Snomed Ct® and 3M™ Hdd: the Successful Implementation Strategy
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Technology and Standards for Health Care
Technology and Standards for Health Care Messaging Standards Used for: HL7 Clinical data X12N Financial data, HIPAA mandated transactions DICOM Images NCPDP Prescription from providers to pharmacies IEEE Bedside instruments, medical information bus Terminology Standards LOINC Drugs NLM/FDA/VA collaboration on RxNorm, NDF-RT Billing CPT, ICD-9CM Clinical UMLS, SNOMED and others Table adopted from Stan Huff MD, HIMSS, 2003 Standards and Standards Organizations American Society for Testing and Materials (ASTM) A component of the American National Standards Institute (ANSI) that has a subcommittee (E31) for general healthcare informatics. This E31 Subcommittee on Healthcare Informatics develops standards related to the architecture, content, storage, security, confidentiality, functionality, and communication of information used within healthcare and healthcare decision making, including patient-specific information and knowledge. URL: www.astm.org Current Procedural Terminology (CPT) CPT® Current Procedural Terminology was developed by the American Medical Association in 1966. These codes are used for the billing of medical procedures. Each year, an annual publication is prepared, that makes changes corresponding with significant updates in medical technology and practice. The most recent version of CPT, CPT 2003, contains 8,107 codes and descriptors. URL: http://www.ama-assn.org/ama/pub/category/3113.html Digital Imaging and Communications in Medicine (DICOM) The Digital Imaging and Communications in Medicine (DICOM) Standard was developed for the transmission of images and is used internationally for Picture Archiving and Communication Systems (PACS). This standard was developed by the joint committee of the ACR (the American College of Radiology) and NEMA (the National Electrical Manufacturers Association) to meet the needs of manufacturers and users of medical imaging equipment for interconnection of devices on standard networks. -
Introduction to Health Level Seven (HL7) International Organization & Process Orientation
Introduction to Health Level Seven (HL7) International Organization & Process Orientation January 2018 HL7 Working Group Meeting New Orleans, LA January 2018 Calvin Beebe © 2015 Health Level Seven ® International. All Rights Reserved. HL7 and Health Level Seven are registered trademarks of Health Level Seven International. Reg. U.S. TM Office. Agenda HL7 International ➢ What is it ➢ How is it Organized ➢ Vision and Mission ➢ Organizational Chart ➢ Affiliates ➢ Role in enabling interoperability ➢ What’s in a name? © 2015 Health Level Seven ® International. All Rights Reserved. 2 HL7 and Health Level Seven are registered trademarks of Health Level Seven International. Reg. U.S. TM Office. Agenda How do we work? ➢ Consensus Driven ➢ Work Groups ➢ Technical Steering Committee ➢ Steering Divisions HL7 International Processes ➢ Meetings ➢ Projects ➢ Ballots HL7 Products Appendices © 2015 Health Level Seven ® International. All Rights Reserved. 3 HL7 and Health Level Seven are registered trademarks of Health Level Seven International. Reg. U.S. TM Office. HL7 INTERNATIONAL WHAT IS IT & HOW IT IS ORGANIZED? © 2015 Health Level Seven ® International. All Rights Reserved. 4 HL7 and Health Level Seven are registered trademarks of Health Level Seven International. Reg. U.S. TM Office. What is HL7 International? HL7 International is one of several American National Standards Institute (ANSI) accredited Standards Developing Organizations (SDOs) operating in the healthcare arena. ➢ Most of these SDOs produce standards (sometimes called specifications or protocols) for a particular healthcare domain such as pharmacy, medical devices, imaging or insurance (claims processing) transactions. © 2015 Health Level Seven ® International. All Rights Reserved. 5 HL7 and Health Level Seven are registered trademarks of Health Level Seven International. -
Health Level 7 (HL7) Adapter
