Natural language processing (NLP), along with machine learning, deep learning, computer vision, and image recognition, are all branches of artificial intelligence (AI). The goal of NLP software is to build computer systems that will accept input in the form of spoken or written language and will provide spoken or written output i.e. communicate as if the computer system were a human.

1. Impact of NLP on Healthcare Industry
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2. Natural language processing (NLP), along with machine
learning, deep learning, computer vision, and image
recognition, are all branches of artificial intelligence (AI).The
goal of NLP software is to build computer systems that will
accept input in the form of spoken or written language and
will provide spoken or written output i.e. communicate as if
the computer system were a human.
Thanks to devices and applications like Alexa, Siri, Google
Assistant and Cortana, much of the world’s population has at
least a passing familiarity with NLP. It is being used today to
perform a wide range of tasks across many industries. Until
recently though, healthcare organizations have lagged
behind others in capturing the benefits NLP delivers.
However, they are beginning to catch up.

3. Here are several use cases for NLP in healthcare that
are already enhancing the field. Each of these will contribute
to the larger digital transformation of healthcare as
technology continues to advance.
Medical Coding and Billing
NLP streamlines the way medical coders extract diagnostic,
procedural and other clinical information. Rather than a coder
reading documents and converting them to alphanumeric
codes, NLP reads them and submits the codes to the coder
for verification.This allows the human coder to work on
documents that NLP cannot process accurately, and reduces
the overall expense of coding medical information. In the end,
more accurate and thorough coding results in more accurate
and timely billing.

4. Virtual Nursing Assistants
The rise of virtual nursing assistants capable of communicating
with patients using NLP is underway. Regular communication
between patients and the nursing bot extends care beyond
the walls of the clinic room without burdening existing
resources.Adherence to the patient’s care plan can be
monitored, and triggers can notify providers of issues that
need human attention. Patients can receive round-the-clock
access to support and answers, including help with
medication. Researchers in this field estimate virtual
nursing assistants will reduce U.S. healthcare costs
$20 billion by 2026.
Robot-Assisted Surgery
Some surgical robots use AI to apply information obtained
from prior surgeries to the current case, leading to
progressively better outcomes. Beyond the many well-known
advantages, robotic surgery delivers, adding an NLP
component allows surgeons to query the system and to direct
its actions verbally.

5. Reducing “EHR Burnout”
Recent studies have indicated that healthcare providers spend
nearly half of each day updating electronic health records and
doing other administrative work, which is a matter of concern.
It leaves them with very less time to perform their core
functions of examining and discussing clinical, diagnostic and
treatment information with patients in a face-to-face
environment.
Entering and managing patient information is a major
contributor to physician burnout. More than half of physicians
surveyed in a Physician’s Foundation 2018 study, reported
entering data into the EHR reduces their efficiency
and detracts them from their interaction with
patients. Systems that use NLP allow physicians to enter
notes into the EHR by speaking to it.This saves time versus
having to type. Besides, it also allows patients to amend or
correct what the doctor is entering into the EHR.

6. Other Important Use Cases
While improving the clinical value of EHRs and reducing
physician burnout is one of the most pressing challenges
among healthcare organizations, NLP is contributing to the
digital transformation of healthcare in several other ways. For
example, NLP is helpful in
While improving the clinical value of EHRs and reducing
physician burnout is one of the most pressing challenges
among healthcare organizations, NLP is contributing to the
digital transformation of healthcare in several other ways.
Comforting patients who become confused and anxious
because they do not understand the data being presented to
them through a portal website. For instance, NLP can explain
the meaning of abbreviations and medical terminology. Rather
than leaving the patient to worry or call the physician to
explain the report, NLP can educate and possibly also calm
the patient.

7. Offering summarized updates of key ideas, concepts,
and conclusions contained in large volumes of clinical notes,
journal articles and other narrative texts gives practitioners
quick access to volumes of information that would otherwise
require a lot of time to read through.Easy extraction of
data from free-form text and insertion into fixed-field data
files, such as the structured fields in an EHR.Handling a
physician’s free-form spoken or text query, which is
especially useful for queries that require gathering and
organizing data from multiple sources.NLP and other AI
components can also accelerate the movement away from
fee-for-service models and toward value-based
healthcare by organizing unstructured health data
derived from EHRs and other sources. Much of that
“hidden” big data can shed light on health outcomes for entire
populations of patients, which has been impractical until
recently.

8. Like other businesses, if you too are looking for IT Solutions
for Healthcare Services, Mindfire Solutions can be your
partner of choice.We have significant experience over the
years working with Healthcare IT Companies.We have a team
of highly skilled and certified software professionals, who have
developed many custom healthcare solutions for our global
clients over the years.

9. ThanksYou
Content Source: Medium
Contented by: Mindfire Solutions