By a News Reporter-Staff News Editor at Information Technology Newsweekly -- A new study on Medical Records is now available. According to news originating from Stanford, California, by VerticalNews correspondents, research stated, "Mental illness is the leading cause of disability in the USA, but boundaries between different mental illnesses are notoriously difficult to define. Electronic medical records (EMRs) have recently emerged as a powerful new source of information for defining the phenotypic signatures of specific diseases."
Our news journalists obtained a quote from the research from Stanford University, "We investigated how EMR-based text mining and statistical analysis could elucidate the phenotypic boundaries of three important neuropsychiatric illnesses-autism, bipolar disorder, and schizophrenia. We analyzed the medical records of over 7000 patients at two facilities using an automated text-processing pipeline to annotate the clinical notes with Unified Medical Language System codes and then searching for enriched codes, and associations among codes, that were representative of the three disorders. We used dimensionality-reduction techniques on individual patient records to understand individual-level phenotypic variation within each disorder, as well as the degree of overlap among disorders. We demonstrate that automated EMR mining can be used to extract relevant drugs and phenotypes associated with neuropsychiatric disorders and characteristic patterns of associations among them. Patient-level analyses suggest a clear separation between autism and the other disorders, while revealing significant overlap between schizophrenia and bipolar disorder. They also enable localization of individual patients within the phenotypic 'landscape' of each disorder."
According to the news editors, the research concluded: "Because EMRs reflect the realities of patient care rather than idealized conceptualizations of disease states, we argue that automated EMR mining can help define the boundaries between different mental illnesses, facilitate cohort building for clinical and genomic studies, and reveal how clear expert-defined disease boundaries are in practice."
For more information on this research see: Identifying phenotypic signatures of neuropsychiatric disorders from electronic medical records. Journal of the American Medical Informatics Association, 2013;20(e2):e297-305.
The news correspondents report that additional information may be obtained from S. Lyalina, Dept. of Bioengineering, Stanford University, Stanford, California, United States. Additional authors for this research include B. Percha, P. LePendu, S.V. Iyer, R.B. Altman and N.H Shah.
Keywords for this news article include: Stanford, California, United States, Records as Topic, North and Central America, Electronic Medical Records.
Our reports deliver fact-based news of research and discoveries from around the world. Copyright 2014, NewsRx LLC