Updated on 17 September 2013
1) NLU technology can be used to uncover critical patient information in electronic health records for more accurate coding. By moving beyond mere recognition, NLU can identify missing pieces in the patient narrative, or can it extrapolate information within the EHR. This can create a fuller, richer patient narrative. It also can help to identify where there are holes in the narrative, or where there appears to be inaccurate information.
2) Also, NLU can be used in real-time physician prompting, as a viable (and cost-effective) way to improve workflow, speed and clinical documentation quality. This can be done by moving NLU to the front-end, real-time prompting can inform physicians of missing details as they are entering the patient's information. Many current workflow systems have NLU in the back-end. With this model, coders will inform physicians about missing information days after seeing the patient.
In this new workflow model (front-end NLU), physicians are not just providing input, but receive direct, immediately feedback from the system. NLU analysis and synthesizes evidence from all of the patient record to determine what additional information or specificity in the patient narrative the physician needs to provide. With this closed-loop structure, EHR systems can constantly monitor the information being provided and prompt physicians to reduce potential inaccuracies or deficiencies. In essence, one facilitates a virtual coding assistant who shepherds the physician through the complex ICD-10 transition. In addition, coders and CDI specialists are included in the loop concurrently to fine-tune their workflow, save time, and deliver more accurate results. The result is more accurate documentation, leading to better revenue-cycle operations and ultimately, better care.
In most HIT environments, the speed and accuracy of coding rely on the narrative that the physician details. However, with the increased specificity of ICD-10, HIT needs to meet the challenge of capturing this specificity. In order to do so, NLU can be used to determine missing pieces in the patient narrative. Currently, NLU is commonly used at the back-end of the coding process. However, by moving NLU to the front-end, the re-defined workflow will ultimately save facilities valuable time and resources. To ensure that the physicians are not prompted for unnecessary details, the NLU not only processes the current context, but is also aware of what exists in the patient chart. Therefore, it will only prompt physicians, when the detail needed is not already specified by some other member of the care giver team. With this change, physicians can receive relevant real-time prompts for missing details as they are entering the patient data. With NLU in the back-end, days after he has seen the patient, a coder will inform a physician that details are missing. By moving NLU to the front-end, physicians can get this feedback immediately, leading to better clinical documentation, as there are fewer inaccuracies and deficiencies. In addition, coders and CDI specialists are included in the loop concurrently to fine-tune their workflow, save time and deliver more accurate results. Ultimately, accurate documentation leads to better revenue-cycle operations and finally, better care.
Fundamentally, the complexity of the transition to ICD-10 has to do with the increase of the number and specificity of codes. There are 69,000 diagnostic codes in ICD-10 compared to 14,000 in ICD-9. The American Association of Professional Coders predicts a 10-20 percent increase in documentation activities. Ultimately, reimbursement challenges related to ICD-10 are fundamentally clinical documentation challenges. In HIT environments, the speed and accuracy of back-end functions like coding and billing are often predicated on the quality of patient narratives captured in the front-end by physicians. NLU technology can be used to uncover critical patient information, which can lead to more accurate coding. Furthermore, many doctors are unaware of what information is necessary downstream for proper coding and billing, but by moving NLU to front-end processes, doctors are given real-time feedback as documentation is created. In this new workflow system, physicians are no longer just supplying input, but are actively given direct and immediate feedback, which reduces inaccuracies and deficiencies. This new approach represents the future of CDI, allowing HIM managers to protect productivity and cost effective care from the coming tide of ICD-10.