Amazon Transcribe Medical
Amazon Transcribe Medical is a machine learning service that makes it easy to quickly create accurate transcriptions from medical consultations between patients and physicians. With Transcribe Medical, the medical and pharmacological terms used in physician dictated notes, practitioner/patient consultations, and tele-medicine are automatically converted from speech to text for use in clinical documentation applications.
Accurate medical transcriptions are expensive, take too much time, or are disruptive to the patient experience. In many hospitals and clinics, physicians will use a recorder to dictate notes that are sent to a third party who manually transcribes the voice file, an expensive and time consuming process that takes multiple days to complete. Others choose to use human scribes, which can be distracting and uncomfortable for patients and clinicians. Some organizations have tried to use existing medical transcription software, but complex medical language can be difficult to transcribe, leading to inefficiency and poor accuracy that can cause serious consequences. Conversations between health care providers and patients provide the foundation of a patient’s diagnosis and treatment plan, and is the start to any clinical documentation workflow. For example, a workflow can include the conversation between a physician and patient, entering the prescription into an electronic health record (EHR) system, and electronically sending the order to the pharmacy. It’s critically important that this information is accurate.
Amazon Transcribe Medical uses machine learning to provide highly accurate automatic speech recognition (ASR) for the medical industry. You can use Transcribe Medical to quickly and efficiently capture physician-patient conversations in text for later analysis using natural language processing or for entry into electronic health record (EHR) systems, because the service is trained to understand the terminology and style of clinical language. With Transcribe Medical, physicians are able to better focus on their patient and provide a more attentive experience instead of interrupting the conversation for note taking.
Transcribe Medical is HIPAA eligible and integrates easily with clinical documentation applications and any device with a microphone. This could include a mobile application that transcribes the entire conversation between physician and patient, or a software application on a computer that captures a dictation from a physician after the patient visit. Then, transcriptions can automatically be sent to a natural language processing service like Amazon Comprehend Medical. Comprehend Medical uses machine learning to extract relevant medical information from transcriptions, such as medical condition, medication, dosage, strength, and frequency. This information can be used for summarizing notes, clinical decision support, revenue cycle management (medical coding), and clinical trial management.
"Extreme accuracy in clinical documentation is critical to workflows and overall caregiver satisfaction. By leveraging Amazon Transcribe Medical's transcription API, Cerner is in initial development of a digital voice scribe that automatically listens to clinician-patient interactions and unobtrusively captures the dialogue in text form. From there, our solution will intelligently translate the concepts for entry into the codified component in the Cerner EHR system."
Solutions Strategist, Cerner Corporation
Using Transcribe Medical, physicians can dictate their notes using a mobile device after the patient interaction. This gives physicians the ability to dictate medical notes quickly, instead of manual note-taking or waiting for third party services, reducing time and cost and improving the patient experience.
Healthcare and life science customers can build transcription applications that capture physician-patient conversations in real time, without disrupting the interaction. Transcripts can be used to gather insights like medication, dosage, strength, and frequency, before final entry into electronic health record (EHR) systems. You can use Comprehend Medical, a natural language processing service for medical text, to extract those insights.
Drug safety monitoring
Pharmaceutical companies can use Transcribe Medical to transcribe patient calls with physicians or physician calls with pharmaceutical companies, accurately capturing names of medicines and key terms that describe health side effects. With this information in text format, pharmaceutical companies can more efficiently analyze and detect drug-related safety issues, for example an unexpected side effect for a new medication.
Transcribe Medical provides accurate real-time speech-to-text that's built for medical language using state of the art machine learning models. This means that a statement like “patient suffered a plantar fibroma” will be captured accurately. This cuts down on the time that physicians have to take and edit notes manually, reducing physician burnout that’s typically caused by tedious hours of medical note taking.
Transcribe Medical supports conversations between multiple people or dictation from a single-speaker. It also provides auto-punctuation so that physicians can speak naturally, instead of explicitly speaking out punctuation marks. The transcription will also automatically include normalized numbers (e.g. 50 beats per minute instead of “fifty”) and capitalization. Because Transcribe Medical captures natural conversations, the physician doesn't have to pause for notes, providing a more attentive and improved patient experience.
Lower medical documentation costs
Because Transcribe Medical reduces reliance on expensive human scribes and doesn’t require licensing fees like other traditional transcription services, it reduces the overall cost of medical documentation. Clinical documentation applications using Transcribe Medical can be deployed at scale across thousands of medical centers, providing affordable, consistent, and accurate note taking for clinical staff and facilities no matter where they're located.