One of the most significant factors in extracting information from EHR record is the use of natural language processing (NLP) which I have referred to in a number of previous notes (see, for example: EMRs and the Data Entry Paradox; Same Concept Not Applicable in the LIS World; Assessing Drugs Using "Real World Evidence" in Addition to Clinical Trials; AI Allows Computers to "Read" EHR Records and Make Predictions). A recent article discussed why one should "care" about Amazon's new medical language processing service (see: Why Should You Care About Amazon's New Medical Language Processing Service). Below is an excerpt from it:
Keeping track of your medical records can be a complex task....One of the significant challenges of handling medical records is that for each patient there is a variety of types of "notes" entered over time by health care professionals. These may include prescriptions, observation and administration of drugs and therapies, test results, x-rays, CT-scans, heart rate measured over months, surgical history, immunization history and family history. So the data type can be anything from a string, or a time-series data to an image or a very high definition video.The second challenge of handling data is accessibility. Although there is a generic set of rules in the US under Health Insurance Portability and Accountability Act (HIPAA) governing access to medical records, that states that the patient and the health-care providers directly involved in delivering care have the right to view the record.
The patient, however, may grant consent for any person or external entity to access the record. Given the complexity of handling and managing medical record, the holy grail of health records is perhaps a global electronic health directory that has both interoperability and liability built into it...Amazon [has] announced a new service called AWS Comprehend Medical...that can potentially impact the whole medical records ecosystem. Although electronic health records (EHR) exist for more than a decade, the majority of historical patient data is still stored today as unstructured medical text, such as medical notes, prescriptions, audio interview transcripts, and printed pathology and radiology reports. Extracting meaningful information from these is still a time-consuming process, and either requires data entry by high skilled medical experts, or teams of developers writing custom code. Comprehend Medical leverages Amazon’s AI technology to build a health record industry-specific solution, that uses natural language processing (NLP) to extract health-related text and data from virtually any medical record.
Here's a key passage from the Amazon Comprehend Medical landing page about its services:
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 Amazon 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.
It's no surprise that Amazon singles out clinical trial management as a suitable use case for the company's new language processing service. For patients enrolled in clinical trials, EHR notes are extremely important. Pharmaceutical companies spend billions on such trials and will not be bothered by the costs involved in using such a service. I will be sure to track the future activities of this new company.
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