The COVID-19 pandemic has further highlighted the ways data integration can make a significant contribution and help to increase the quality of decision-making. This is especially pertinent in healthcare where clinical decision-makers face multiple barriers and challenges along the patient pathway. This last year has seen the NHS consider the challenge of how patient pathways can be improved and silos addressed. Data has been key to breaking down these organisational silos by providing information at the point of contact and then later once the patient has been discharged from care. MobiHealthNews explores how companies have strengthened patient pathways through data and artificial intelligence (AI).
Medtech data platforms
Digital technology offers the potential to transform the patient pathway, and this clear potential to disrupt traditional models is what continues to fuel investment in the medtech sector. While there is now no shortage of data for medtech innovators to work with, difficulties exchanging and using data between different systems and devices hold back many companies from realising their clinical potential. John Kelly, sales manager Ireland at InterSystems shared how data platforms can help medtech companies eliminate the need to integrate multiple technologies and toolsets, reducing the time-to-market for new innovations.
Kelly told MobiHealthNews: “While there is now no shortage of data for medtech innovators to work with, difficulties with exchanging and using data between different systems and devices hold back many companies from realising their clinical and market potential quickly.
“It is no longer acceptable for medtech innovations to operate as standalone systems, as sharing data with other systems and devices is essential to improve patient safety and clinical outcomes. The implementation of a data platform can help medtech companies to eliminate the need to integrate multiple technologies and toolsets, reduce the amount of code than needs to be developed and tested, and in turn, significantly reduce the time-to-market for new innovations.”
“The AI powered insights we are now seeing deployed are improving outcomes for people as they move us more into the personalised precision space.”
– Dr Charless Alessi, chief clinical officer, HIMSS
The machine learning boom
The UK-based software company, Kortical offers a platform that is able to absorb the data sets of any company and creates algorithms that offer strategic and commercial insights for them. Experts have predicted that the machine learning (ML) platform market will boom, with Gartner estimating that by 2022 75% of all new end-user solutions using AI and ML techniques will be built using commercial solutions rather than open source.
Andy Gray, CEO and co-founder at Kortical, told MobiHealthNews: “At the moment businesses are still in the early days of the ML gold rush, where you can crest a hill and stumble upon a nugget. Better ML accelerators are like better metal detectors helping you find those nuggets faster.
“Initially it was really only the big players that were the early adopters, where they had the luxury to experiment with new technology and those experiments have turned into significant business so increasingly we’re seeing smaller businesses that recognise the strategic advantage and huge potential of ML to really distance themselves from their competitors.”
The healthcare industry has been quick to take advantage of the potential of using ML to produce actionable insights. From capturing healthcare information, summarising the information, to coordinating care, securing reimbursement and making critical decisions.
The future of AI and data
Metadvice is a global healthcare technology company that utilises AI-based analyses and advancements in medical science to improve the consistency and personalisation of clinical decision making.
Professor Richard Barker, founder and business strategy advisor at Metadvice, told MobiHealthNews: “The value of AI is directly proportional to the data quality that you can access. Although we have seen data sharing accelerated through the COVID pandemic, we still have a decline with regard to interoperability and data quality.
“So for example, we put a lot of emphasis on finding databases that have already been well-curated, and so we are not great fans of what you might call a big data approach. Just give me millions and millions of patient records and we’ll make something out of it. It’s much more important to us to get a more mid-sized data set that we know can be relied upon.
“I think that there’s a great deal of public and patient education to be done about the value of data being identified, and I think that’s really only just beginning.”
Highlighting the strides made with AI-led insights, Dr Charles Alessi, chief clinical officer at HIMSS, said: “The AI-powered insights we are now seeing deployed are improving outcomes for people as they move us more into the personalised precision space.
“None of this is of course possible unless we have the means to train on algorithms on real-world data to ensure our interventions continue to iterate and change towards better outcomes. We live in an interconnected world where interoperability and access to good quality data are inherently interlinked as we strive to deliver better outcomes for people.”
As healthcare organisations are relying more on technologies and datasets to drive forward patient pathways, digital health indicators such as the HIMSS Analytics Electronic Medical Record Adoption Model (EMRAM) maturity model leads by example by harnessing data with methodology and algorithms to automatically score hospitals relative to their EMR capabilities. Most recently, two Saudi Arabian hospitals in the Al Mouwasat group achieved the highest level of the HIMSS Electronic Medical Records Adoption Model (EMRAM). The hospitals were assisted by investment in the Dedalus Enterprise Management (EM) system in 2016. This solution helps to eliminate inefficiencies by connecting information such as patient demographics, clinical data and financial reports. Solutions like these will be on the rise as healthcare experts aim to broaden the quality of data and translate it into actionable insights that can make a quantifiable difference to the delivery of care for years to come.