Remote Patient Monitoring with Internet of Medical Things (IoMT)
Summary
TLDRThe video discusses a Microsoft Research team's project focused on healthcare data interoperability, using the FHIR (Fast Healthcare Interoperability Resources) open standard. Rashmi Raj from Microsoft showcases how the team is developing tools to securely ingest and normalize data from various IoT medical devices, storing it in a FHIR server via Azure. The project aims to consolidate scattered data sources, creating a comprehensive patient record that can be used for applications like remote patient monitoring and AI-based healthcare solutions. The open-source project encourages community contributions for further enhancement.
Takeaways
- 🔗 Interoperability is a critical challenge in healthcare due to the diverse data coming from various medical devices.
- 💻 Microsoft Research, led by Rashmi Raj, is developing a data platform that uses the FHIR (Fast Health Interoperability Resources) standard to address this challenge.
- 🌐 FHIR (pronounced 'fire') is an open standard rapidly growing for healthcare data exchange and interoperability.
- 🔐 The platform focuses on secure and scalable data ingestion from IoMT (Internet of Medical Things) devices, utilizing Azure services.
- 🏥 Key use cases include remote patient monitoring, clinical trials, telehealth, and home care, all powered by data pulled from various IoT medical devices.
- 📂 The project features the IoMT FHIR connector, an open-source tool available on GitHub, allowing devices to send data to Azure and store it in a FHIR server.
- 🔓 Open-source contributions are encouraged, enabling users to extend and improve the platform by creating new data templates and normalizing device data.
- 🧑💻 The platform integrates data from electronic medical records (EMRs), labs, retail, and social determinants of health to build a comprehensive patient record.
- ⚙️ Users can deploy the IoMT FHIR connector via Azure and configure it to manage identity and security, ensuring HIPAA and HITRUST compliance for protected health data.
- 📊 Real-world scenarios include using Postman to query data from the FHIR server, and this data can be integrated into dashboards or used for AI and machine learning applications.
Q & A
What is the main challenge in healthcare data that the video addresses?
-The main challenge is data interoperability—how to make sense of data coming from various healthcare devices and applications in a unified way.
What is the focus of Rashmi Raj's team at Microsoft?
-Rashmi Raj's team focuses on creating a data platform for interoperability using the FHIR (Fast Healthcare Interoperability Resources) standard, specifically in the context of Internet of Medical Things (IoMT) devices.
What does FHIR stand for, and why is it important?
-FHIR stands for Fast Healthcare Interoperability Resources. It is an open standard designed to enable the exchange of healthcare information electronically, which helps with data interoperability in healthcare systems.
What is the Azure IoMT FHIR Connector?
-The Azure IoMT FHIR Connector is an open-source project that allows for the secure ingestion and normalization of data from IoMT devices into a FHIR-compliant format, enabling downstream business applications to use the data.
How does the IoMT FHIR Connector ensure security and compliance?
-The IoMT FHIR Connector ensures security by using Azure's secure cloud infrastructure, which is HIPAA, HITRUST, and SOC2 compliant, ensuring the safe handling of Protected Health Information (PHI).
What types of data can be ingested and used by the FHIR Connector?
-The connector can ingest various types of data, including data from IoMT devices (e.g., heart rate, respiratory rate), Electronic Medical Record (EMR) data, lab results, and social determinants of health data.
What scenarios can benefit from this data platform?
-The platform can support scenarios such as remote patient monitoring, telehealth, clinical trials, and home care, by enabling the integration of various health data types into a single system.
How does the open-source nature of the IoMT FHIR Connector benefit the healthcare community?
-The open-source nature allows developers and organizations to not only use the connector but also contribute to its development, such as by creating templates for different devices and expanding its capabilities.
What role does Azure API for FHIR play in this solution?
-Azure API for FHIR provides a fully compliant and managed service that stores and normalizes the ingested data from IoMT devices, enabling developers to build applications on top of the FHIR API.
What is the significance of creating templates for different devices in this system?
-Templates are essential because they map data from specific devices to the FHIR standard, allowing for the normalization of device data so that it can be processed and used in various healthcare applications.
Outlines
📊 The Importance of Interoperability in Healthcare Data
This paragraph highlights the challenge of managing large volumes of healthcare data from various devices, emphasizing the importance of interoperability. Rashmi from the Microsoft research team introduces a project focused on creating open standards for data management in healthcare. The discussion touches on building solutions around the FHIR (Fast Health Interoperability Resources) standard and mentions a project aimed at solving data challenges through secure, scalable technology for remote patient monitoring and other use cases.
