The importance of proper medical coding in a value-based healthcare ecosystem cannot be overstated. The sheer accuracy of the medical coding process plays a crucial role in maintaining patient records and a healthy revenue cycle, with incorrect coding inevitably resulting in claim denials or reduced reimbursements from payers. However, increasing complexities in coding protocols have caused healthcare institutions to grapple with upholding the efficacy of the medical coding process.
With the introduction of the ICD-10 coding classification in 2015, the coding and documentation process has become a complicated affair. Moreover, the CMS has been known to modify codes as frequently as three months. As a result, hospitals face an uphill struggle to optimize their coding framework and maintain a steady revenue channel. According to the 2019 report “Medicare Fee-for-Service Supplemental Improper Payment Data” by Centers for Medicare & Medicaid Services (CMS), 80% of improper payments were a direct result of incorrect coding.
When it comes to incorrect coding, the consequences are numerous. While revenue loss is the most obvious and direct result of improper coding, the repercussions of inaccurate coding go far beyond adversely affecting revenue cycles.
The Repercussions of Improper Coding: Beyond Revenue Loss
The most important aspect of the value-based care model is ensuring the quality of care. The purpose of accurate coding, among other things, is to ensure the delivery of enhanced care quality. Inaccurate or improper coding defeats this purpose and could lead to irreparable damages. For instance, assigning incorrect diagnosis codes leads to wrong procedures that could prove fatal for the patient.
Codes vary slightly with the specifics of each diagnosis. This makes it one of the most error-prone areas of the coding process. Such errors could result in chaos and confusion that ultimately causes a breakdown of long-standing relationships between patients and hospital care providers.
Another significantly adverse consequence of improper coding is fraud and medical abuse charges. Medical abuse occurs when medical codes falsely represent treatment, intentional or not, that lead to monetary gains for hospitals. Circumstances such as these are considered fraud and are violations of the Federal Civil False Claims Act (FCA). The penalties of violating the FCA could amount to up to three times the value of the false claim. Moreover, a history of such violations could result in the loss of reputation.
Getting ahead of it with AI/NLP based CAC
The consequences of financial and reputational damage from improper billing are terrifying and often take a lot of time and effort to recover from. But hospitals are not left completely helpless in the bleak shadow of these disasters. With the advent of innovative technology, hospitals are striving to constantly improve their processes and avert revenue loss due to inaccurate medical billing and coding errors.
This is where AI-powered computer-assisted coding software comes into play. These systems leverage specific linguistic algorithm capabilities of NLP to extract clinical indicators from unstructured data, such as notes and prescriptions. This information can then be used to allocate suitable clinical codes. Moreover, voice-enabled NLP can be instrumental in extracting relevant information from dictation for easy identification and translation to the recommended coding format.
AI- and clinical NLP-enabled CAC streamlines the clinical coding process and allows organizations to significantly reduce denials and ensure superior care quality. Additionally, the speed at which these tools operate boosts the overall productivity of the coding team. Hospitals, therefore, will not only eliminate inaccuracies in their code – but will be able to do so efficiently. The CAC tool also detects the pattern and probability of claims denials. This can guide the billing team to focus on specific areas to maximize payment returns.
AI-powered CAC software has the potential to streamline hospitals’ coding programs and add value to their revenue streams. This allows them to maintain a robust coding framework while pushing forward to introduce innovations that could establish them as pioneers in transforming the healthcare industry. For hospitals, offerings such as ezDI’s suite of Computer Assisted Coding solutions that leverage clinical natural language processing will provide relief against the struggles of improper coding. ezNLP is a comprehensive service platform that helps hospitals gain crucial insights from unstructured data and then organizing that data into a structured format to be used for clinical analysis. This software as a service reduces cost, time, error margins and effort spent in processing and clinical coding so that hospitals can receive quick and accurate healthcare expertise in near-real-time.
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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.