Architecting and Building the Future of Healthcare Informatics: Cloud, Containers,

Big Data and CHIPS

Rudolph Pienaar, PhD

Technical Director
Fetal-Neonatal Neuroimaging and Developmental Science Center

Staff Scientist
Boston Children's Hospital

introduction

Healthcare informatics is at an inflection point and is perhaps ill suited to handle the information tsunami

This talk considers some of the patterns in information flow - both historical and trending

Data portability
Compute portability, i.e. containers
Big Data

introduction

and offers one particular solution we have developed called...

Cloud

Healthcare

Information

Processing

Service

CHIPS

overview

to guess at the future...

you have to understand the present

Carl Sagan

you have to know the past

to understand the present

overview

Information explosion...

Healthcare

Information explosion...

Healthcare

1.65M tumors measured in various modalities
> 4 exabytes of data in various localities
1 petabyte of data (0.001EB) to transfer
On current Internet, would take about 21 days to transfer this data around.

healthcare... philosophy shapes informatics

historically, healthcare is differential, not integrative

informatics is poorly understood and not seen necessarily as fundamental

classically information relationship is best described as 1:1

the practice of medicine is less integrative

healthcare "compute"...

provided by vendors with very specialized skills and market

thin, vertical stacks

Typical hospital "web" apps...

silos...

Multiple, deep data sets exist in the healthcare dataverse

Largely disconnected and independent of each other

clinical

billing

health records

patterns of information flow in healthcare

Current

Unidirectional
Isolated
Non-integrative
Static

Future

patterns of information flow in healthcare

Current

Unidirectional
Isolated
Non-integrative
Static

Future

Multi-directional
Collaborative
Integrative
Dynamic

medical compute... in the cloud

definite need for data mobility and centralization...

with compute being "free" to process data where-ever it might naturally collect...

CHIPS...

CHIPS is a bio-medical data workflow manage that allows easy and intuitive collection, analysis, and sharing of data between parties.

allows for advanced view rendering
allows for sharing of images
allows for immersive real time collaboration
allows for post-processing of images

many data sources... many compute sources...

via here

connect data here

to here...

and compute!

containerization

security

Medical data is constrained by many external factors
Logging and control
Single shutoff point
Communication pathways

HIPAA
Local regulatory
IRB

secure architecturally

big data

Imaging
Genomics
Pathology

Input DICOM space
Processed result space
Structured clinical reporting

big data...

UI concepts

conclusion

Healthcare compute is at an inflection point
Lags larger computing -verse
Many opportunities and challenges exist

Untapped opportunity to integrate cutting edge approaches to inform healthcare

references... CHIPS/ChRIS

https://github.com/FNNDSC/ChRIS_ultron_backEnd

https://github.com/FNNDSC/ChRIS_ultron_frontEnd

references... services

```
https://github.com/FNNDSC/viewerjs
```
```
https://github.com/FNNDSC/gcjs
```
```
https://github.com/FNNDSC/fmjs
```
```
https://github.com/FNNDSC/toolbarjs
```
```
https://github.com/FNNDSC/rboxjs
```
```
https://github.com/FNNDSC/rendererjs
```
```
https://github.com/FNNDSC/thbarjs
```
```
https://github.com/FNNDSC/pman
```
```
https://github.com/FNNDSC/pfioh
```
```
https://github.com/FNNDSC/pfcon
```

references... viewers

```
https://goxtk.com
```
```
https://github.com/FNNDSC/ami
```

team

Jorge Bernal
Nicolas Rannou
Rudolph Pienaar
Yangming Ou

Daniel Haehn
Daniel Ginsburg

Ellen Grant

BCH Team

BU Team

Orran Krieger
Ata Turk
Aditya Awalker

RedHat

Dan McPherson
and others!

fin!

Thank you!