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Tutorial for CDISC Builder| Getting Started | validate SDTM

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Tutorial for CDISC Builder| Getting Started | validate SDTM

CDISC
Consortium of Data Interchange Standards Committee (CDISC) is primarily concerned withdeveloping standards that aid in the exchange of information between companies in the BioPharmaecosystems.

These include the following models:
• Operational Data Model (ODM) —operational support of data collection
• Study Data Tabulation Model (SDTM) —data tabulation data sets
• Case Report Tabulation Data Definition Specification (CRTDDS – aka define.xml)
• Laboratory Data Model (Lab)• Standard for Exchange of Non-clinical Data (SEND)
• BRIDG—Protocol Representation• Analysis Data Model (ADaM) —analysis data structures
• And others… (For example, LAB, SEND)Taken together, these standards and guidelines represent challenges of supporting the clinical researchprocess.

The importance of data standards Data standards are a critical component in the quest to improve global public health. Inefficiencies in the collection, processing and analysis of patient and health-related information drive up the cost of research and development for life sciences companies as well as negatively impact the cost and quality of healthcare delivery for patients and consumers.

SAS software support for CDISC standards In addition to helping define CDISC standards, SAS is making certain that our products and solutions support the implementation of CDISC data standards. SAS®9 includes a component called PROC CDISC that enables organizations running SAS programs to work with CDISC structured data. PROC CDISC supports bi-directional conversion of data content contained in a CDISC ODM XML document to and from SAS-accessible data sources. The current version of PROC CDISC also supports content validation of SAS-accessible data sources to the CDISC SDTM data domain definitions. See http://www.cdisc.org/ for details on individual format descriptions.

CDISC standards such as SDTM, ODM, LAB and ADaM can be effectively implemented in solutions like SAS Drug Development and SAS DI Studio, and we’re currently exploring additional ways that these standard processes and data structures can be utilized within our software.

The SAS XML Libname Engine has been enhanced in SAS 9.1.3 to natively read and write CDISC ODM file content. Using the SAS XML Libname Engine, any data content accessible to SAS may be converted to a CDISC ODM XML document, or conversely, any content in a CDISC ODM XML document may be converted to a SAS dataset or other SAS-accessible data source.
SAS CDISC implementation services In addition to providing CDISC support within our software, SAS consultants are ready to help your organization implement CDISC standards to drive efficiencies in your clinical development processes.

Glossary
AdaM: Analysis Dataset Model
CDISC: Clinical Data Interchange Standards Consortium
CRT-DDS: Case Report Tabulation Data Definition Specification
LAB: Laboratory Data Model
ODM: Operational Data Model
SDS: Submission Data Standards
SDTM: Study Data Tabulation Model
XML: eXtensible Markup Language

to learn more about CDISC: http://www.lexjansen.com/pharmasug/2003/fdacompliance/fda055.pdf

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Cancer Treatement & Genome Analysis:Reducing Cost from $1 Billion to $1,000 & Quick

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Cancer Treatement & Genome Analysis:Reducing Cost from $1 Billion to $1,000 & Quick

Problem:

Currently it takes two days to find differences in genome data between cancer patients and healthy people resulting in:

  • Poor decision making for hospitals that conduct cancer detection from base on DNA sequence matching
  • Delays in new drug discovery and higher associated costs due to lack of insights in patient data

 

Solution:

By using SAP HANA as the mission-critical and reliable genome data platform it becomes possible to deliver advanced medical treatment to many more patients.

 

MKI offers cloud-based genome analytic services and anticipates that with SAP HANA what traditionally took two days to process can be performed in 20 minutes.  Their Genome Analysis process has three steps:

  1. Case analysis:  comprises of Fragment Extraction, High Speed Entry, and Genome DNA extraction.  First, all cases are collected and the data is preprocessed using Hadoop (fragment extraction).  After that, HANA is used to do fast data analysis to find the patterns in the genome fragments and find the relationship between genome and the case.
  2. Data Consumption: With the genome fragment library and the relationship to the cases in place a doctor can collect a patient’s genome and send it to the system to compare the genome fragment.  Based on the knowledge library, the doctor can recommend most appropriate treatment for the patient.
  3. Case study: The new clinic case will be sent to the researcher to do further study which can improve the correctness of the knowledge library.

 

Benefits:

Successfully overcoming challenges of Big Data in the bioscience sphere has far-reaching ramifications on drug discovery as well as and on individual, detailed medical practices in the medical front such as:

  • For hospitals: Real-time DNA sequence data analysis makes it faster and easier to identify the root cause.
  • Patient care based on genome analysis results can actually happen in one doctor visit Vs. waiting for several days or multiple follow-up visits
  • For Pharmaceutical companies: provide required drugs in time and help identify “driver mutation” for new drug target


Source:https://www.youtube.com/v/U6dA41_ulxo?autoplay=1&rel=0


Source:https://www.youtube.com/v/YfKq6oohUFM?autoplay=1&rel=0

 

 

Resources:

created by Rukhshaan Omar

 

 

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Snow Owl™ is a free SNOMED CT browser. TUTORIAL

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Snow Owl™ is a free SNOMED CT browser. TUTORIAL

Snow Owl™ is a free SNOMED CT browser.