🏥 Securing Protected Health Information on Azure
The second paragraph explains how healthcare data, including Protected Health Information (PHI), can be securely stored on Azure using services that comply with HIPAA, HITRUST, and other regulations. The use of FHIR standard enables interoperability, allowing the integration of data from various sources such as electronic medical records (EMR), lab results, and even social determinants of health. The goal is to create a comprehensive longitudinal patient record for advanced use cases like AI-driven healthcare models, ensuring privacy and security.
⚙️ Setting Up the IoMT-FHIR Connector in Azure
This section walks through the setup process for integrating Internet of Medical Things (IoMT) devices using the FHIR connector in Azure. It details the steps to deploy an FHIR server via Azure API and integrate IoMT devices by configuring them in Azure's IoT Central platform. The paragraph also explains how the FHIR server handles secure data ingestion and device interoperability, using open-source tools available on GitHub to help developers get started.
🔧 Data Templates for Normalizing IoMT Device Data
In this paragraph, Rashmi discusses the process of normalizing data from various IoMT devices using templates that map device data to FHIR-compliant formats. She mentions the availability of templates for common devices and the flexibility to create new templates for other devices. The open-source project encourages contributions to these templates, aiming to simplify the integration of any medical device into the FHIR ecosystem. This data normalization is key for creating interoperable healthcare applications.
💻 Demonstrating FHIR Data Flow with IoMT Devices
This section demonstrates the complete setup of an IoMT device pipeline, from simulating device data in Azure IoT Central to viewing normalized data using Postman. It shows how telemetry data like heart rate and respiratory rate from devices are sent through the IoMT-FHIR connector, securely ingested, and then stored in the FHIR server. The paragraph emphasizes how easy it is to scale this solution to handle millions of devices while ensuring security and privacy for healthcare data.
🛠️ Open-Source Contributions and Feedback
The final paragraph invites the audience to explore the open-source GitHub repository for the IoMT-FHIR connector, contribute templates and code, and provide feedback. Rashmi expresses excitement about the community's potential to build on the team's work and help improve healthcare through interoperability and scalable solutions. The segment concludes with a call to action for developers to engage with the project.
Mindmap
Keywords
💡Interoperability
💡FHIR (Fast Healthcare Interoperability Resources)
💡IoMT (Internet of Medical Things)
💡Azure API for FHIR
💡Data Normalization
💡Remote Patient Monitoring
💡Azure IoT Central
💡HIPAA Compliance
💡Longitudinal Patient Record
💡Machine Learning in Healthcare
Highlights
The critical challenge in healthcare is ensuring interoperability of data generated by numerous IoT devices.
Rashmi Raj from Microsoft Research discusses the development of an open-source project aimed at solving data interoperability in healthcare.
Microsoft's team is focused on building a platform using the FHIR (Fast Healthcare Interoperability Resources) standard to ingest and manage IoT data in Azure.
The project allows for secure and scalable ingestion of data from various IoT medical devices using the FHIR open standard.
Azure IoT Hub and Central services connect devices securely, and data is normalized and stored in a FHIR server for further application use.
The FHIR open-source project allows developers not only to use the tool but also contribute to it, helping expand its use cases.
A demonstration of the system shows how data from IoT medical devices can be mapped, normalized, and stored using the IoMT FHIR connector.
By using Azure's compliant cloud, healthcare providers can securely store Protected Health Information (PHI) and meet HIPAA and other regulatory standards.
The system integrates various healthcare data, including Electronic Medical Records (EMR), lab data, and social determinants of health data, to create a comprehensive longitudinal patient record.
The solution enables new healthcare use cases, such as remote patient monitoring, clinical trials, telehealth, and home care scenarios.
The demo simulates a medical device (Smart Vitals Patch) sending biometric data like heart rate and respiratory rate, which is normalized and stored in a FHIR server.
Postman is used to query the normalized heart rate data stored in the FHIR server, showing real-time ingestion and retrieval of IoT medical data.
The system is designed for scalability, allowing providers to connect and manage data from a few devices to millions, ensuring both security and scalability.
Azure IoT Central provides pre-configured templates for healthcare applications, speeding up the setup of remote patient monitoring solutions.
The open-source nature of the project invites the community to extend, contribute, and build new templates for various devices like Fitbit and Garmin.
The project is helping to advance healthcare technology by enabling the integration of IoT data into machine learning models for AI-driven healthcare solutions.
