Epic's 'Look-Alikes' technology matches patients with
hard-to-diagnose conditions to similar cases from around the world,
using records from its massive Cosmos dataset
PITTSBURGH, Aug. 15,
2024 /PRNewswire-PRWeb/ -- AHN Becomes First Health
Network in Western Pennsylvania to
Utilize New Data Tool to Identify Rare Symptoms and Diseases
"When a patient has a rare or unusual
condition, finding the correct diagnosis and developing an
appropriate treatment plan is a bit like searching for a needle in
a haystack," said Susan Manzi, MD,
MPH, chair of the AHN Medicine Institute.
Epic's 'Look-Alikes' technology matches patients with
hard-to-diagnose conditions to similar cases from around the world,
using records from its massive Cosmos dataset
PITTSBURGH (August 15, 2024) – When patients have unusual
health symptoms or a rare medical condition, their doctors are
often left searching for similar cases by checking medical journals
or by chasing down peer specialists across the country. So-called
"rare disease odysseys" can be frustrating for caregivers and
patients alike – the process of narrowing the clinical
possibilities, visiting different specialists, obtaining a
diagnosis, and settling on a treatment plan can drag on for
years.
But now, Allegheny Health Network (AHN) has a new technology at
its disposal for tackling these rare diseases: Epic's "Look-Alikes"
tool, which is embedded into Epic's electronic health record (EHR)
system. Look-Alikes, in turn, scans Epic's "Cosmos" research
dataset, which houses billions of pieces of de-identified patient
data, drawing on 12.2 billion patient encounters gleaned from more
than 257 million patients, 1,500 Epic-affiliated hospitals and
352,000 physicians worldwide.
Using the Look-Alikes tool, AHN doctors can now query the Cosmos
dataset to find doctors who have treated patients whose symptoms
mirror the unusual cases they are seeing locally. Whether across
the state or across the country, if there's a strong match between
patients and symptoms, AHN's physician can connect with the doctors
who managed the similar cases, compare notes, and potentially
arrive at a diagnosis and treatment plan much more quickly.
The tool is bi-directional, meaning AHN doctors who have already
diagnosed a patient with one of the dataset's rare diseases can
also be contacted by other physicians who have patients with
similar symptoms or the same diagnosis. For now, the Look-Alikes
system flags symptoms related to 37 rare diseases – conditions such
as erythropoietic protoporphyria (a metabolic disorder that causes
severe pain when a patient is exposed to sunlight),
Beckwith-Wiedemann syndrome (which causes overgrowth of limbs and
organs), and Friedreich ataxia (which causes neurological
degeneration).
In June, AHN became the first health system in the region, and
one of the first in the U.S., to start using Epic's Look-Alikes
technology. Epic is one of the world's largest providers of
electronic health records technologies, and its EHR products are
broadly considered the industry's gold standard. AHN has been
utilizing Epic's EHR and patient-charting technologies since 2013,
and also utilizes Epic's patient-facing records portal, known as
MyChart.
"When a patient has a rare or unusual condition, finding the
correct diagnosis and developing an appropriate treatment plan is a
bit like searching for a needle in a haystack," said Susan Manzi, MD, MPH, chair of the AHN Medicine
Institute, and director of the AHN Autoimmunity Institute's Lupus
Center of Excellence. "With the Look-Alikes tool, we have the
ability to search for that needle far more efficiently – or better
yet, we can consult with someone who has already found it."
The Look-Alikes tool will prove especially useful for the
Autoimmunity Institute, and for patients with autoimmune diseases.
Autoimmune conditions, some of which are rare to begin with, can be
notoriously difficult to diagnose – symptoms can come and go, mimic
those caused by other diseases, vary from person to person, and
affect a variety of bodily systems simultaneously.
"AHN is a national referral center for many
difficult-to-diagnosis autoimmune conditions," Dr. Manzi said.
"This tool allows us to connect with other physicians in the
country that have similar patients but, more importantly, it
provides a tool for those physicians to find us."
According to Global Genes, an advocacy organization advocacy for
people fighting rare and genetic diseases, the average time from
disease onset to accurate diagnosis for a rare disease is 4.8
years. And even when a rare disease is quickly diagnosed, the
scarcity of similar patients often means there is little clinical
evidence to draw from when determining the best course of treatment
for a patient.
All AHN physicians – including primary care and specialty
providers – are able to utilize the tool. Many of the diseases
currently being tracked by Look-Alikes exhibit a combination of
neurological, musculoskeletal, hematologic and autoimmune
symptoms.
An AHN doctor utilizing the tool enters the patient's unusual
symptoms and other health indicators, known allergies, and
demographic information. Look-Alikes then scans the Cosmos dataset
for doctors treating similar patients and allows the physicians to
connect with each other. The system is intelligent: If no matches
are found, the system suggests similar searches that might find
matches.
And when an AHN doctor diagnoses the condition, the patient's
de-identified record can be "tagged" with the disease in question,
making it easier for other physicians to seek AHN's expertise.
"Through this tool from Epic, AHN physicians will be able to
augment rare disease research, physician collaboration, and
clinical decision support capabilities while still protecting
patient privacy," said John J.
Gabrick, AHN's vice president, Clinical Information
Systems.
Media Contact
Bill Toland, Allegheny Health
Network, 4123371738, william.toland@highmarkhealth.org,
www.ahn.org
View original
content:https://www.prweb.com/releases/ahn-becomes-first-health-network-in-western-pennsylvania-to-utilize-new-data-tool-to-identify-rare-symptoms-and-diseases-302223160.html
SOURCE Allegheny Health Network