Smart Content for Clinical Practice: EMMeT and ClinicalKey
NFAIS Annual Conference 2013
February 25, 2013
Helen Parr Moran
Vice President, Smart Content
Elsevier Operations, CEC h.moran@elsevier.com
Elsevier is the largest Science, Technical and Medical (STM) Publisher in the world. In the area of Health Sciences, Elsevier publishes leading brands including The Lancet , Braunwald’s Heart Disease , Gray’s
Anatomy , as well as leading online clinical support tools and products including ClinicalKey, Mosby’s Nursing Consult and Gold Standard Drug
Database.
The Content Enrichment Center (CEC) in Elsevier Operations has more than 25 years of experience in creating and maintaining terminologies for use in manual and automated Abstracting and Indexing (A&I). Current taxonomies include EMTREE, Genetree, Geotree, and EMMeT and support products in a wide range of domains, such as life sciences, medicine, chemistry, pharmacology, and engineering.
Copyright © 2013 Elsevier, Inc. | All Rights Reserved
Copyright © 2013 Elsevier, Inc. | All Rights Reserved
The Challenge: Getting doctors the right information to make the best decisions and provide the best clinical care
The Physician’s
Dilemma
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No current offering delivers on all three components doctors need in a medical information product
ClinicalKey Complements Physician Workflows
Patient Care Management Workflows
1
Diagnosis
Create Care Plan
Medical Treatment
Treatment
Surgical Treatment
Procedures
After-Treatment Care Plan
Patient Education & Compliance
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Collateral Workflows
2
Keeping Current
• Conferences/ society meetings
• Reading current literature
3
Sharing
Information
• Patient specific information
• Case presentation
(within dept)
• Presentation to other bodies
(eg, treatment committees, drug committees, etc.)
• External presentations
(grand rounds, association presentations, etc)
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Taxonomy-Powered Content = Smart Content
Content with applied taxonomy
Content with structured XML
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Copyright 2011 Outsell Gilbane Services, Inc.
http://www.outsellinc.com
http://gilbane.com/xml/2009/11/what-is-smart-content.html#ixzz0hnuRhaBc
Role of Smart Content
Smart Content is Infrastructure
Product Development & Enhancement
• More accurate search results
• Faceted navigation
• Improved content discoverability
Content Analytics
• Greater insights into what we publish
• Identification of co-occurring terms
• Link to related external content & data
Personalization
• Individual content recommendations
• Targeted individual marketing
• Contextual advertising
Editorial Productivity
• Flexible product types – new collections, image banks, etc.
• Increased speed to market
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ClinicalKey Workflow
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Introducing EMMeT (Elsevier Merged Medical Taxonomy)
Parent Terms
• Breast Disorders
• Cancer of the Thorax
• Mammary Neoplasms
• More….
2
Breast Lump, Nipple Retraction, …..
Medical Name
Malignant Neoplasm of the Breast
Consumer Friendly Name
Breast Cancer
Synonyms
Malignant Tumor of Breast
Malignant Breast Neoplasm
Breast Ca
Codes
ICD9 – 174.9
MeSH – D001943
SNOMED-CT – 190121004
Semantic Type/Group
Neoplastic Process/Disease
1
Symptoms
Diagnostic
Procedures
Treatment
Procedures
4
Medications
Mammography, Breast Biopsy, …..
Chemotherapy, Mastectomy, ….
Tamoxifen, Doxorubicin, …..
Risk Factors Family History, Genetics, Predisposition, ….
Children Terms
• Breast Sarcoma
•
Familial Breast Cancer
• Malignant lymphoma of the Breast
• Malignant Neoplasm of the breast outer
3 quadrant
• More…
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Prevention
Complications
Screening, Preemptive Mastectomy, ….
Metastatic Cancer, ….
Automated Indexing: Weighted Tags for Better Search
Article-level SMART Content tags help confirm relevance and provide a topical overview about a piece of content.
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Paragraph-level SMART Content tags uncover highly-relevant information not necessarily evident from the title or abstract alone.
Testing Quality: Multipronged QA
1.
Technical Test Set
• Validate the field selection and delivery format
2.
Representative Gold Test
• Establish recall, precision, and harmonic mean versus a manually tagged set of content
3.
Query Set
• Compare product results with expected results from established search queries
4.
Search Logs
• Analyze search logs for candidate terms and noise
5.
Linguistic Intelligence (NLP) Use Cases
• Test language parsing by rules engine using test cases (e.g., hepatitis B/C)
1.
2.
3.
4.
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Copyright © 2013 Elsevier, Inc. | All Rights Reserved
EMMeT Powered Auto-Suggest
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Speed to Answer: Content Filters & Previews
Workflow: Presentation Maker, Reading List & Saved Searches
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Non-invasive cardiologist wants the latest information on the use of biomarker guided therapy in treating congestive heart failure.
He enters search term:
• BNP guided therapy in CHF
BNP guided therapy for CHF Search
TM
• 1 relevant result, last updated in 2009
• 310,000 results—mostly news summaries
• Requires Google Scholar to produce a sublist of journal articles
• 10 results in reverse chronological order, burying several key papers
• 2nd result is an unwanted editorial comment
• Result set misses several key publications due to lack of term expansion and acronym confusion
*Based on an actual case study. Search conducted in March 2011.
Google is a trademark of Google Inc.
• 128 results
• Results from various 12 content types appear in rank order based on their currency and clinical impact
• 1st four results are journals citing the most relevant and current studies
• Highly relevant and current content from various information sources:
• Clinical Trials
• Books
• First Consult
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BETA
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Copyright © 2012 Elsevier, Inc. | All Rights Reserved
Copyright © 2013 Elsevier, Inc. | All Rights Reserved
Helen Moran
Vice President, Smart Content
Elsevier Operations, CEC h.moran@elsevier.com