Transcripts
one critical thing in healthcare is data
data coming very often from tons of
different types of devices a big
challenge for building applications on
top of that data is interoperability how
do you make sense of all that data
Rashmi from the Microsoft research team
is here to show us a project her team is
developing to rationalise and to build
appropriately around an open standard
coal fire with a nice ash or connector
that's today on the IOT show
[Music]
[Music]
hi everyone you're watching the
internet-of-things show and I'm Olivia
your host as you might know there is a
lot of IOT devices out there and the
medical space is no exception there's
tons of devices that produce data in in
the healthcare systems in the medical
environments and there's a big challenge
today which is all that data needs to be
consumed by various systems and we need
interoperability and rashmi rise from
the Microsoft Research Group is here and
it's going to tell us about some work
that your team is doing
Rashmi thanks for joining the show -
that sure so for our audience can you
rapidly introduce yourself and tell us
what your team is doing at Microsoft
okay so my name is Rashmi Raj I am part
of health cloud and data team our team
is very focused on creating data
platform for interrupt interoperability
using fire open standard fire is rapidly
growing a standard stands for fast
health interoperability resources
my team is specifically focused on
creating tools for ingesting and pulling
data from these IO empty internet of
medical things which are devices
applications sensors pull that data
bring it to Azul with security and
scalability and in able to create huge
cases like remote patient monitoring
clinical trials tele health home care
scenarios so this is a full team of you
guys working on that yep I think it's
brilliant so we have we have different
services like azure IOT hub and central
that allow connecting these devices
securely as you were saying but the key
of your project really is about
ingesting the data coming from various
sources of these IOT are UMT are your
medical things and and then you know
anything that data and doing something
out of it in a very in Tripura balay so
let's dive a bit into you know what
would the team is producing and others a
connector for a sure that allows
ingesting that data let's jump into the
details and I know you have a nice demo
of how things are working okay so as I
said earlier one of the biggest
challenges
in health care has been lack of data
interoperability so we built a fire
server as open-source and released it on
github we also have Azure API for fire
fully compliant and managed service to
enrich the ecosystem of fire and
enabling the data ingestion from IO
empty device edge we have created IO
empty fire connector for Azure it's
available at open source on github this
allows to again connect these devices
with security and scalability ingest the
data normalize the data in fire and
store it in fire server and then
downstream business applications can
consume and huge open fire API for
building applications on top of it also
and and so basically the fact that this
open source means that people not only
can use it right but also they can
contribute exactly and there's a there's
that standard actually is a standard
body that actually works in that myself
contributes to in the formulate open
source project yes cool what I want to
see how that works
sounds good so in so in real world as I
was saying you will have device it so if
you see here high level architecture you
have devices and then you use the IMT
fire connector which is open source
project which will allow you to ingest
data and persist it in fire server and
then you will use tools to query the
data and create your business
applications so how's it done today I
mean like when you have these equipments
like they're set where they're sending
data where's that data lending and how
do medical staff and and and personnel
interact with their data today
so right now data is very scattered and
that's the reason why we are building on
it right now if you see in IO empty
space there is no clear standard either
but what we are building will allow
answering a question to bring this data
and interoperable way on Azure and Azure
is against a cure compliant cloud so you
can bring pH I protected health
information data and store it and our
services are fully HIPAA compliant as
well as high trust and sacto compliant
as well
I see so so basically you get all the
benefits of that as your compliance with
these requirements and the other thing
you get as well I guess is the ability
as you're building an infrastructure or
a solution to aggregate different
sources of data different types of
devices and offer to your customers
which would be in a hospital or you know
a healthcare facility or something an
actual you know one solution versus a
scattered set of the apps and things to
maintain and so forth right
exactly and on top of it since we are
using fire standard you can bring EMR
electronic medical record data along
with devices data you can bring lab data
we are also looking at retail data we
are also looking at social determinants
of health data as well and bring all of
them with interoperability with the goal
to create a longitudinal patient record
so that you can use that data and create
a I machine learning model for improving
healthcare with mobility security and
privacy at the core of all of that so
for the demo we will use IOT Center for
simulating the device we will go to
github and deploy io empty connector we
will use as your API for fire and then
we will use postman to query the data
and see the data in the fire store so
let's go to Azure portal so here I'm at
the azure portal I go as your API for
fire and I add and create as your API
for fire server I have already created
with the basic configuration so you can
see I have a fire server created the
important thing is the endpoint that we
will use it when we deploy IO empty
connector so that's the first step we
have fire server now okay in the second
step I go to get up this is the IMT fire
github repository here I look at the end
of the presentation for this one for
people to find it sure and here you have
we have rich document about the
architecture how to use it how to debug
it
for easy deployment you just go to
getting started and you click deploy to
Azure when you deploy to Azure it will
