Technology can play a big role in assisting you with this process and alleviating costly mistakes and lost revenues.
We offer several ways to help streamline the coding process, and speed up the revenue cycle.
Our AbbaDox workflow portal has an integrated coding module. It eliminates the need to physically distribute documents to coders. Because the application is in the cloud, the coder may even be located in a different country or continent. A document’s chain of custody always remains with AbbaDox so files are never lost, and if questions arise, a record can be tagged with a note or reviewed by another coder or coding supervisor. Coders can review historical documents since the documents are stored in the patient chart.
Documents, including transcribed reports, scanned documents and lab and pathology reports, are stored securely on the AbbaDox Cloud. With role-based security, access is granted only for those who need to know.
The coding workflow separates the coding process into four major categories: coding queue, coding review, coding approval and completed. Completed codes are transmitted to the billing system.
AbbaDox produces reports based on the coding information including patient encounters by coder, date of service, date coded, and CPT, ICD or modifier codes.
Natural Language Processing
Another way IDS can help automate the coding process is with Natural Language Processing (NLP.) When implemented properly, NLP can improve coding consistency and accuracy. By applying algorithms, the technology scans clinical documentation and suggests appropriate medical codes, such as ICD-10 or SNOMED to assign to the case. It can automatically extracts key phrases from dictations or reports created by providers and maps terminology that is clinically relevant to codes. By automating data associations, organizations can streamline many processes such billing, meaningful use, compliance and clinical decision support.
In this way, NLP can be instrumental in the transformation of healthcare delivery. Reducing manual data entry and extraction processes allows data to be parsed, making it easier to move, store and share. This data-driven approach follows the trend toward an outcomes-based healthcare model.
Natural Language Processing assists numerous clinical applications and integrates with a host of applications including medical transcription and clinical documentation, EHR, and quality management.
By embedding intelligent language processing tools into clinical documentation workflows, IDS technology identifies clinical concepts such as Problems Diagnosis, Medications, Allergies, Labs and Procedures and codes them according to standard coding protocol such as ICD-9, ICD-10, SNOMED and Hierarchical Condition Categories (HCC). These automated processes provide efficiencies and streamline payment and reimbursement workflows.
NLP can help compensate for productivity loss associated with EHR adoption by compiling data from different sources and reducing data entry time. The end result is physicians spend less time with an EHR.
All digital data makes multiple formats and EHR Meaningful Use reporting possible.
One of the best ways to tighten up the coding cycle is to look at the originating points, such as the patient encounter. Physicians and hospitalists can identify the services rendered at the point of care. This can ensure patients are charged comprehensively and compliantly for the services, medical devices, or medications they receive.
Recording these services at the point of care means far fewer missed or lost charges and a more efficient revenue cycle. And because the application works on a mobile device, it is easy and fast, a process physicians can complete in seconds.