Struggling with medical coding? Discover the best medical coding app powered by AI. Boost accuracy & efficiency.

In 2023, hospitals in the United States recorded approximately 33.68 million admissions. This data includes all types of hospitals, including community hospitals, which accounted for about 31.56 million of these admissions (American Hospital Association).

Every visit to a healthcare provider necessitates the creation of a medical bill with specific codes that health systems submit to insurance companies for payment. Converting the medical notes written by caregivers into billing codes for various diseases and treatments is a largely cumbersome and manual process. This process is prone to errors because it is done manually, despite our increasingly digital world. Over the past ten years, nearly every health system our life sciences team has encountered has experienced this common pain point.

Medical coders find themselves sorting through months-old notes to update clinically meaningless sections to ensure compliance with billing requirements.

Is there a better way? While medical coding directors/managers look for an answer to this question, MediCodio emerges as a helping hand.

MediCodio has come up with the best medical coding app designed meticulously to analyze the patients’ charts and suggest relevant medical codes.

By using large learning modules and robotic process automation, the best medical coding app will fetch the patient data from EMR and analyze the illness, treatments, and medical services provided to the patient, and then suggest appropriate codes. Medical Coders get an opportunity to verify and finalize the codes, before sending it to the billing module.

With MediCodio’s novel medical coding app, medical coders can generate real-time audit reports, which are critical to health systems. These reports are used to replace burdensome auditing processes as well as to give clinicians feedback about missed opportunities to document their work in order to optimize insurance reimbursement.

For example, A patient visits an orthopedic clinic for a knee replacement surgery. The medical coder, working manually, needs to assign the correct CPT (Current Procedural Terminology) and ICD-10 (International Classification of Diseases, 10th Revision) codes for the procedure and diagnosis.

Manual Coding Process:

The coder reviews the patient’s medical records and selects the following codes:

• • Procedure Code (CPT): 27447 – Arthroplasty, knee, condyle and plateau; medial AND lateral compartments with or without patella resurfacing (total knee arthroplasty)

• • Diagnosis Code (ICD-10): M17.0 – Bilateral primary osteoarthritis of knee

Mistake: The coder mistakenly chose the diagnosis code M17.0, which is for bilateral knee osteoarthritis, even though the patient only had surgery on one knee. The correct code should have been M17.11 (Unilateral primary osteoarthritis, right knee) or M17.12 (Unilateral primary osteoarthritis, left knee).

Consequences:

This error could lead to issues such as:

• • Incorrect billing and potential claim denials

• • Misleading patient medical records

• • Increased administrative burden to correct the error

Case Study: MediCodio’s AI Boosts Super Specialty Hospital’s Revenue and Efficiency

How the Best Medical Coding App Using AI Can Overcome This

AI-Powered Coding Process: Using an AI-powered medical coding app like MediCodio, the system automatically reviews the patient’s medical records, identifies relevant keywords, and cross-references them with updated medical coding databases.

AI medical coding app accuracy:

1. 1. Contextual Understanding: The AI tool understands the context of the surgery and recognizes that it was a unilateral knee replacement.
   2. Code Suggestion: It suggests the appropriate CPT code 27447 for the procedure and accurately identifies the correct ICD-10 code, whether M17.11 or M17.12, based on the detailed surgical notes.
   3. Real-Time Validation: The AI system validates the selected codes against the latest coding guidelines and payer-specific rules, ensuring accuracy before submission.

Benefits:

• • Reduced Errors: The AI medical coding app minimizes the risk of incorrect code selection by leveraging advanced algorithms and machine learning.

• • Efficiency: It speeds up the coding process, allowing medical coders to focus on more complex cases.

• • Compliance: The medical coding app ensures compliance with the latest coding standards, reducing the likelihood of claim denials and audits.

By using MediCodio’s AI-powered medical coding tool, healthcare providers can significantly enhance the accuracy and efficiency of their coding processes, leading to better patient care and optimized revenue cycle management.

MediCodio is a rapidly growing company already partnering with multiple hospitals and revenue cycle management firms in the United States. By tackling the highly error-prone area of medical coding, MediCodio is positioned to significantly reduce healthcare costs nationwide.

Integrate AI into your Healthcare Facility in 5 Easy Steps

Now that you understand how an AI medical coding app can positively impact your workforce and bottom line, how can you integrate it into your facility? Here are five steps to get started, using medical coding and revenue cycle management as examples.

1. 1. Assess Your Organizational Readiness: Half the battle of successful AI integration is ensuring your facility has the proper foundation. This involves a thorough evaluation of your organization’s current processes, IT infrastructure, and capabilities. What does this look like in the facility? Develop a complete understanding of your workflows and the requirements for an AI system to integrate successfully. Among other assessments, this comprehensive effort upfront will surface features and needs that enable a more targeted vendor search and a smoother implementation down the road. Also, consider your data management facilities. How much data is available to help fine-tune an AI application, and how is it organized? Answering these kinds of questions will help you determine if your organization is ready to implement AI.
   2. Identify Inefficiencies in Your Operations: Once your facility appears ready for AI, the next step is pinpointing where the technology can make the most significant impact. Start by evaluating your daily operations. Do appointment bookings and patient visits flow smoothly, or do bottlenecks exist? Examine your billing cycle: perhaps coding inaccuracies lead to claim denials and revenue losses. Also, consider patient care. Are there delays in diagnosis or treatment due to administrative overload? Identifying your pain points not only clarifies where AI can streamline workflows but also reveals opportunities to elevate patient care.
   3. Set Measurable Goals: Having identified potential AI medical coding apps, it’s time to set clear, achievable goals. What does success look like for your facility? It might be cutting billing errors by half, enhancing patient satisfaction scores, or fully automating coding for 90% of encounters. Establish metrics that matter, both qualitative and quantitative. For instance, you can track the reduction in administrative tasks to see how it impacts staff workloads, and you can measure patient feedback pre- and post-AI integration. Setting these targets provides a roadmap for implementation and a clear benchmark for evaluating AI’s impact.
   4. Research AI Vendors: Finding the best AI medical coding app for your company starts with research. Begin by cataloging the specific challenges and goals you identified from points two and three above. Next, assess the available AI providers. Which options have a proven track record in healthcare? Aspects to consider include compatibility with your current systems, ease of integration, and the level of support offered by vendors. Lastly, don’t forget to evaluate whether the solution can meet your goals. For example, can it scale with your facility? This research phase ensures you select AI tools that not only resolve current issues but also propel your facility toward future goals.
   5. Trial an AI Solution and Vendor: Trialing a vendor before selecting an AI medical coding app is highly recommended. The goal is to ensure the solution meets your facility’s needs and expectations. It’s not uncommon for vendors to make big claims. Any reputable vendors will welcome the audition and allow you to see their solution in action.

To know more about MediCodio’s AI medical coding app, schedule a demo here!