatics with Artemis”, Medical Informatics Europe, Oslo, Norway, pp 115‐119

Late Onset Neonatal Sepsis (LONS)

0

500

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29/06/2010 12:00:00

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02/07/20104:00:00

Hourly Rows Level=0 Hourly Rows Level=1 Hourly Rows Level=2 Hourly Rows Level=3 Hourly Rows Level=4

In 1924

Cloud Computing

h //i di i /i h l d/

Artemis CloudWIHRI

McGregor, C., 2011, “A Cloud Computing Framework for Real‐time Rural and Remote Service of Critical Care”, IEEE Computer Based Medical Systems, Bristol, UK, 6 pages CDROM



October 4, 2015 3

0

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1/1/08 0:00

1/1/08 12:00

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1/3/08 12:00

1/4/08 0:00

1/4/08 12:00

1/5/08 0:00

Date

HRV

RRV

Number of minutes low

variability/hour

LONS and Narcotics

0

10

20

30

40

50

60

1/1/08

0:00

1/3/08

0:00

1/5/08

0:00

1/7/08

0:00

1/9/08

0:00

1/11/0

8 0:00

HRV

RRV

Number of minutes low

variability/hour

DateMcGregor, C., Catley, C., James, (2012), “Variability Analysis with Analytics Applied to Physiological Data Streams from the Neonatal Intensive Care Unit”, 25th IEEE International Symposium on Computer‐Based Medical Systems (CBMS 2012), Rome, Italy

17.83

7.72

36.3838.97

45.79

53.31

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

55%

60%

7am - 7 pm Day Shift 7pm - 7 am Evening Shift

O2 saturation percent frequency using Artemis 1 Hz data collection, day 28

<85% Below 85%- 92% Target 93% - 100% Above

8.33

25.0025.00

41.67

66.67

33.33

0%5%

10%15%20%25%30%35%40%45%50%55%60%65%70%

7am - 7pm Day Shift 7pm - 7 am Evening Shift

O2 saturation percent frequency using top of the hour spot readings, day 28

<85% Below 85% - 92% Target 93% - 100% Above

OxygenAnalytics

OxygenAnalytics

NeonatalSpells

Spells Classification Anemia of Prematurity

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HR RR



October 4, 2015 4

PK/PD Morphine

Bressan N McGregor C Smith K Lecce L James A 2014 “Heart rate ariabilit as an indicator for morphine pharmacokinetics

Implications forClinical Engineering

Greer, R., Olivier, C., Pugh, J. E., Eklund, J.M., McGregor, C., 2014, “Remote, Real‐Time Monitoring and Analysis of Vital Signs ofNeonatal Graduate Infants”, 36th Annual International Conference of the IEEE EMBS, Chicago, USA, pp 1382‐5





Deployment Server

Alert SinkOp

QRS

BP

RR PT

FA

WT

AR

SepsisBPA

EP

WTA

HR Source Op

SpO2 Source Op

BP Source Op

CIS Source Op

PatientStream

SPAD

E ID

E

USE

R IN

TE

RFA

CE

MedicalDataHub

CIS Adapter

ConfigurationServer

ClinicalInformation

System

Data Aquisition

Online Analysis

Knowledge Extraction(Re)deployment

ResultPresentation

Stream Persistency

Artemis in Space

Stream Persistency

Knowledge Extraction(Re)deployment Stream Persistency

ResultPresentation


Data Miner HIRData MoverOntology Driven

Rule Modifier

Deployment Server

PatientStream

McGregor C 2013 “A Platform for Real‐time Online Health Analytics during Spaceflight” IEEE Aerospace CDROM 8 pages

Athena





Deployment Server

Alert SinkOp

QRS

BP

RR PT

FA

WT

AR

SepsisBPA

EP

WTA

HR Source Op

SpO2 Source Op

BP Source Op

CIS Source Op

PatientStream

SPAD

E ID

E

USE

R IN

TE

RFA

CE

Cognos

Data Aquisition

Online Analysis

Knowledge Extraction

(Re)deployment

ResultPresentation

Stream Persistency

Athena

McGregor C Bonnis B Stanfield B Stanfield M 2015 “A Method for Real time Stimulation and ResponseMonitoring using Big Data and



October 4, 2015 5

Change Management andTechnology Impact Assessment

• Healthcare Innovation is not a Magic Pill– Rigorous research

– Linkages to outcomes

– Scalability/Reliability/Resiliency

– Policy Changes to Guidelines and Practices

– Impact on Healthcare Organisations

– Change Management for Integration into Care Practices

– New Information Technology Strategic Architectures

– Use of Data Governance

ArtemisClinical Applications

Questions?

Documents

Physiologic Monitoring in the Cloud · Annual Quality Congress Breakout Session, Sunday, October 4, 2015 Physiologic Monitoring in the Cloud Objective: Develop an awareness of Big