Key features:

Browse and search SNOMED CT quickly and easily
Display and edit SNOMED CT concepts
Use SNOMED CT reference sets to create a subset of concepts
Map existing clinical terms to SNOMED CT
Easy installation, just download, unzip, and run.
Commercial versions of Snow Owl provide many additional features, including:

Collaborative authoring
Customizing the concept model to simplify concept and reference set member authoring
Publishing a release
Advanced ontology engineering that supports emerging pharmacy models
If you’d like to learn more, please have a look at our Getting Started guide and watch the video tutorials.

If you have any questions, ask us on our Facebook page or drop us a note at [email protected]. Have fun!

‘

pLAYLIST: http://www.youtube.com/playlist?list=PLRV87N4oJ5mFHG0JChM4JPdHGW6iWpBJN

dOWNLOAD SNOW OWL:
http://www.b2international.com/portal/snow-owl

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SNOMED-CT to ICD9 Mapping Files (2009)

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SNOMED-CT to ICD9 Mapping Files (2009)

overview on how to leverage the ICD9 cross map files in the SNOMED-CT optional download. Grab a sandwich, MS Access and curl up by the monitor and see how this great resource from the NLM can save you some time and effort mapping SNOMED-CT terms to ICD9.

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SNOMED-CT Essentials and Core Subset Overview (2009)

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SNOMED-CT Essentials and Core Subset Overview (2009)

UNDERSTANDING SNOMED CT

This video provides and overview of the basic structure of SNOMED-CT as well as the Core problem subset.

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Snomed CT | Video Tutorial | BASICS Part 2

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Snomed CT | Video Tutorial | BASICS Part 2

http://www.youtube.com/watch?v=cfP2MWbhECw&list=PL842440B7867442B7

http://www.youtube.com/watch?v=uGdqiSne6c0

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Snomed CT | Video Tutorial | Over View Part 1

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Snomed CT | Video Tutorial | Over View Part 1

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Snomed CT ScreenCast | Tutorial

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Snomed CT ScreenCast | Tutorial

Unified Medical Language System (UMLS) is a comprehensive list of biomedical terms for developing computer systems capable of understanding the specialized vocabulary used in biomedicine and health care.

 

The Unified Medical Language System  was developed by the National Library of Medicine (NLM). NLM produces and distributes the UMLS Knowledge Source databases and associated software tools for use by system developers in building or enhancing electronic information systems that create, process, retrieve, integrate, and/or aggregate biomedical and health data and informatics research. All UMLS Knowledge Sources and associated software tools are free of charge to U.S. and international users.

The UMLS consists of these major components:

Metathesaurus: This serves as the core database for the UMLS.  It is the raw collections of concepts and terms from various controlled vocabularies and their relationships. The Metathesaurus has a license agreement because it includes vocabulary content produced by different copyright holders as well as content produced by NLM.

Semantic Network: These are the overall categories that the information from the Metathesaurus is divided into, as a method of organization.

Specialist Lexicon: This is a database of lexicographic information for use in natural language processing.  This database holds the criteria for the categorization of the concepts in the Metathesaurus.  The Specialist Lexicons define the categories of the Semantic Network, which is the organizer for the individual terms and concepts in the Metathesarus.

In addition to access to SNOMED CT  within the UMLS Metathesaurus, UMLS licensees also have free access to SNOMED CT in its native file formats, to the documentation of these files and to a set of subsets and mapping files.  UMLS licensees have broader rights to create and distribute SNOMED CT extensions and derivative works under the uniform international IHTSDO Affiliate License that is now part of the UMLS License. The license covers all types of use in all countries. Fees apply to some types of distribution or use in countries that are not yet Members of the International Health Terminology Standards Development Organization (IHTSDO).

 

http://www.screencast.com/t/67SaMvNZNL

 

UMLS Step-by-Step

Extract SNOMED CT from the UMLS

Source :http://searchhealthit.techtarget.com/

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SNOMED Clinical Terms® (SNOMED CT®) | Sign up to Practice

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SNOMED Clinical Terms® (SNOMED CT®) | Sign up to Practice

Unified Medical Language System® (UMLS®)

SNOMED CT (Systematized Nomenclature of Medicine–Clinical Terms) is a comprehensive clinical terminology, originally created by the College of American Pathologists (CAP) and, as of April 2007, owned, maintained, and distributed by the International Health Terminology Standards Development Organisation (IHTSDO), a not-for-profit association in Denmark. The CAP continues to support SNOMED CT operations under contract to the IHTSDO and provides SNOMED-related products and services as a licensee of the terminology.

