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The discriminatory cost of ICD-10-CM transition between clinical specialties: metrics, case study, and mitigating tools.

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TLDR
The complexity of this transition between clinical specialties is substantiated with a thorough quantitative summary per clinical specialty, a case study, and the tools to apply this methodology easily to any clinical practice in the form of a web portal and analytic tables.
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This article is published in Journal of the American Medical Informatics Association.The article was published on 2013-07-01 and is currently open access. It has received 50 citations till now.

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Embolectomy for stroke with emergent large vessel occlusion (ELVO): report of the Standards and Guidelines Committee of the Society of NeuroInterventional Surgery

TL;DR: The purpose of this document is to summarize the results of these trials and synthesize the level of evidence supporting the use of embolectomy in patients with ELVO, to summarized using a scale previously described by the American Heart Association.
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Preparing for the ICD-10-CM Transition: Automated Methods for Translating ICD Codes in Clinical Phenotype Definitions

TL;DR: It appears that for clinically distinct and homogenous conditions, the recall of FBM is sufficient, and different mapping approaches yield different collections of ICD-10-CM codes.
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Clinical Research Informatics and Electronic Health Record Data

TL;DR: Considerations for the use of EHR data provide a starting point for practical applications and a CRI research agenda, which will be facilitated by CRI's key role in the infrastructure of a learning healthcare system.
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Comparing chronic condition rates using ICD-9 and ICD-10 in VA patients FY2014–2016

TL;DR: Many chronic condition rates were consistent from FY14–16, and there did not appear to be widespread undercoding of conditions after ICD-10 transition, and it is unknown whether increased sensitivity or underc coding led to decreases in mental health conditions.
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Using Electronic Health Records To Generate Phenotypes For Research.

TL;DR: Common and emerging electronic phenotyping approaches applied to electronic health records are described, as well as current limitations of both the approaches and the biases associated with these clinically collected data that impact their use in research.
References
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Journal ArticleDOI

The importance of bottlenecks in protein networks: correlation with gene essentiality and expression dynamics.

TL;DR: In this article, the authors define bottlenecks as proteins with a high betweenness centrality (i.e., network nodes that have many "shortest paths" going through them, analogous to major bridges and tunnels on a highway map).
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Assessing Validity of ICD-9-CM and ICD-10 Administrative Data in Recording Clinical Conditions in a Unique Dually Coded Database

TL;DR: The validity of the International Classification of Disease, 10th Version (ICD-10) administrative hospital discharge data was generally similar though validity differed between coding versions for some conditions.

Comparability of cause of death between ICD-9 and ICD-10: preliminary estimates.

TL;DR: Preliminary comparability ratios by cause of death presented in this report indicate the extent of discontinuities in cause-of-death trends from 1998 through 1999 resulting from implementing ICD-10, including Septicemia, Influenza and pneumonia, Alzheimer's disease, and Nephritis, nephrotic syndrome and nephrosis.
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Desiderata for Controlled Medical Vocabularies in the Twenty-First Century

TL;DR: This paper brings together some of the common themes which have been described, including: vocabulary content, concept orientation, concept Orientation, concept permanence, nonsemantic concept identifiers, polyhierarchy, formal definitions, rejection of "not elsewhere classified" terms, multiple granularities, multiple consistent views, context representation, graceful evolution, and recognized redundancy.
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A Dynamic Network Approach for the Study of Human Phenotypes

TL;DR: A new phenotypic database summarizing correlations obtained from the disease history of more than 30 million patients in a Phenotypic Disease Network (PDN) is introduced, offering the potential to enhance the understanding of the origin and evolution of human diseases.
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