AI Case Study
Amazon announces its Comprehend Medical platform to analyse unstructured medical texts
Amazon has announced a machine learning service for analysing and extracting information from different unstructured medical records and text. Comprehend Medical is accessible for developers through AWS, and is partnering with healthcare research centres to assist with things like clinical trial patient matching.
Healthcare Providers And Services
" Amazon Comprehend Medical, a new HIPAA-eligible machine learning service that allows developers to process unstructured medical text and identify information such as patient diagnosis, treatments, dosages, symptoms and signs, and more. Comprehend Medical helps health care providers, insurers, researchers, and clinical trial investigators as well as health care IT, biotech, and pharmaceutical companies to improve clinical decision support, streamline revenue cycle and clinical trials management, and better address data privacy and protected health information (PHI) requirements.
Amazon Comprehend Medical allows developers to identify the key common types of medical information automatically, with high accuracy, and without the need for large numbers of custom rules. Comprehend Medical can identify medical conditions, anatomic terms, medications, details of medical tests, treatments and procedures. Ultimately, this richness of information may be able to one day help consumers with managing their own health, including medication management, proactively scheduling care visits, or empowering them to make informed decisions about their health and eligibility.
There are no servers to provision or manage – developers only need to provide unstructured medical text to Comprehend Medical. The service will “read” the text and then identify and return the medical information contained within it. Comprehend medical will also highlight protected health information (PHI). There are no models to train and no ML experience is required. And, no data processed by the service is stored or used for training. Through the Comprehend Medical API, these new capabilities can be integrated with existing services and health systems easily. The service is also covered under AWS’s HIPAA eligibility and BAA.
Unlocking this information from medical language makes a variety of common medical use cases easier and cost-effective, including: clinical decision support (e.g., getting a historical snapshot of a patient’s medical history), revenue cycle management (e.g., simplifying the time-intensive manual process of data entry), clinical trial management (e.g., by identifying and recruiting patients with certain attributes into clinical trials), building population health platforms, and helping address (PHI) requirements (e.g., for privacy and security assurance.)"
While the service has just been officially announced, the company said it's already partnered with some healthcare providers: "We are working closely with Seattle’s own Fred Hutchinson Cancer Research Center – known as Fred Hutch to Seattleites – to support their goals to eradicate cancer in the future. Comprehend Medical is helping to identify patients for clinical trials who may benefit from specific cancer therapies. Fred Hutch was able to evaluate millions of clinical notes to extract and index medical conditions, medications, and choice of cancer therapeutic options, reducing the time to process each document from hours, to seconds."
"The majority of health and patient data is stored today as unstructured medical text, such as medical notes, prescriptions, audio interview transcripts, and pathology and radiology reports. Identifying this information today is a manual and time consuming process, which either requires data entry by high skilled medical experts, or teams of developers writing custom code and rules to try and extract the information automatically. In both cases this undifferentiated heavy lifting takes material resources away from efforts to improve patient outcomes through technology."
Unstructured electronic medical records