In today’s rapidly advancing digital world, autonomous medical coding solutions are changing the landscape of the healthcare revenue cycle. It isn’t a matter of if autonomous coding will gain widespread adoption, but rather a matter of when, particularly if your organization performs a large volume of procedures.
During a recent presentation, members of the audience were asked about their timeframe for implementing an autonomous coding solution. 76% of the audience was twelve months or more out from implementation. This group is in a perfect position to take some necessary steps to ensure a highly successful go-live experience with a high direct to bill percentage. Regardless of your timeline for implementing a solution, it’s never too early to begin planning.
Because autonomous coding solutions are unique from computer assisted coding (CAC) in being trained on historical data, a highly successful roll out is dependent upon the quality and accuracy of information provided to train the model. To achieve the highest direct-to-bill rate possible at go-live there are three main areas that should be addressed.
It’s no secret that the number one key to correct coding and reimbursement is complete and accurate documentation. While the autonomous coding models are more forgiving with documentation than CAC, models still cannot code what is not documented in the report. The more robust the documentation, the better the output.
To see to it that all applicable codes will be assigned accurately, it is important to review all radiology report templates to ensure all required elements for coding and billing can be captured in the final radiology report.
CPT & HCPCS Coding
Key items that should be in each template to ensure correct CPT & HCPCS coding:
- A clear, concise exam title;
- Detailed technique/parameters for the test being performed (ie, number and types of views, without and/or with
- Documentation of all supplies utilized (ie, contrast materials, radiopharmaceuticals, etc.);
- Supporting documentation for all selected quality measures.
The assignment of accurate diagnosis codes presents its own unique challenges when it comes to documentation. Emphasis should be placed on clear and comprehensive documentation of both the presenting clinical indications and the impression specified by the radiologist to ensure correct ICD-10-CM coding.
The ICD-10-CM Official Coding Guidelines for Outpatient Reporting require that encounters are coded to the highest level of specificity. This information is typically found in the impression. When there are findings in the impression that are related to the reason for the exam, this condition should be coded as the first listed (primary) diagnosis for the encounter. If the impression is normal, correct code assignment is based on the presenting clinical indications noted in the reason for exam or history fields.
Some radiologists will state in the impression “see findings”, but often there are findings listed that are considered incidental or not clinically relevant to the reason for the test. It is a best practice for the radiologist to prioritize findings in the impression section of the radiology report.
In general, it is recommended for radiologists to follow the ACR Practice Guideline for Communication of Diagnostic Imaging Findings for final reports. Following these guidelines ensures all required elements for coding and billing will be documented in the report.
Implementation of an autonomous coding solution is a great opportunity to improve your current workflow affecting coding compliance.
In addition to the radiology report, the medical record is composed of other documents often stored in the radiology information system (RIS) including diagnostic test orders, patient questionnaires and technologist worksheets. While these items are all part of the patient medical record, it is a best practice for all key elements needed for complete coding to flow into the final radiology report itself.
In particular, it is important to note that Center for Medicare & Medicaid Services (CMS) charges the referring (ordering) physician with documenting medical necessity for any diagnostic tests that are ordered. This information is communicated via the diagnostic test order. The reason for the test provided by the ordering physician should be entered into a predefined field in the RIS to auto-populate the radiology report. While additional information can be taken from the patient and added to the report, it should not be considered as the primary source for ICD-10-CM coding.
Regardless of your coding process or workflow, when information needed for coding is not contained in the radiology report (indications supporting medical necessity, supplies, exam parameters, etc.) this is very disruptive to the coding workflow, as the coder must go searching for this information in the RIS, or place the encounter on hold for someone else to research, slowing down the coding process, resulting in decreased productivity.
Furthermore, if this has been and continues to be an ongoing problem, this will affect the performance of the model because it cannot learn to code accurately what is not documented in the radiology report. Additionally, if this problem persists after go-live, the model will not be able to code these encounters, they will be routed to the coders for review and the model misses the opportunity to learn from the final code assignments.
Since the model initially learns to code from historical data, achieving a high direct-to-bil percentage at go-live is heavily dependent upon the quality and accuracy of historical coding and documentation.
Proactive steps to ensure coding quality include:
- Perform coding audits on a regularly scheduled basis, either monthly or quarterly. While coding audits may be done internally, it is prudent to periodically hire an external auditor for a fresh perspective to determine if there are any areas of concern that may have been missed through the internal auditing process. It is imperative to identify any potential coding and compliance issues and implement corrective action prior to go-live
- Implement written coding directives to limit subjectivity and promote coding consistency among members of your coding team. This will minimize variations in how certain encounters are coded and this information will help your chosen vendor in guiding the model to perform to your specific expectations. Additionally, this information is helpful after go-live to ensure that any edits made to coding engine output are made in the same manner by each coder so as not to confuse the model.
- Provide coder education on a regular basis. This will ensure high rates of accuracy and consistency are maintained.
Taking these proactive steps ensures the model is trained with the most up-to-date coding guidelines for your organization.
By focusing on comprehensive documentation improvement, refining CPT & HCPCS and ICD-10-CM coding practices, optimizing workflow, and placing a magnifying glass on coding quality, providers lay the groundwork for an autonomous coding solution that’s both effective and efficient. Regular audits, ongoing education, and a commitment to consistent quality assurance will ensure the highest direct-to-bill rates and an autonomous coding solution that is trained on the very best historical data.