Title: How Artificial Intelligence is elevating Outpatient Medical Coding Automation
1EZDI
- Transforming clinical data
- into actionable intelligence
2How Artificial Intelligence is elevating
Outpatient Medical Coding Automation
- Artificial Intelligence and Machine Learning
algorithms are transforming every industry, and
healthcare is not far behind. - Healthcare organizations are effectively
leveraging AI to allocate resources better,
anticipate patient outcomes and effectively
schedule personnel. - Artificial Intelligence and Machine Learning help
augment the ability of medical coders to code
outpatient services efficiently and accurately. - They help coders to focus their time on complex
tasks rather than coding simple charts.
3(No Transcript)
4What is outpatient medical coding?
- Medical coding, at a basic level, is a piece that
a coder takes and translates into a numeric or
alphanumeric coded format. - A patient who visits a medical practice or the ER
and is undergoing treatment but is not admitted
is considered an outpatient. - Outpatient medical coding focuses on the direct
treatment offered to a patient on a single visit,
typically a few hours. - Generally, outpatient care is for less than 24
hours. - Outpatient coding used ICD-10-CM for diagnosis
and reimbursement is primarily based on physician
fees, insurance rates, ambulatory rates and so
on.
5How does Artificial Intelligence help outpatient
medical coding?
- There are several limitations in a manual
outpatient coding process, such as reduced
productivity, lower case review rates, and
greater physician response time that reduces the
reimbursement speed. -
- The DRG assignment is not optimized through
manual coding and the staff will not be able to
track queries effectively. - Artificial Intelligence is a powerful automation
tool that can assist in addressing the
shortcomings of the manual processes in
outpatient coding. - This can help HIMs optimize the coding quality,
ensure quick reimbursement, manage hospital
finances better and improve patient care.
6Benefits of AI in Outpatient Medical Coding
7Tailored Patient Care
- AI analyzes the outpatient data collected from
physicians records, diagnostic results, lab
tests and compares them with medical protocols,
recommendations, and clinical procedures. -
- Through the results, medical staff can determine
any additional tests required and the best course
of treatment for the patient. - AI allows us to tailor medical solutions in
outpatient care.
8Computer Assisted Coding (CAC)
- Computer Assisted Coding or CAC is an
amalgamation of various features of AI and NLP. -
- AI-powered CAC software can scrutinize and
interpret physician notes, assign modifiers,
identify errors, and catch coding edits, freeing
medical coders on other tasks. - Its dedicated algorithms can extract clinical
facts and assign the appropriate E/M code. - Physicians need to no longer worry about
identifying, extracting, and feeding it into the
system.
9Computer Assisted Physician Documentation (CAPD)
- AI enabled CAPD added to EHRs (Electronic Health
Records) helps medical staff to fix gaps in
clinical data. - AI tools can review the documentation and guide
the healthcare provider to correct the
documentation to accurately reflect the patients
condition. - AI technology can capture any specific conditions
or comorbidities that may impact outpatient
care.
10Real-time feedback
- Real-time feedback helps coders improve faster.
- Assume that a new coder makes a mistake in coding
an outpatient chart. - His AI assistant will immediately flag the
mistake, recommend a solution, and inform the
coder of the repercussions of the change. - This way, the accuracy issue is caught the same
day while the case is new and before it goes to
billing.
11Improved Billing Procedures
- AI technology allows medical billing staff to
enhance the efficacy and efficiency of the
outpatient coding and billing process. - Many companies are adopting AI applications to
simplify manual coding labor. - Apart from processing codes and huge data
volumes, AI can considerably reduce working hours
and human error.
12Interaction analysis
- Interaction analysis systems for outpatient care
are typically done manually. - These turn out to be laborious, time-consuming,
and expensive. -
- Artificial Intelligences computerized algorithms
can make this process more cost-effective and
easier. - The technology also allows us to explore beyond
the established boundaries of patient-physician
communication.
13On a large scale, AI/ML solutions can pinpoint
common mistakes in outpatient medical coding,
tighten the floodgates against coding errors, and
improve documentation. Through real-time
feedback, coders can enhance their skills.
Top-tier coders can focus their attention on
complex cases rather than routine menial tasks.
14Contact Us
- Visit https//www.ezdi.com/
- Phone No. 8866408081
- Email team_at_ezDI.us
- Address 12806 Townepark Way Louisville United
States Kentucky 40243