Extract information from unstructured medical text accurately and quickly No machine learning experience required
Comprehend Medical is a natural language processing service that makes it easy to use machine learning to extract relevant medical information from unstructured text. Using Comprehend Medical, you can quickly and accurately gather information, such as medical condition, medication, dosage, strength, and frequency from a variety of sources like doctors’ notes, clinical trial reports, and patient health records.
One of the important ways to improve patient care and accelerate clinical research is by understanding and analyzing the insights and relationships that are “trapped” in free-form medical text, including hospital admission notes and a patient’s medical history.
Today this is achieved by writing and maintaining a set of customized rules for natural language processing software, which are complicated to build, time-consuming to maintain, and fragile. A change to a single classification code name, for example, can impact dozens of hard-coded rules and failing to update a single one of them can result in missed or incorrect data. Machine learning can change all that with models that can reliably understand the medical information in unstructured text, identify meaningful relationships, and improve over-time.
Comprehend Medical uses advanced machine learning models to accurately and quickly identify medical information, such as medical conditions and medications, and determines their relationship to each other, for instance, medicine dosage and strength. You access Comprehend Medical through a simple API call, no machine learning expertise is required, no complicated rules to write, and no models to train.
You can use the extracted medical information and their relationships to build applications for use cases like clinical decision support, revenue cycle management (medical coding), and clinical trial management. Because Comprehend Medical is HIPAA eligible and can quickly identify protected health information (PHI), such as name, age, and medical record number, you can also use it to create applications that securely process, maintain, and transmit PHI. You pay only for what you use, and there are no minimum fees or upfront commitments.
Perform medical cohort analysis
In oncology, it is critical that the right selection criteria are quickly discovered to recruit patients for clinical trials. Comprehend Medical understands and identifies complex medical information found in unstructured text to help make indexing and searching easier. You can use these insights to identify recruit patients to the appropriate clinical trial in a fraction of the time and cost from manual selection processes.
Support clinical decisions
Comprehend Medical extracts medical information from patient data stored in storage and returns structured results that you can integrate into a healthcare dashboard a care support team can access. For example, a developer can build an early warning system to help identify individuals at risk of multiple sclerosis by extracting diagnosis, sign, and symptoms from more than 100,000 clinical notes using Comprehend Medical. By providing a “single lens” into the patients’ medical history, clinical teams can make decisions that are more informed.
Improve medical coding in revenue cycle management
For a hospital, the process of finding the right diagnosis in the patient notes that should be mapped to the correct code in the International Classification of Diseases (ICD) can be time-consuming and tedious. It is particularly challenging to extract diagnoses that can be represented in different ways. For example, “atrial fibrillation” is sometimes written as “AF.” Comprehend Medical can accurately identify abbreviations, misspellings, and typos in medical text. This reduces the time a medical coder must spend analyzing unstructured notes, decreases the time burden on clinical staff, and improves efficiency.