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Cognitive Computing for Electronic Medical Records

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Healthcare Information Management Systems

Part of the book series: Health Informatics ((HI))

Abstract

The explosive growth of data has led to a situation where the human brain is overloaded with more information than it can process. It is particularly dire in healthcare where critical information may be buried in the mountains of data in the Electronic Medical Record systems (EMR systems) and healthcare workers struggle to make sense of this information to provide the best care for their patients. Cognitive computing, exemplified by Watson, offers the promise of transforming EMR systems from mere data storage to intelligent systems that help physicians in providing improved patient care. When seeing a patient, a physician needs to quickly grasp the summary of the patient’s medical history from the EMR to prepare for the visit and to put the patient’s complaints in context. During the visit, there may be a need to supplement, confirm, and investigate the information that the patient provides with information from the EMR. These information needs can be fulfilled by a cognitive system using advanced analytics on the patient record data. Some of the ways this can happen are a problem-oriented summary of a patient record, precisely answering natural language questions about the patient record content, automatically identifying urgent abnormalities, and by providing precise causes for such abnormalities. In this cognitive computing view, an EMR is an active entity that leverages the vast knowledge of the medical sciences, drug information, and medical ontologies in the context of the patient medical records to meet the information needs of the healthcare provider.

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Notes

  1. 1.

    Computer stored and managed patient data is referred to by multiple names, such as, EHR and EMR, often with little or no difference between the terms. To avoid possible confusion, we consistently use the term EMR to refer to a patient medical record and EMRs as its plural. Furthermore, we use the term EMR system(s) to refer to the software and hardware system that stores and provides access to the contents of EMRs.

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Acknowledgements

We thank the physicians and IT staff at Cleveland Clinic who guided definition of the requirements for the functionality discussed here and provided de-identified EMRs under an IRB protocol for the studies. Watson EMRA is a next higher level function built on the medical-domain adapted Jeopardy! Watson. All three, the Jeopardy! Watson, Medical Watson, and Watson EMRA, are the results of an extraordinary team of research, engineering, and support staff at IBM. We gratefully acknowledge their work and contributions which are discussed here.

Author information

Authors and Affiliations

  1. IBM T.J. Watson Research Center, Yorktown Heights, NY, USA

    Murthy V. Devarakonda PhD (IBM) (Research Staff Member and Manager)

  2. Education Institute and Medicine Institute, Cleveland Clinic, Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland, OH, USA

    Neil Mehta MBBS, MS

Authors
  1. Murthy V. Devarakonda PhD (IBM)
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  2. Neil Mehta MBBS, MS
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Corresponding author

Correspondence to Murthy V. Devarakonda PhD (IBM) .

Editor information

Editors and Affiliations

  1. Gentiva Health Services, Atlanta, Georgia, USA

    Charlotte A. Weaver

  2. Healthcare Informatics, IBM Research, Baltimore, Maryland, USA

    Marion J. Ball

  3. Division of Health Sciences Informatics, The Johns Hopkins University, Baltimore, Maryland, USA

    George R. Kim

  4. Duquesne University, Pittsburgh, Pennsylvania, USA

    Joan M. Kiel

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© 2016 Springer International Publishing Switzerland

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Devarakonda, M.V., Mehta, N. (2016). Cognitive Computing for Electronic Medical Records. In: Weaver, C., Ball, M., Kim, G., Kiel, J. (eds) Healthcare Information Management Systems. Health Informatics. Springer, Cham. https://doi.org/10.1007/978-3-319-20765-0_32

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  • DOI: https://doi.org/10.1007/978-3-319-20765-0_32

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-20764-3

  • Online ISBN: 978-3-319-20765-0

  • eBook Packages: MedicineMedicine (R0)

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