The NLM is the U.S. Member of the IHTSDO and, as such, distributes SNOMED CT at no cost in accordance with the Member rights and responsibilities outlined in the IHTSDO’s Articles. The IHTSDO’s uniform international license terms for SNOMED CT will replace the U.S.-wide license terms NLM negotiated with the CAP in 2003, giving U.S. users broader rights to distribute derivative products internationally. The new license terms have been incorporated into the License for Use of the UMLS Metathesaurus.

Licensees of the UMLS Metathesaurus have access to SNOMED CT (both English and Spanish versions) in multiple formats – as part of the UMLS Metathesaurus, where it is linked to many other biomedical terminologies and natural language processing tools. Additionally UMLS licensees will now have free access to SNOMED CT in its native file formats downloaded directly from the UTS. The IHTSDO license terms for SNOMED CT cover use and distribution worldwide, but fees may be applicable outside IHTSDO Member countries. A list of current member countries and information on becoming a member country is available on the IHTSDO website.

SNOMED CT is one of a suite of designated standards for use in U.S. Federal Government systems for the electronic exchange of clinical health information and is also a required standard in interoperability specifications of the U.S. Healthcare Information Technology Standards Panel. SNOMED CT is also being implemented internationally as a standard within other IHTSDO Member countries.

umls_tree_sm

The UMLS Terminology Services (UTS) allows you to:

  • Request a UMLS Metathesaurus License and create a UTS account
  • Search and display content from UTS Applications including:
    • Metathesaurus Browser
    • Semantic Network Browser
    • SNOMED CT Browser
  • Download data files including:
    • UMLS Knowledge Sources
    • RxNorm weekly and monthly updates
    • SNOMED CT
    • CORE Problem List and Route of Administration Subsets of SNOMED CT
  • Query data remotely via Web Services (see API Documentation)
  • Complete UMLS Annual Report and SNOMED CT® Affiliate Reports

UMLS Terminology Services (UTS) provide both web interfaces as well as Web Services to search and retrieve UMLS data.

We welcome you to contact us with your comments and suggestions to improve the UTS.

Learn more and Get licence from NIH

signup and get the access to practice

https://uts.nlm.nih.gov//home.html

 

USER Guide how to use

umls_tree_sm

 

 

Read more …Documentation ..to learn how to use the Snomed CT

  • SNOMED CT Documentation

 

 

For more information users should contact NLM Customer service at [email protected]

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Panel Backs Insomnia Drug; GSK, U.S. Partner on Antibiotics

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Despite Concerns, Panel Backs Insomnia Drug
A majority of medical experts on a U.S. Food and Drug Administration panel said that an experimental insomnia drug from Merck & Co. Inc. appears safe and effective, in spite of evidence from company trials that the pill can cause daytime sleepiness and difficulty driving.

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A Potential Treatment for Hypoactive Sexual Desire Disorder
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J&J Forecasts 10 NDAs by 2017
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Glaxo, U.S. Partnering on Antibiotics
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Moody’s Reviewing Hospira Debt Rating
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Twitter Adds Two-Factor Security | HP’s Whitman: Rebuild Plan Working

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Between The Lines Columnist HP CEO Whitman Keeps Calm, Carries On
By Doug Henschen
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Samsung’s Galaxy S 4 is its fastest-shipping smartphone, the company says. HTC’s One also moving briskly.

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In the battle for tech talent, small colleges and universities have a lot to offer Gen Xers and Millennials.

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Mostashari – Beacons ‘taught us’

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Mostashari: Beacons ‘taught us’
The Beacon Communities proved that organizations can advocate changes to how healthcare is paid for by working with payers and providers, while improving quality and safety at the same time. "These were the pillars of the Beacon Community activities, and they taught us," National Coordinator for Health IT Farzad Mostashari, MD, said. "They showed what we needed to do."

9 ‘Cs,’ part 2: The ‘back-end’
Much of healthcare reform involves changing the relationship between providers and patients. But for providers, efforts to deliver more accountable care necessarily involves changing the way they manage their practices and keep abreast of near-constant developments across healthcare.

ISU hands over $400K for HIPAA violation
Idaho State University will pay $400,000 to the U.S. Department of Health Human Services to settle alleged violations of the HIPAA Security Rule. The settlement comes after ISU’s Pocatello Family Medicine Clinic disabled server firewall protections for a period of at least 10 months, resulting in the breach of electronic protected health information for some 17,500 patients.

Intermountain measures total radiation
Intermountain Heathcare has launched a program that measures cumulative radiation doses patients receive over their lifetime for medical treatment. Intermountain hospitals and clinics are first in the country to compile the cumulative radiation patients receive from about 220,000 higher-dose procedures and imaging exams each year, starting with exams performed in the last quarter of 2012.

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