Health Level 7 (HL7) Adapter Edifecs SpecBuilder and XEngine Accelerate the Design, Development, Validation and Integration of HL7 Messages Background on HL7 Messages Edifecs HL7 Highlights Healthcare providers are facing a daunting challenge: to provide the best clinical patient care while reducing Supports HL7 versions: 2.1, 2.2, 2.3, costs. Adoption of HL7 message protocols provides 2.3.1, 2.4, 2.x and 3.x (XML based) a valuable resource in overcoming these challenges. HL7 is an ANSI-accredited standards organization that Produces CCD and CDA, including publishes specifications for the electronic exchange of schematron validation administrative, clinical, and financial information among independent healthcareoriented systems. This approach Validates against HL7 message enables provider healthcare organizations to select and specifications and custom rules integrate best-of-breed systems for patient care, clinical lab, etc. However, implementation of HL7 is not plug-n- Creates automatic acknowledgements play because each organization and department has its own specific business needs. These needs translate into Supports full envelope and batching custom requirements that must be properly documented, communicated and applied to the various systems in order Converts to and from HL7 2.x XML to function properly. Edifecs products include HL7 support format to provide an easy way to capture, document and maintain these requirements and ensure that messages comply Exports HL7 message specifications with these requirements. to W3C XML Schema format SB Solution Brief | Health Level 7 (HL7) Adapter 1 Comprehensive HL7 standards support with seamless, Comprehensive Standards Support fast integration The Edifecs HL7 solution offers comprehensive standards support, a powerful editor with compliance checking and easy, seamless integration through a COM, Java API, or standalone server (includes connectors to IBM Websphere MQ, Java messaging server (JMS) or folder). -
Session 100: Beyond Claims: Unlocking the Power of EMR And
Session 100, Beyond Claims: Unlocking the Power of EMR and Real-Time Clinical ADT Data SOA Antitrust Disclaimer SOA Presentation Disclaimer 2019 Health Meeting ANDREW LOEWER, KELVIN WURSTEN, & KATHERINE ZHAO Session 100: Beyond Claims: Unlocking the Power of EMR and Real-Time Clinical ADT Data June 25, 2019 SOCIETY OF ACTUARIES Antitrust Compliance Guidelines Active participation in the Society of Actuaries is an important aspect of membership. While the positive contributions of professional societies and associations are well-recognized and encouraged, association activities are vulnerable to close antitrust scrutiny. By their very nature, associations bring together industry competitors and other market participants. The United States antitrust laws aim to protect consumers by preserving the free economy and prohibiting anti-competitive business practices; they promote competition. There are both state and federal antitrust laws, although state antitrust laws closely follow federal law. The Sherman Act, is the primary U.S. antitrust law pertaining to association activities. The Sherman Act prohibits every contract, combination or conspiracy that places an unreasonable restraint on trade. There are, however, some activities that are illegal under all circumstances, such as price fixing, market allocation and collusive bidding. There is no safe harbor under the antitrust law for professional association activities. Therefore, association meeting participants should refrain from discussing any activity that could potentially be construed as having an anti-competitive effect. Discussions relating to product or service pricing, market allocations, membership restrictions, product standardization or other conditions on trade could arguably be perceived as a restraint on trade and may expose the SOA and its members to antitrust enforcement procedures. -
Using LOINC with SNOMED CT 3 April 2017
Using LOINC with SNOMED CT 3 April 2017 Latest web browsable version: http://snomed.org/loinc SNOMED CT Document Library: http://snomed.org/doc 1. Using LOINC with SNOMED CT . 3 1 Introduction . 4 2 Short Introduction to SNOMED CT . 6 2.1 Features of SNOMED CT . 6 2.2 Benefits of SNOMED CT . 7 3 Short Introduction to LOINC . 9 3.1 Features of LOINC . 9 3.2 Benefits of LOINC . 13 4 Cooperative Work . 15 4.1 Cooperative Work Overview . 15 4.2 Release File Specifications . 16 4.2.1 LOINC Part map reference set . 16 4.2.2 LOINC Term to Expression Reference Set . 18 4.3 Benefits of Products of the Cooperative Work . 21 5 Guidance on Use of SNOMED CT and LOINC Together . 22 5.1 Use of SNOMED CT and/or LOINC in . 22 5.2 Practical Guidance on Uses of SNOMED CT and LOINC . 23 5.2.1 Guideline A - Vital Signs (Observation Names and Values) . 23 5.2.2 Guideline B - Laboratory Orders . 24 5.2.3 Guideline C - Laboratory Test Results (Observation Names and Values) . 26 5.2.4 Guideline D - Specimens . 30 5.2.5 Guideline E - Animal Species and Breeds . 32 5.2.6 Guideline F - Procedures (Laboratory Methods) . 33 5.2.7 Practical Uses of Part Maps and Expression Associations . 34 5.2 Terminology Scenarios - Summary . 40 6 References . 40 Using LOINC with SNOMED CT (3 April 2017) Using LOINC with SNOMED CT The Guide to Use of SNOMED CT and LOINC together provides advice on combined use of SNOMED CT and LOINC. -
Building the Business Case for SNOMED CT®
