Human vs. Machine: A Comparative Analysis of Medical Transcription Accuracy and Cost-efficiency

Medical Transcription Accuracy

Man versus machine seems to be a never-ending topic of discussion. On the one hand, human use the brain’s computing power, memory, and ability to think. On the other hand, machines rely on past data to process much more information at a higher speed than individuals. In the context of medical transcription, ‘manual’ involves a healthcare professional listening to the entire audio or video recording and typing it out. In contrast, automatic transcription uses artificial intelligence (AI) to convert speech to text. Although voice recognition software saves doctors time and is more convenient, accuracy suffers. That’s why physicians depend on medical transcription services to uphold precision in medical record documentation, even fine-tuning AI-generated reports for utmost accuracy. While outsourcing transcription is considered costly and time-consuming, reports generated by humans are superior when it comes to accuracy.

Let’s take a look at the advantages and disadvantage of these approaches to medical transcription.

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Machine transcription

As the name implies, machine transcription relies primarily on software to understand audio and convert it to text. AI transcription is fast and minimizes human effort. Its precision, however, falls short of the 99% accuracy level required for compliance.

Automated transcription is quick, inexpensive, and moderately accurate. It can convert audio to text in about a minute. It is a practical option if you’re require large volume transcription at a reasonable price. However, for medical records, automated transcription is not enough. In a multi-center clinical trial conducted at Harvard Pilgrim, Guisinger observed a voice recognition mistake rate of over 7% and that 15% of ER notes contained one or more major errors, potentially resulting in misunderstandings that could have an impact on patient treatment.

Manual Transcription

Human transcription, to put it simply, involves an individual listening to an audio file converting it into text format. Since cognitive capacity is used during human transcription, the outcomes are up to 99% more accurate than those produced by AI transcription. Machines have a hard time understanding nuances, tone, dialect, or jargon, especially in poorer quality recordings or video files. Additionally, human transcriptionists are accurate at identifying the speaker and can also provide more detailed explanations. Human transcriptionists are proficient in formatting, proper language usage, punctuation, phase correction, and other writing conventions. Medical transcription companies have qualified and trained transcriptionists who have excellent typing skills and proficiency in medical terminology and jargon. They comprehend what the speaker is saying, avoiding misunderstandings. They can deliver clean, precise patient data.

While this method has the advantages of being accurate and reliable, it can also be time-consuming and need significant human effort.

Where Machine Transcription Fails

Using speech recognition’s commands for navigation, editing, and macro insertion can increase speed and productivity. It is quite typical for a physician to want to go back and add to, delete from, or edit something in the patient record. This calls for a lot of mouse clicking or navigation and correction commands, which human medical transcriptionists are accustomed to handling. Words are often misunderstood by speech recognition tools. The software lacks the contextual awareness that a human transcriptionist would have given their experience and understanding of patients, medications, anatomical findings, tests, and other things, often on a level comparable to physicians.

A Combined Effort

With EHR adoption, healthcare professionals often struggle to balance patient care with EHR documentation, contributing to physician burnout. Physicians are required to enter all information into the EHR system during the consultation. Since the average physician can only type 30 words per minute, they prefer to dictate their notes.

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These problems might be resolved by combining medical transcription services with speech recognition generated medical documentation. Physicians can record patient information into a recording device, and then send the encrypted audio files to a medical transcription company. Skilled transcriptionists will proofread the notes and correct any mistakes.

The main advantage of this hybrid approach is that it will enable practitioners to guarantee accurate clinical documentation. This will also enable physicians to focus on their patients and providing better care. Partnering with a human-based medical transcription service is also most cost-effective than hiring in-house transcriptionists, which also involves considerable infrastructural costs.