One of the new tools already in use, Amazon Comprehend
Medical, is already proving itself. Partovi describes it as “a highly accurate
natural language processing service for medical text, which uses machine
learning to extract disease conditions, medications, and treatment outcomes
from patient notes, clinical trial reports, and other electronic health records”.
The beauty of Comprehend Medical is that requires no ML
expertise, no complicated rules to write, no models to train, and it is
continuously improving.
It is in use at the Fred Hutchinson Cancer Research Centre,
home to three Nobel laureates, where interdisciplinary teams of world-renowned
scientists seek new ways to prevent, diagnose and treat cancer, HIV/AIDS and
other life-threatening diseases.
Matthew Trunnell, chief information officer at the institution,
gives a powerful perspective on its use: “Curing cancer is, inherently, an
issue of time. For cancer patients and the researchers dedicated to curing
them, time is the limiting resource. The process of developing clinical trials
and connecting them with the right patients requires research teams to manually
sift through mountains of unstructured medical records to look for treatment
insights. Amazon Comprehend Medical can reduce this time burden from hours to
seconds. This is a vital step toward getting researchers rapid access to the
information they need when they need it so they can find actionable insights to
advance lifesaving therapies for patients.”
In South Africa, the Department of Health is working to
create paperless hospitals in the country.
Partovi spells out the clear benefits: “Paper-based clinical
records in healthcare facilities result in extended patient waiting times – sometimes
between 60 and 80 minutes; reduced quality of care due to files being lost in
overcrowded filing rooms; and increased litigation costs. Using Amazon
Comprehend Medical, regional public hospitals implemented indexing systems for
easier retrieval of scanned patient records.
“Called Hybrid e-scripting, the solution enables electronic
data storage without typing, an e-sketch pad for electronically accessible
medical diagrams, and easy-to-use automated pharmacy labelling to reduce
medication dispensing time. The impact to implementing this solution was a 90%
reduction in patient wait time for fulfilling prescriptions, a 10% reduction in
patient hospital wait time, and a cost savings of R1- million in software licenses.”
And then there is the Covid-19 pandemic and the massive
challenge of tracking exposure. History may well record this as one of the
great triumphs of AI and ML. For example,
South African developer A2D24, was in just three days able to develop and
deploy an automated AI platform using Amazon Lex for a private hospital group,
to inform anyone who has been in one of their hospitals of possible exposure to
a confirmed COVID-19 patient.
The system automatically sends an alert message and conducts
an SMS based triage where, each day, patients are asked questions about the
type of symptoms they are experiencing and, based on the responses, the chatbot
recommends what to do, and whether to seek further medical help.
“This application has helped provide critical care to
thousands of patients and staff across the country, and potentially prevent
many new infections,” says Partovi.
The fundamental issue of messy patient data remains, however,
he says.
“A challenge to fully realising the potential of ML in
healthcare is health data locked in unstructured medical text, which makes
applying ML time consuming, costly, and sometimes impossible. Having patient
medical data consolidated into a secure data lake, organized in a standard
format, and properly indexed with key entities identified, is key to making
this vast amount of information searchable and ready for applying ML learning
on top, to derive insights and relationships for improving patient care.”
Get that right, and the long-term potential is incalculable.
Says Partovi: “We’re seeing a renaissance in healthcare as
more of our customers leverage ML technologies to uncover new ways to enhance
patient care, improve health outcomes, and ultimately save lives.”
- Arthur Goldstuck is founder of World Wide Worx
and editor-in-chief of Gadget.co.za. Follow him on Twitter and Instagram on
@art2gee
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