How Artificial Intelligence Is Optimizing RCM?

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How Artificial Intelligence Is
Optimizing RCM?
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How Artificial Intelligence Is Optimizing RCM?
It is widely accepted among the practitioners
that Revenue Cycle Management (RCM) has become
increasingly more complex day by day due to the
abundance of tagged data. However, applying AI to
revenue cycle management could be the
technologys biggest break in the healthcare
sector. For instance, Various manual and
redundant tasks that are taking place in patient
access, coding, billing, collections, and
denials, can be automated using AI. What exactly
AI does? AI is imitating intelligent human
behavior with the help of various algorithms that
find patterns and plan future actions to produce
a positive outcome. AI is slightly different from
other emerging technologies such as machine
learning or robotic process automation, which can
identify patterns like AI but focus on improving
accuracy rather than achieving positive
outcomes. We know artificial intelligence is
helping optimizing revenue cycle management, but
how? we have illustrated below Role of AI in
prior authorization The most stressed issue in
RCM is prior authorization due to its
transactional nature and AI is proven to be the
best use case for this in the healthcare sector
lately. Currently, various cases such as needing
prior authorization, submit requests to payers,
and check statuses of claims are identified with
the help of real-time analytics and machine
learning and these technologies are are
leveraging AI. Moreover, AI and robotic
automation can be used to allow providers or RCM
partners to auto-correct the claims and prepare
any supporting documents in advance.
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How Artificial Intelligence Is Optimizing RCM?
Real time analytics by AI AI-powered RCM helps
both practitioners and patients in
decision-making. for instance, Providers need to
know in real-time who is cleared to be treated
financially and Patients need to know what
theyre responsible for paying which enables
patients to choose treatment options that are
good for them. AI powered RCM reduced the risk
of Claims Denial RCM is a mundane job. You have
to manage many processes manually which includes
entering the details of every patient, write the
code for the procedures and perform a quality
check. As the number of patients increases
operating costs also go high and you need huge
manpower to manage your revenue cycle. Adoption
of AI and automation can reduce your operating
expenses drastically. Clean claims submissions
play a crucial role in insurance submission for
healthcare practices. Recent research finds that
Insurance claims cost hospitals approximately
262 billion annually, and this total doesnt
include unnecessary processing costs to insurers
and intermediaries. AI helps you to identify
potential denials and fix them before they go out
the first time. AI also helps to detect missing
charges before claims are filed so that a more
complete claim can be filed and paid timely. AI
can even be used in place of rules-based methods
that are often time-consuming and difficult to
maintain.
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How Artificial Intelligence Is Optimizing RCM?
After the penetration of AI, the handling of
claim denials can now be electronically grouped
to tackle claims with similar rejections for
faster turnaround. Future of AI in RCM RCM space
is now adopting AI as-a-service which allows
healthcare organizations to outsource AI
technology, which enables providers to experiment
with AI for RCM without heavy upfront
investments. Moreover, AI-as-a-service is
focusing on offering that maintenance aspect, as
well as using machine learning capabilities and
learning thats taking place across a neural
network to enhance that bot. The service enables
providers to engage with AI to optimize revenue
cycle management and even beyond. At
MedisysData, we are continuously keeping track of
the application of AI in the industry and monitor
the benefits from a user perspective. We have
successfully built bots to automate sub-processes
in Revenue Cycle Management such as
Transcription, Coding, Billing, and most
importantly AR Denial Management.
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