Artificial Intelligence and NLP Technology

Artificial Medical Intelligence Announces Automatic Generation of Medical Problem Lists

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Robert Wood Johnson University Hospital Successfully Using EMscribe Problem List Capability with Allscripts SCM

EATONTOWN, N.J.–(BUSINESS WIRE)–Artificial Medical Intelligence (AMI) and Robert Wood Johnson University Hospital (RWJUH) today announced a process that automatically generates medical problem lists from AMI’s EMscribe® Computer Assisted Coding (CAC) data abstraction engine. RWJUH is currently using the EMscribe solution to successfully generate problem lists from its Allscripts SCM EMR system.

A problem list is a vital part of a patient’s medical chart that details the most important medical information. As the health care industry transitions to Electronic Medical Records (EMRs), the problem list is recognized as one of the core meaningful use criteria that require standardization in content and structure in order to be compatible for health information exchange (HIE).

Currently health care organizations either manually enter patient problem list information or may not have a system in place at all. AMI’s EMscribe addresses this issue by utilizing its innovative Natural Language Processing (NLP) technology to read patient health records for appropriate medical terminology, generates a problem list based on this information and automatically populates a healthcare organization’s EMR system. It allows clinicians to capture the true clinical intent that leverages their existing medical documentation through immediate access to the identified patient problems.

RWJUH is unique in applying EMscribe’s data abstraction engine in this capacity and is realizing the benefits of enhanced clinical workflow while aiding in the achievement of meaningful use compliance. Clinical documentation comprising the patient record from multiple sources is analyzed automatically by EMscribe “behind the scenes.” RWJUH designed and developed a custom workspace in the Allscripts SCM EMR where clinicians can selectively “drag and drop” suggested diagnoses into the patient’s active, chronic, or resolved medical problem list.

“Utilizing EMscribe’s NLP to generate medical problem lists improves our hospital’s efficiency and clinical care, and most importantly, helps manage populations of patients while they are hospitalized,” said Joshua Bershad, MD, senior vice president and chief medical officer at RWJUH.

Jordan D. Ruch, administrative director of Clinical Information Systems at RWJUH added, “In addition to supporting Meaningful Use, it allows our providers to easily manage the problem list in real-time with automated suggestions from the source medical record. With a discrete, up-to-date problem list, we are able to build robust patient-specific clinical decision support.”

According to Stuart Covit, COO AMI, “The beauty of EMscribe’s CAC platform is that it is driven by Natural Language Processing, the most efficient medical record information abstraction engine available. This means that it can go well beyond the scope of medial coding and help provide solutions like generating problem lists by simply abstracting data from documented patient charts. The EMscribe platform is innovative technology that helps healthcare organizations with customized applications to keep pace with the rapidly changing healthcare environment.”

AMI’s EMscribe with problem list capabilities is available immediately. Interested parties can contact the company here.