bring you to basic configuration screen
where you can choose resource group you
can put service name the important thing
is to use your fire server URL so the
fire server that we created in the
previous step I've already saved it here
you remove slash metadata here you just
need the basic URL okay so I om t
connector is deployed after the
deployment what we need to do is we need
to take the identity of Io empty
connector and save it in fire so that
IMD connector can write data to fire sir
security thank you why we are sure that
we know the source of data is recognized
exactly so I come to fire server go to
authentication and add the managed
identity of the connector here so now we
have server we have connector which is
ready and configured to talk to each
other now devices so for the demo we
will use IOT central for simulating
devices so I can went to IOT central
created an application here you can
create custom application or you choose
pre create a template yes so we have the
new templates for healthcare exactly so
and that's what I'm going to use so we
have a template continuous patient
monitoring I'll choose it and create it
when I create this application it
creates it comes with a dashboard as
well as to pre created devices for my
demo we are going to use smart vitals
patch so I'll go to device template and
for those we're not familiar with azure
IOT in general azure RT central is that
quote-unquote not turnkey solution but
it's what we call a a solution platform
so you very rapidly get to work with
simulators and that's what you're
showing right now okay that will send
the same kind of data an actual device
would send yes and there's a way of
describing it device capabilities in IOT
central that device will be compliant
with and will be able to send data to
your azure IOT central then then you're
gonna consume in exactly
will consume it so if we use here is
smart vitals patch you can see it had
telemetry a biometric data in PH i did i
was talking about about my health
information for example heart rate
respiratory rate it also has data for
device monitoring I got device battery
device temperature device firmware
version for medical and this scenario we
will focus on the biometric or telemetry
data so let's see that data as an
example in JSON format so if you see
this is an example of the data coming
from a smart vitals patch you see heart
rate respiratory rate and other data for
my yeah once you have data now we need
to create two templates so that this
data can be extracted and mapped to open
fire standard okay for in the same I
have gone to the same IMT fire
repository the github repo here we have
sample template which will give you a
good example of how this template looks
like as well as there is a detailed
document on how to create a new template
for your own devices so these are two
template one for device one for fire
mapping so if you see device 1 I am
picking up heart rate and other
information or extracting it from that's
the way you normalize the data that's
coming from different devices you know
which device is the data format and then
you normalize to something that is fire
compliant basically exactly and so when
we are creating it we were debating
should we create for a few devices or
should we create it in such a way that
you can bring any device so the way it
is now you can bring any device as long
as you have the template yeah you can
pick it up will normalize it once again
it's an open source project people want
to contribute these templates these
converters for data normalization they
can definitely contribute to the project
exactly and as we move we also plan to
contribute and create for like very
common variables like fitbit Carmen
create those templates here so that
people can get started
so we have those two templates you take
these two templates save it into the
storage account for the IMT connector so
now if you see and to end we have fire
server we have the connector and we have
seen
device I go to the simulator device
again the IOT central application and I
export this data to IMT connector IMT
connector is listening on event hub okay
so I go to event up I select I am D
connector I have already created one
here and I choose the device data as I
said I'm interested in telemetric the
heart rate respiratory rate bhi data i
save it nice so easy is that exactly and
you have we have not device connected
and fire server and the data is flowing
through yes
now with this let's go to now postman
and query as your api of fire and CD
data especially hard right data so
postman here so I come to postman here
and I am querying again open API
standard and querying the heart rate
with the line code okay and I send it
and it comes back and as I scroll I can
see the heart rate here and I can see
the data value for the heart rate here
as well awesome in a matter of minutes
you actually built an actual you know
fire compliant solution obviously behind
that postman example you would have an
actual application was a dashboarding
with the venting workflows and so on as
you had in your diagram at the beginning
exactly or you can take data from fire
and you can do a I machine learning to
again go into scenarios like telehealth
remote patient monitoring and the key
here that you were saying is the
security and scalability which azure IOT
platform gives you start with a few
devices and you can scale it to hundreds
and millions of devices and store it
with privacy on as you're awesome
that that's fantastic work you guys are
doing leveraging the azure IOT
technology adding on top of that you're
part of months of research so you need
input and feedback so what's your ask to
our audience today
so the ask is first let go and check out
the github repository it's open source I
tried out extend it
ad templates firebugs ad code base and
give us feedback we are very excited to
see the work that we are doing how it's
helping the community to improve the
healthcare awesome so there's a short
link to get to that hit up repo if you
don't catch it in the video is aka dot
ms / IOT show / iom t-connector as IO
medical things in terms of medical
things connector thanks rash me for
joining us on the show today hope to see
you soon and the work your guys are
doing you know on another episode thanks
everyone for watching don't forget to
subscribe and see you soon
[Music]
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