Revolutionizing Clinical Coding: A New Era in Healthcare Documentation

Healthcare involves multiple risk factors, one being handling the complexities of clinical documentation. The patient’s records and healthcare details are crucial to manage within the clinical space. They are further used for multiple pivotal processes including billing, reimbursements, insurance, healthcare policies & planning, and analysis of epidemiological areas.

Clinical coding converts patient records into encoded reports following a structured and unified coding system. Manually coding clinical data is a non-trivial and time-consuming task with high susceptibility to human errors.

As these further impact the other healthcare processes, even the slightest mistake in the process can lead to big blunders and far-reaching consequences. Clinical code assignment simplifies the complex and voluminous clinical records into standard clinical documentation.

“Clinical code is the unified foundation of storing, retrieving, and maintaining healthcare documentation.”

What is Clinical Coding and Why is It Crucial?

The process of clinical coding is a systematic process of deciphering the medical diagnosis, procedures, and clinical information into standardized codes. The assigned clinical codes are derived from the global coding system such as SNOMED CT (Systematized Nomenclature of Medicine-Clinical Terms), ICD, CPT, etc. These codes are assigned to ensure that the overall global health data records are processed, stored, and shared in a consistently structured format.

As per a report by Healthcare Finance, improper clinical coding costs the US healthcare system around $262 Billion annually.

This process allows for:

• Accurate billing and insurance claims
• Improved patient care approach
• Regulatory compliances

Though this process simplifies healthcare documentation to a great extent but also imposes a set of challenges that hinder the efficiency and accuracy of the healthcare ecosystem.

Present Challenges in the Clinical Coding

As we have already discussed above, clinical coding comes with a set of challenges. Even the expert coders with years of experience in the domain get stuck to fetch the right codes balancing accuracy and productivity at the same time.

Converting clinical documents into numeric codes or ConceptIDs is fundamentally important to follow a standard approach for recording or sharing clinical data globally. The challenges of clinical coding affect the overall operational and financial efficiency of healthcare organizations and hence, need to be addressed in some way.

Data Inconsistency & Manual Errors

The complexities of the clinical documents and complete reliance on human input are the best combination to bring about the chances of errors in code assignment and documentation management.

Considering the vast ecosystem of healthcare including multiple diseases, diagnoses, drug formulations, common symptoms, etc, understanding the clinical report accurately and assigning the right codes accordingly is challenging.

The chances of misinterpretations, typing errors, and mistakes in codes can cause data inconsistency, incorrect diagnosis, billing issues and affect patient care.

Complexity of Medical Codes

Millions of clinical codes are available with thousands of millions of code combinations possible. Assigning the exact and most accurate code as per the disease symptoms and diagnosis is as crucial as challenging.

Moreover, any inaccuracy in the process may further lead to incorrect reports, delayed billing processes and reimbursements, and false or inaccurate insurance claims.

Frequent Coding Updates

The coding standards for clinical codes are frequently updated. Any new symptom or disease identification, drug inventions, new diagnosis discoveries, etc causes changes in the coding ecosystem.

Clinical coders need simultaneous education or training for the updates for easy adaptation and maintaining accuracy.

Accuracy vs Productivity

Achieving accuracy as well as productivity in the clinical coding process is not a practical approach. While accuracy is essential for further operations like billing, or reimbursement, focusing solely on accuracy may hamper productivity to a great extent.

Complex Coding Cases

Sometimes clinicians or clinical coders encounter highly complex patient reports with no exact code matching. In such scenarios, they need to create the most matched clinical code combinations to represent the case complexity.

Time-Consuming Processes

Clinical coding is a slow and labor-intensive process, where clinical coders need to sift through lengthy clinical records to extract the required detail and match it to the right codes.

There are many more challenges that healthcare regulation authorities face due to inaccuracy in clinical coding like data processing delays, interdisciplinary communication, and more.

Simplifying Clinical Coding for Better Accuracy

The importance of clinical coding within the healthcare sector is indisputable as it affects overall operational efficiency. Technological advancements simplify the overlong and complex clinical coding process to a great extent. With technologies like AI, NLP, ML, and cloud-based platforms, clinical coders can address the inherent challenges of manual coding and reduce the chances of errors.

Automating the entire clinical coding is not the right approach as it anyway needs human intervention for either code verification or managing the flow of AI operations. But with the help of these technologies or clinical coding tools, the chances of manual errors, and inaccuracies across data, can be avoided while achieving time efficiency in the process.

Benefits of Automated Clinical Coding:

Improved Coding Accuracy

Maintain a high level of accuracy with clinical documents while avoiding manual errors in the clinical coding process.

Streamlined Workflows & Better Efficiency

Automated AI clinical coding helps clinical coders with an efficient and more streamlined coding approach.

Better Data Analysis

Analyse and process the medical report documents without missing any details for accurate clinical coding.

No Insurance Claim Inaccuracy

Any discrepancy in medical reports may lead to false or erroneous insurance claims, but with automation in clinical coding, insurance claims inaccuracy can be avoided to a great extent.

Healthy Revenue Stream

Speedy claim submissions, accurate medical billing, and reimbursement processes reduce the load of RCM staff and help create a better and healthier revenue cycle.

Accurate Reimbursements

Automating the process of clinical coding with correct medical codes, and low human errors results in faster claim processing and reduced denial rates to ensure accurate reimbursement.

Regulatory Compliance

Real-time auditing and minimized coding errors enhanced regulatory compliance adherence, avoiding claim denials and penalties due to non-adherence to the coding guidelines.

Docs4Docs: Bringing Down the Clinical Code Complexities

Docs4Docs is developed as a web-based platform to allow clinicians and health organizations to generate, manage, and share high-quality clinical documents. With the incorporation of advanced technologies, Docs4Docs automates the entire clinical documentation process with faster and more accurate clinical coding experience.

While developing Docs4Docs for our client, we struggled with building a function to fetch the right codes from the millions of available codes and maintain the accuracy level of clinical documents while balancing productivity. But with consistent brainstorming, strategic minds, and great coding skills, e have implemented various methodologies like custom AI logic, training AI with cross co-relations, vector database, etc.

How Docs4Docs works for clinicians:

Automated Code Assignment

After the document upload, Docs4Docs automatically converts the text report into image form to scan the clinical records, extract the medical terms, and assign relevant SNOMED CT codes.

Modification/Edit Window

Coders can check if the text extraction is correct or not to avoid any inaccuracy in the clinical codes.

Time-Efficient Clinical Coding

With real-time data processing and monitoring of medical data, Docs4Docs accelerates decision-making, and workflow efficiency and helps with administrative workload.

Human-in-Loop Approach

Even AI alone cannot handle the complexities of clinical coding, hence the expert clinical coder does the final verification of the assigned clinical codes to allow AI to generate the final report. Any changes in the codes can be made before report generation.

No doubt clinical coding is the cornerstone for effective and systematic clinical documentation. Everything works over data and for the healthcare industry, efficiently recording, processing, and sharing patient information is the utmost priority. Any kind of disparity in the data further affects the various processes including insurance claims, billing, reimbursements, fetching patient medical history, and more.