Quire Granted Patent on Text-Powered, Predictive Modeling for Healthcare

MEMPHIS, Tenn.–(BUSINESS WIRE)–The United States Patent and Trademark Office has granted Quire,
Inc
, a patent
on the company’s method for using text in medical records to predict
health outcomes, risks, and behaviors. The unique method uses
practitioner observations, captured in clinical notes, to build a
patient’s “story” which can then be used to identify and prioritize
patients with similar stories for outreach and interventions.

“Text is the easiest data to manage, contains the richest information on
patients, but can be a challenging data-type from which to extract
actionable information. Quire’s capability enables practitioners to
quickly build, test, and implement predictive models using only text,”
said Quire CEO Brad
Silver
.

For Brigadier General (Ret) Stephen
N. Xenakis, M.D
., Quire allows him to scale his knowledge to assess
hundreds of thousands of people, fast. “In my areas of interest – risk
prediction for suicide and dangerous behavior – only 53% of the people
at risk for harm have self-selected for treatment or support. However,
100% of the people with serious problems have clinical signals, recorded
in notes, like insomnia, headaches, alcohol use, relationship problems
etc. recognized as patterns alerting practitioners to be concerned.”

With value-based care, the largest portion of immediate savings
opportunities are related to proactive management of patients with
chronic conditions. Provider notes offer the most detailed and nuanced
understanding of patients and their propensity to engage, or not, in
behaviors which increase the risk of emergency room visits or inpatient
admissions.

“Social and behavioral determinants of health are a hot topic with
providers. Many health systems are spending tons of time and money to
implement assessment templates, which will be inconsistently used, to
collect this information. However, this data already exists, because the
people treating patients record things like, ‘transportation is a
problem, no family support, can’t afford medications, etc.’ Quire uses
this information in notes to predict who should be prioritized for
outreach,” said Silver.

Text also enables practitioners and operators to unpack drivers of poor
outcomes and make workflow adjustments to address those drivers in
clinical process. “A big challenge with AI and deep learning approaches
is that they are still a black box. These methods can produce good
predictions, but they don’t reveal why. With Quire’s unique approach to
predicting outcomes, the underlying basis for the predictions can be
more readily teased out of the text,” explained Ramin
Homayouni, Ph.D
., Quire’s chief scientist and current director of
Population Health Informatics at the Oakland University William Beaumont
School of Medicine.

Silver added, “Quire gives providers the ability to leverage, at a
population-level, the best means of recording interactions with
patients, their notes.”

ABOUT QUIRE

Quire provides software and services needed to extract actionable
information from text. With a focus on healthcare, the company also
provides capabilities to law enforcement and other markets where text
contains data needed for decision-making.

Contacts

Brad Silver | brad@quiredata.com
| 901.866.1624

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