We have reached the point when one of our major EHR vendors, Cerner, has come to understand that it can no longer rely on its own internal resources for AI and predictive analytics development (see: Cerner builds machine learning platform on Amazon Web Services). AI has become so sophisticated that EHR vendors like Cerner can't hope to compete in the field without support from experts such as those working for AWS. An excerpt from this article is presented below:
In July...[Cerner] named AWS its preferred cloud provider. Under the agreement, Cerner is transitioning its artificial intelligence and machine learning workloads to AWS to develop predictive technology. The new platform, called Cerner Machine Learning Ecosystem, was built using several Amazon services and includes machine learning services Amazon Transcribe and Amazon Translate, among others. With the platform, developers will be able to create chatbots that give patients access to their personal medical records as well as the ability to ask questions about their medication, diagnoses and medical conditions. Cerner is also developing voice-activated documentation tools; the EHR vendor recently achieved its 500th patent with a new voice-assisted technology that supports clinician documentation.
I have blogged extensively about AI technology developments in diagnostic medicine such as predictive analytics (see, for example: Three Examples of Predictive Analytics in Clinical Practice; Diagnostic and Predictive Analytics and Their Possible Link to the Future of the LIS; Diagnostics Versus Therapeutics; The Changing Role of Physicians). On the basis of this new technology, pathology reporting to physicians will change radically in upcoming years. Pathology reports will no longer contain only a listing of test results or surgical pathology diagnoses but also a list of diseases and conditions that patients may develop in the future (see: Predisposition to Disease and Pre-Disease on the Health Continuum; The Challenge of Diagnosing Predisease in Our Healthcare Delivery System; The Diagnosis and Treatment of Pre-Diseases: A Look at the Future). It goes without saying that some patients will have no interest in their future diseases so such reports will certainly be modeled on clinician/patient preferences.
This only rarely happens to me but the following passage from the article above caused me to laugh out loud: Chatbots will allow patients to ask questions about their EHR records. Although I can envision a small number of patients in the future wanting to query their EHR records with a chatbot, such a low level of interest could not not possibly justify the development of such an app by Cerner and AWS. Much more likely as the impetus to develop such a chatbot would be to provide assistance to physician and nurses working with the EHR for extracting critical information from patient records.
But why, you might ask, would the article not cite such a justification for the development of "chatbot EHR query" as a feature highly desired by physicians and nurses? To state this overtly would constitute an admission that the EHR is difficult for medical professionals to use in its current state (see: The Benefits and Challenges of Electronic Health Records). Although not mentioned in the article above, I am also sure that an essential part of the development project turfed by AWS to Cerner is natural language processing (NLP) of the EHR record that will enable a larger portion of the record to be searchable using the aforementioned chatbots (see: AI Allows Computers to "Read" EHR Records and Make Predictions).
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