Building the Business Case for SNOMED CT® Promoting and Realising SNOMED CT®’s value in enabling high-performing health systems Russell Buchanan Marc Koehn A Gevity Consulting Inc. Company Building the Business Case for SNOMED CT® Promoting and Realising SNOMED CT®’s value in enabling high-performing health systems Copyright © 2014, International Health Terminology Standards Development Organisation (www.ihtsdo.org) Gordon Point Informatics Ltd. (GPi), Gevity Consulting Inc., and IHTSDO recognize all trademarks, registered trademarks and other marks as the property of their respective owners. Gordon Point Informatics Ltd. A Gevity Consulting Inc. Company (Gevity Consulting Inc. was formerly known as Global Village Consulting Inc.) #350 - 375 Water Street Vancouver, British Columbia Canada V6B 5C6 Telephone: +1-604-608-1779 www.gpinformatics.com | www.gevityinc.com ii Acknowledgments The authors would like to gratefully acknowledge a number of contributors without whose advice and support this paper would not have been possible. PROJECT STEERING COMMITTEE MEMBERS Members of the project steering committee provided overall guidance and insights throughout the project: • Liara Tutina, Customer Relations Lead (Asia Pac), IHTSDO • Vivian A. Auld, Senior Specialist for Health Data Standards, National Library of Medicine, USA • Dr. Md Khadzir Sheikh Ahmad, Deputy Director, Health informatic Centre, P&D Division, Ministry of Health, Malaysia • Kate Ebrlll, Head of National Service Operation and Management, National eHealth Transition Authority (NEHTA), Australia • Anna Adelöf, Customer Relations Lead (EMEA) , IHTSDO WORKING GROUP MEMBERS Our working group offered not only ongoing advice and reviews but also provided access to critical materials and contacts: • Liara Tutina, Customer Relations Lead (Asia Pac), IHTSDO • Dr. -
Direct Comparison of MEDCIN and SNOMED CT for Representation Of
Direct Comparison of MEDCIN ® and SNOMED CT ® for Representation of a General Medical Evaluation Template Steven H. Brown MS MD 1,2 , S. Trent Rosenbloom MD MPH 2 , Brent A. Bauer MD 3, Dietli nd Wahner -Roedler MD 3, David A. Froehling, MD, Kent R, Bailey PhD, M ichael J Lincoln MD, Diane Montella MD 1, Elliot M. Fielstein PhD 1,2 Peter L. Elkin MD 3 1. Department of Veterans Affairs 2. Vanderbilt University, Nashville TN 3. Mayo Clinic, Rochester MN Background : Two candidate terminologies to efforts. Usable and functionally complete support entry of ge neral medical data are standard terminologies need to be available to SNOMED CT and MEDCIN . W e compare the systems designers and architects. Two candidate ability of SNOMED CT and MEDCIN to terminologies to support entry of general medical represent concepts and interface terms from a data are SNOMED CT and MED CIN . VA gener al medical examination template. Methods : We parsed the VA general medical SNOMED CT is a reference terminology that evaluation template and mapped the resulting has been recommended for various components expressions into SNOMED CT and MEDCIN . of patient medical record information by the Internists conducted d ouble independent reviews Consolidated Health Informatics Council and the on 864 expressions . Exact concept level matches National Committee on Vital and Health were used to evaluate reference coverage. Exact Statistics. (12) SNOMED CT, licensed for US - term level matches were required for interface wide use by the National Library of Medicine in terms. 2003, was evaluated in 15 M edline indexed Resul ts : Sensitivity of SNOMED CT as a studie s in 2006 . -
Advancing Standards for Precision Medicine
Advancing Standards for Precision Medicine FINAL REPORT Prepared by: Audacious Inquiry on behalf of the Office of the National Coordinator for Health Information Technology under Contract No. HHSM-500-2017-000101 Task Order No. HHSP23320100013U January 2021 ONC Advancing Standards for Precision Medicine Table of Contents Executive Summary ...................................................................................................................................... 5 Standards Development and Demonstration Projects ............................................................................ 5 Mobile Health, Sensors, and Wearables ........................................................................................... 5 Social Determinants of Health (SDOH) ............................................................................................. 5 Findings and Lessons Learned .......................................................................................................... 6 Recommendations ........................................................................................................................................ 6 Introduction ................................................................................................................................................... 7 Background ................................................................................................................................................... 7 Project Purpose, Goals, and Objectives .................................................................................................. -
