The clinical documentation improvement (CDI) market is growing significantly due to the transition to value-based care models and the importance of accurate clinical documentation for healthcare revenue. Incomplete or inaccurate documentation can lead to denied claims and lost revenue. Hospitals are implementing CDI software and tools using clinical natural language processing and machine learning to automate documentation processes and identify coding opportunities to optimize reimbursement and minimize revenue loss.

2. The clinical documentation improvement (CDI) market is set to reach USD 4.5
billion by 2023, at a compound annual growth rate (CAGR) of 7.9%. And for
good reason.
With 23 states embracing a value-based care model to improve their healthcare
systems, the spotlight is firmly on clinical documentation.
Appropriate clinical documentation is the lifeblood of healthcare revenue
streams. Missing or incomplete documentation of diagnosis or treatment could
result in delayed, denied, or partially paid reimbursements from payers.

3. A build-up of such cases not only makes it difficult for hospitals to
sustain their emergency medical practice, but also causes financial,
legal, and reputational damage through charges of medical fraud and
abuse.
As terrifying as the consequences of inadequate documentation are,
they can be avoided. In order to minimize claim denials and rejections,
and maximize reimbursements, hospitals need to understand the
factors that could lead to loss in revenue.

4. Leading Factors that Cut Down Revenue
The alarming number of rejected reimbursements calls for serious
consideration of the loopholes that lead to denied or rejected claims:
Missed information: Since the coding process directly impacts the revenue of
healthcare organizations, accuracy is imperative.
Coders need to extract relevant information from medical reports and assign
accurate diagnosis and treatment codes for each clinical identifier. The quality
of codes is, however, reliant on proper documentation by the healthcare
provider.

5. Under- and over-coding: Under-coding involves registering codes for
treatment or diagnosis that cost less. As a result, hospitals suffer in the
long run from reduced, and often denied claims. In 2016, the cost of
under-coded claims cost hospitals and healthcare institutions USD 1.2
million.
Over-coding or upcoding violations, on the other hand, involve assigning
costlier diagnosis and treatment codes for higher billing values. Both these
practices are considered medical fraud and could result in hefty fines and
legal complications.

6. Unbundling: Another fraudulent practice is to unbundle code. This refers to false
reporting that involves using separate codes for procedures that fall under one code
category.
Like over-coding, this leads to higher billing value and is considered medical abuse.
The transition to ICD-10, and the subsequent complexity, as a result, has further
contributed to billing errors, missing information, and inadequate patient coverage. It
has affected operations, data analysis, reporting, and IT systems that use diagnostic
and procedural information. Employees who are not up to date with the changes are
more prone to create erroneous documentation due to inaccurate coding practices.

7. The transition to ICD-10, and the subsequent complexity, as a result, has further
contributed to billing errors, missing information, and inadequate patient coverage. It
has affected operations, data analysis, reporting, and IT systems that use diagnostic
and procedural information. Employees who are not up to date with the changes are
more prone to create erroneous documentation due to inaccurate coding practices.
A lack of understanding of medical terminology in the patient’s discharge summary
also leads to inaccurate coding. As a result, a patient may have to undergo more than
their required diagnostic or surgical procedures.

8. According to Black Book Market Research, 90% of hospitals reportedly
boosted their revenue by at least USD 1.5 million after implementing
CDI software. The CDI tools help represent patient health information,
clinical status, and EHR office visits as data codes.
These codes are used to report quality, process reimbursements, track
diseases, and manage administrative and clinical processes. This results
in revenue gains which are significant for hospitals.
Your Secret Weapon to
Revenue Generation

9. Accurately coded CDI is a necessity in boosting operational efficiency in healthcare.
Increased documentation demands in the electronic health record (EHR) sector, has
seen an increase in erroneous manual processing of poor-quality redundant
information. With physicians spending more time looking at screens rather than with
patients, more than 40% of healthcare givers are experiencing burnout and
depression.
With the help of AI and clinical NLP-assisted CDI, hospitals can:
• Improve legacy CDI to minimize revenue loss.
• Identify opportunities for optimal reimbursement.
• Streamline the CDI process for increased efficiency.
Some of the ways that strategically chosen AI-tools are bringing in new-age
transformation in CDI include:
Words of Wisdom

10. 1. Clinical NLP: Much time is consumed in analyzing physician documentation. In
case of a discrepancy, the time required is more. Clinical NLP can automate
documentation processes, reducing the need for medical note-reading staff, and
drastically bringing down the time required.
2. Machine learning: With a dramatic increase in medical literature produced,
machine learning can help medical experts stay up to date. This AI technology
helps with feedback and training, enhancing learning outcomes.
3. Computer-assisted physician documentation: This AI tool analyses physician
documentation to provide real-time feedback and resolve inaccuracies.
Words of Wisdom

11. As these technologies evolve, so will their implementation in the healthcare
domain. ezDI’s CDI solution (ezCDI) solution allows for the transformation of
clinical data into opportunities for quality and compliance and revenue
improvement. By automatically identifying missing or incomplete diagnoses from
any clinical documentation, the ezCDI software can help hospitals establish
steady revenue generation. Alongside this, the ezNLP offers a cohesive service
platform from which hospitals will gain crucial insights from unstructured data
which can then be quickly and easily organized into a structured format for use in
immediate clinical analysis. By reducing cost, time, error margins and effort spent
in processing and clinical coding, ezNLP will enable hospitals to receive quick and
accurate healthcare expertise in near-real-time.
Words of Wisdom

12. To learn more about ezCDI and what it can offer you, follow the link here. For more
information on ezNLP, also follow this link.
To learn more about ezDI’s AI-based mid-revenue cycle management solutions
visit www.ezDI.com and to see the live product demo of our Clinical Documentation,
Coding, Compliance/Auditing, Quality Measures, Encoder, and Enterprise
Analytics request a live demo.
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13. Contact us
Visit Our Website:- https://www.ezdi.com/
Address:- 12806 Townepark Way, Louisville, Kentucky
40243