In the decade since its introduction to the US healthcare system, the value-based care (VBC) model has picked up a tremendous pace. The rapid growth has been a direct result of an organized effort among commercial and public insurance providers and healthcare organizations to move from a ‘fee-for-service’ to a ‘fee-for-value’ model.
The shift towards a value-based model was initiated in October 2007 through the implementation of the Centers for Medicare and Medicaid Services’ diagnosis-related groups (CMS-DRG). According to this new clinical classification system, inpatient diagnoses and treatment procedures are documented using the International Statistical Classification of Disease and Related Health Problems (ICD) codes. The ICD codes (developed by WHO) allowed hospitals to accurately document diagnoses and procedures, which in turn helped hospitals determine reimbursements based on care quality.
The Shift to ICD-10
In October 2015, hospitals and healthcare organizations across the US transitioned to the tenth version of the ICD, the ICD-10-CM/PCS (clinical modification and procedure coding system). Compared to its predecessor, the ICD-9-CM, the new code system introduced 19 times as many procedure codes and 5 times as many diagnosis codes. The ICD-10-CM/PCS uses 3 to 7 character-long alphanumeric codes compared to ICD-9-CM’s 3 to 4 character-long numeric codes.
The extensive range of codes allows healthcare providers to capture diagnoses and treatment in greater detail leading to optimization of reimbursements. The extensive specificity of the ICD-10-CM/PCS codes helps insurance providers identify acute areas of care, trends, and costs. Moreover, by allowing the clinical information to be recorded in finer detail, the ICD-10-CM/PCS offers an accurate method of evaluating care quality and novel treatment procedures. This information can, in turn, be used to reallocate resources and promote enhanced care quality through patient and physician buy-in.
While the benefits of implementing the ICD-10-CM/PCS are numerous and very apparent, the adoption of the advanced clinical coding system has been slower than anticipated.
The sluggish adoption rates are a result of the complications that come with implementing the new system. The large volume of codes in the ICD-10-CM/PCS, a staggering 141,747 codes, makes it a herculean task for coders to accurately assign codes and even harder to identify coding errors. Since the accuracy of these codes determines proper reimbursements, these errors adversely impact the hospitals’ revenue stream. The greater specificity of sensitive patient information is an additional point of vulnerability for healthcare security systems.
Besides the complexity of codes, it is often difficult to keep pace with the American Hospital Association (AHA) ICD-10-CM/PCS Coding Clinic changes. The Coding Clinic changes is essential for coding professionals, HIM professionals, and CDI specialists to gain insights into modifications to codes and classifications.
The crux of the problem lies in the fact that most hospitals continue to rely on manual coding procedures and legacy information systems. The advent of technology and the digital maturity of the healthcare industry provides healthcare organizations with an avenue to resolve the complex issue of the ICD-10-CM/PCS coding system.
Leveraging Technology to Achieve Accuracy: Computer-assisted Coding Systems
The rise of next-generation technology, such as artificial intelligence (AI) and its various applications like natural language processing (NLP) and machine learning (ML), promises to considerably simplify the coding workflow. As a result, they can also play a crucial role in optimizing the mid-revenue cycle management processes. Powered by these technologies, advanced computer-assisted coding (CAC) software has the potential to transform and expand the scope of the clinical coding framework.
Comprehensive CAC systems leverage the linguistic algorithm-based capabilities of NLP to analyze unstructured data sources, such as written medical notes, to identify and abstract relevant clinical markers. This information, terms, and phrases, are then parsed and the accurate ICD-10-CM/PCS codes are assigned to them. CAC software applications are also capable of utilizing contextual algorithms to simplify and communicate clinical briefs from written notes to various stakeholders across the entire coding value chain.
Leveraging the capabilities of CAC can allow hospitals to overcome the complexities of ICD-10-CM/PCS. Using NLP to identify clinical markers and codes, alleviates the burden on coders to manually go through every minor change to the Coding Clinic to assign correct codes. Moreover, CAC systems also ensure documentation accuracy which helps hospitals reduce denial, ensure proper reimbursements, and maintain a healthy revenue cycle.
Advanced CAC systems are capable of safeguarding protected health information (PHI) and ensure the confidentiality of sensitive patient information. Cloud-based, HIPAA compliant CAC systems come with comprehensive security protocols such as PHI data encryption and two-factor authentication to go the extra mile in protecting patient information.
The advantages of NLP-enabled CAC are not just limited to simplifying the transition to ICD-10-CM/PCS. These comprehensive tools can help hospitals increase data transparency by creating a unified source of information for all stakeholders to access. This, in turn, promotes collaboration between siloes to improve productivity. By providing real-time tracking of key performance indicators (KPIs), CAC systems provide hospital management with relevant insights to improve organizational performance.
To know more about or to get a demo of ezDI’s born-in-the-cloud, AI-powered CAC solution (ezCAC) please visit us at https://www.ezdi.com/computer-assisted-coding-software/
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.