The importance of data for clinical decision-making
04 Oct 2022
Vaccine
"If we're genuine about changing patient experience we have to make sure we collect data and make the clinical decisions as close to the data collection as possible," said
AJ Missaghi, CTO of Healthcare and Life Sciences at Dell Technologies.
During his session, "
Healthcare Industrial Revolution," sponsored by Dell Technologies, Missaghi argued it was important that healthcare leaders use insights from data to bring new levels of efficiency to patient care.
One example is the
Digital LifeCare programme
, which was launched in collaboration between Dell, the government of India, and Tata Trusts in 2018. Using a digital platform with mobile, cloud and analytics applications, accredited social health activists (ASHAs), and auxiliary nurse midwives (ANMs) monitor the health of more than 135 million people in districts across India.
"
ASHAs go into remote areas and start collecting data from communities which typically wouldn't have had that sort of interaction," explained Missaghi. "This data allows us to start making assessments really quickly about what sort of diseases are about to take place."
Another example is Dell's work with genomics in the US, which helps researchers to make decisions faster with the data they are collecting in labs.
"You need access to high-performance computing – that's what we bring to the table. We have specialised solutions that allow you to do it a lot quicker," said Missaghi.
DataOps
Data collected in real-time is known as 'streaming data', which is valuable for both short-term and long-term decision-making.
"Over time, the value of that data is going to start going up because you can start building long-term profiles of that data and feeding into different studies, bed management, process optimisation or whatever you like," said Missaghi. "You can make decisions that are impacting not just patients but also clinicians and quickly iterate and optimise the process or change the triage process. If it's around accessing genomics data, you can make those process decisions a lot quicker. We call this DataOps."
DataOps is a set of practices, processes and technologies focused on improving the communication, integration and automation of data flows between data managers and data consumers across an organisation.
Big pharma and labs took advantage of DataOps to aid the fast creation of vaccines during the COVID-19 pandemic.
"It was enabled because of data being collected and globally streamed into databases," continued Missaghi. "People around the world were analysing it, working on it, and testing it and ultimately quickly turning around those vaccinations that we saw."
Finally, Missaghi invited the audience to consider the kind of data their clinical processes are generating and how it is being used.
"If you're not making decisions quickly enough, I can assure you that it's having an impact on your patient experience and even on your clinicians' experience," concluded Missaghi. "If you have any data points that might be manual at the moment let's digitalise."
For more details,please visit the original website
The content of the article does not represent any opinions of Synapse and its affiliated companies. If there is any copyright infringement or error, please contact us, and we will deal with it within 24 hours.
Organizations
Indications
Targets
-Drugs
-Chat with Hiro
Hot reports
Get started for free today!
Accelerate Strategic R&D decision making with Synapse, PatSnap’s AI-powered Connected Innovation Intelligence Platform Built for Life Sciences Professionals.
Start your data trial now!
Synapse data is also accessible to external entities via APIs or data packages. Empower better decisions with the latest in pharmaceutical intelligence.