AI-driven Clinical Documentation

How AI can free providers from clerical work

September 10, 2019 | 04.00 PM EDT

Clinical Documentation is an integral part of the healthcare workflow. Generally, doctors have to double up as data entry operators as well in order to capture and update patient data in an Electronic Health Record (EHR) system. It results in a higher workload for the physicians and poorer patient experience. Consequently, they resorted to scribes to assist them in filling out the EMRs. It incurred higher cost and longer turnaround times.
A patient's experience during a doctor visit is one of the key determinants in patient satisfaction. According to a recent study by Annals of Internal Medicine, doctors spent 49% of their workday in data entry on an EMR system and 27% in interacting with patients directly. As a result, healthcare providers are now opting for EMR systems with enabling technology including speech recognition. It helps improve their efficiency and productivity.

Unstructured Data to Structured Data

CascadeMD is an AI-driven documentation workflow system that helps automate data entry for doctors. The transcription engine receives unstructured data from the doctor's dictation notes and transcribes these audio files into transcripts. Furthermore, the AI engine maps the patient's medical information to the respective fields in the EHR with a higher level of accuracy. This reduces the workload of doctors and affords them more time to spend on treating patients.

Data Entry and Insightful Inferences

The most accurate speech recognition software can recognize and transcribe the most complex medical terminologies from audio to text. CascadeMD goes one step ahead and can infer meanings from unstructured sentences from transcription notes. For example, it's inference engine can analyse if a patient is alcoholic or not based on the insights gained from their EMR. If a patient report states that "he drinks a bottle of Vodka every day", then it will infer that the patient is "alcoholic", but "a bottle of beer" would not be construed as being alcoholic.

Human Transcriptionists Vs. Artificial Intelligence (AI)

A highly efficient transcriptionist can transcribe voice recording to text at 65 words per minute (wpm) with 95% to 98% accuracy. On the contrary, a doctor's voice dictation speed averages at 150 wpm. The AI-powered transcription engine converts the audio to text automatically in real-time resulting in shorter Turn-Around Times (TAT). Currently, it requires human intervention in order to deliver greater accuracy.

AI will drive the future of clinical documentation for an advanced healthcare experience. Healthcare providers and organizations will opt for AI-powered Medical Virtual Assistants (MVAs) to record, transcribe, infer and share actionable insights with doctors regarding their patient's health. They will improve the overall patient experience while supporting doctors on their everyday tasks. Ultimately, AI-powered clinical documentation applications such as CascadeMD offers a win-win situation for providers, administrators and patients in the healthcare industry.