How Artificial Intelligence is elevating Outpatient Medical Coding Automation

How 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.

What 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. 

How 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.  Experienced coders need not have to spend hours on coding simple charts when they can focus on other convoluted tasks that no machine can accomplish.

Benefits of AI in Outpatient Medical Coding

  • Tailored Patient Care

    AI analyzes the outpatient data collected from physician’s 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.

  • Computer 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. Additionally, AI powered CAC provides real-time feedback to the healthcare system and physicians about the precision of E/M codes of patient evaluation during their outpatient visits. Cloud-based systems are not only secure but also offer easy access to data, enhance data scalability, and reduce process downtime.

  • Computer 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 patient’s condition. AI technology can capture any specific conditions or comorbidities that may impact outpatient care.  

  • Real-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. 

  • Improved 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.

  • Interaction analysis

    Interaction analysis systems for outpatient care are typically done manually. These turn out to be laborious, time-consuming, and expensive. Artificial Intelligence’s 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.

On 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.



By designing a next-generation clinical NLP engine supporting advanced documentation and coding functions, EZDI turned their vision to reality. Their CAC and CDI solutions received tremendous feedback, providing system accuracy and ease of use. EZDI removes the data complexity and highlights what matters for healthcare professionals.

EZDI is a provider of AI-based mid-revenue cycle management solutions to Hospitals and Health Systems.

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