Understanding the Differences Between Dictation and Transcription in the Medical Field

Dictation vs. Transcription

With so many medical documentation solutions available for care providers, sometimes it can be hard to remember how each tool approaches the issue of clinical documentation. To understand the scope of what we’re talking about, we must first understand the fundamental differences between dictation and transcription. Dictation is the action of speaking to a person (or device) and transcription is the process of taking that dictated speech, and writing or transcribing it into a text document. More simply, dictation is an action of a speaker and transcription is a process of a writer.

Because the relationship between dictation and transcription is often so interdependent, the pair have been used in tandem throughout history; in the documentation of scientific findings, legal proceedings, judicial reports, historical events, and medical records. However, as technology advances, the interdependence between dictation and transcription has loosened significantly, and their defining lines are less clear. This is especially true in the modern medical field, where both dictation and transcription are used to ease the burden of clinical documentation.

Dictation in the Medical Field

If we remember that dictation is an action, it’s easier to understand how it is used in the medical field. That being said, there are two major ways medical dictation is used to ease documentation: 

Dictation Recording

Medical dictation recording always occurs either in the immediate presence of the patient, or after the visit. Many health professionals and thought leaders argue that the former leads to better patient health outcomes and less burnout, but both methods are still in practice. 

In either case, it’s important to remember that dictating is always a very intentional process. Because dictation is used to record patient health information and not small-talk, it relies on specific vocal prompts and cues from the care provider in order to be logged as intended. For example, after exchanging pleasantries, a provider may ask why the patient has come to see them. After listening to the patient explain their chest pain, the provider would turn to their recording device and dictate: “Patient presents today with pain in his chest and stomach.” When that dictated and recorded sentence reaches a transcriptionist, it will be logged into a patient’s HPI or subjective field. Similarly, that same sentence can be dictated to the recording device after the patient leaves the exam room. While potentially less disruptive, dictating after the visit relies on more extensive recall which has been known to increase the probability of miscare. 

Regardless of how a provider prefers to dictate, this general method is a traditional example of dictation recording in the medical field, and really illustrates how much dictation relies on transcription and vice versa. But as technology advances, this interdependence has loosened significantly. Now, we are beginning to see more robust dictation technology that is capable of transcribing as well.

AI Dictation Software

AI dictation software differs from traditional dictation because it uses speech and voice recognition to actually interpret the words and meaning of what is being said. This means that the software can actually work to complete the transcription as well, eliminating the need for a human medical transcriptionist or lengthy post-session note taking. Additionally, AI dictation software is often capable of integrating with a provider’s electronic health record system, meaning that it can not only listen and interpret a provider’s dictation, but record it into the discrete fields of the EHR if prompted correctly. 

After a patient visit, a care provider sits down and starts dictating the information collected during the encounter, being sure to intentionally prompt the dictation device to each discrete EHR field and data set. If we take the same example of HPI recording used above, the provider might say: “Section one, subjective, History of Present Illness: Patient presents today with pain in his chest and stomach.” 

As always, there’s pros and cons to this method. While many providers prefer this approach to human medical transcriptionists, an equal or greater amount find the technology to be clunky and cumbersome. This is in large part due to the fact that AI dictation software requires a great deal of very intentional dictation. To use these tools effectively, providers must start and stop their notes frequently as they move from field to field, and the tech also requires them to dictate each element of punctuation including commas and periods, etc. Over time, some providers find this technology to be exhausting and end up seeking an alternative method that is less mentally draining.

Transcription in the Medical Field

By now we know that transcription is the process of turning dictated speech into a written document. Traditionally, medical transcription is done by human transcriptionists who work for larger medical transcription companies. These companies, while not subjected to the same federal guidelines as individual providers and health organizations, do often require their employees to complete some level of medical training or industry experience. This vetting process ensures that any transcriptionist assigned to any given dictation recording, has an understanding of the medical terminology and industry language necessary to produce complete medical notes.

Using these outsourced transcriptionists allows providers to focus more intently on the patient during their encounters and exams. Instead of logging information into their notepad or directly into their EHR, they can simply speak to their patient face-to-face, interrupting that conversation only to dictate to their recording device as necessary. Compared to traditional medical scribes, hiring a medical transcriptionist or using a larger medical transcription company can actually be, in some cases, more secure and safe due to a phenomenon known as functional creep. Functional creep refers to the unintentional practice of trusted scribes sometimes engaging in clerical work that is outside the scope of their role, putting the provider at risk of malpractice. With medical transcriptionists, their relationship with a provider is very transactional and regulated, significantly reducing the risk of functional creep.

On the other hand, however, medical transcription does still have a handful of significant downsides. We’ve documented this in depth already, but in short, transcribed documents can have long, unrealistic turnaround times, and the quality of the produced documentation can vary dramatically based on who is completing the transcription. Additionally, the transmission of sensitive information across unsecured channels can pose malpractice risks to care professionals, and for those who dictate after the patient encounter, extensive recall can hurt note and care quality. 

AI Transcription     

At DeepScribe, our all-encompassing medical documentation solution uses a state-of-the-art AI transcription software that converts your natural patient conversation into a high-fidelity transcription. What makes DeepScribe so unique, though, is that it does not rely on any direct prompting or intentional dictation. Our software uses natural language processing to distinguish between small talk and the medically relevant information to produce a transcription that only contains the pertinent patient health information. But that’s not all.

AI Scribe

Unlike medical dictation and transcription tools, DeepScribe’s advanced AI technology is capable of extracting the contents of that transcription and applying that information to the appropriate fields of a provider's EHR. With DeepScribe, all a provider has to do is speak to their patient as they normally would, and our technology extracts the relevant information, produces a HIPPA-compliant SOAP note (modified to your templates and preferences) and then applies that note directly into your EHR.

Learn more about our all-encompassing AI medical scribe.

text

Related stories

Blog

Context Awareness in Ambient AI Clinical Notes: Responding to the Moment of Care

Context awareness in AI medical scribing intelligently uses patient history to create more accurate, efficient clinical notes without redundancy or excessive verbalization.
Blog

Enhancing Multilingual Patient Visits with AI

AI is helping bridge language barriers in healthcare with real-time translation and multilingual support for better patient outcomes and care delivery.
Blog

Ambient AI on the Air: Recent Podcast Highlights

DeepScribe’s leaders discuss ambient AI's impact on clinician well-being and patient care on two top podcasts, exploring real-world applications and future potential.

Realize the full potential of Healthcare AI with DeepScribe

Explore how DeepScribe’s customizable ambient AI platform can help you save time, improve patient care, and maximize revenue.