Comparative Study of Healthcare Messaging Standards for Interoperability in Ehealth Systems
Comparative Study of Healthcare Messaging Standards for Interoperability in eHealth systems BOAZ ABRAHAM | STUDENT ID: 18481798 | SUPERVISOR: DR ANUPAMA GINIGE |SUBMISSION YEAR: 2017 DEDICATION To my loving wife Ruth and daughter Sharon Rose Page | I ACKNOWLEDGEMENTS I would like to express my sincere thanks to, Dr Anupama Ginige, my supervisor, for providing guidance from the beginning and reviewing the thesis regularly. Her encouragement, feedback, tips and knowledge sharing helped me to complete this dissertation. I would like to thank all the Western Sydney University, SCEM and GRS department staffs who supported throughout my Master of Research course. I would like to thank my eHealth and Ministry of Health colleagues, friends and management who helped at different stages to gather information for the research. Lastly, I would like to thank my family for sharing their family time and support to complete this course in time. Page | II STATEMENT OF AUTHENTICATION The content presented in this thesis is, to the best of my knowledge and belief, original except as acknowledged in the references. I hereby declare that I have not submitted this material, either in full or in part, for a degree at this or any other institution. Boaz Abraham Page | III Table of Contents List of Tables .......................................................................................................................... VI List of figures ........................................................................................................................ -
Standard Nursing Terminologies: a Landscape Analysis
Standard Nursing Terminologies: A Landscape Analysis MBL Technologies, Clinovations, Contract # GS35F0475X Task Order # HHSP2332015004726 May 15, 2017 Table of Contents I. Introduction ....................................................................................................... 4 II. Background ........................................................................................................ 4 III. Landscape Analysis Approach ............................................................................. 6 IV. Summary of Background Data ............................................................................ 7 V. Findings.............................................................................................................. 8 A. Reference Terminologies .....................................................................................................8 1. SNOMED CT ................................................................................................................................... 8 2. Logical Observation Identifiers Names and Codes (LOINC) ........................................................ 10 B. Interface Terminologies .................................................................................................... 11 1. Clinical Care Classification (CCC) System .................................................................................... 11 2. International Classification for Nursing Practice (ICNP) ............................................................. 12 3. NANDA International -
Identifying Clinical Terms in Medical Text Using Ontology-Guided Machine Learning
JMIR MEDICAL INFORMATICS Arbabi et al Original Paper Identifying Clinical Terms in Medical Text Using Ontology-Guided Machine Learning Aryan Arbabi1,2, MSc; David R Adams3, MD, PhD; Sanja Fidler1, PhD; Michael Brudno1,2, PhD 1Department of Computer Science, University of Toronto, Toronto, ON, Canada 2Centre for Computational Medicine, Hospital for Sick Children, Toronto, ON, Canada 3Section on Human Biochemical Genetics, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, United States Corresponding Author: Michael Brudno, PhD Department of Computer Science University of Toronto 10 King©s College Road, SF 3303 Toronto, ON, M5S 3G4 Canada Phone: 1 4169782589 Email: [email protected] Abstract Background: Automatic recognition of medical concepts in unstructured text is an important component of many clinical and research applications, and its accuracy has a large impact on electronic health record analysis. The mining of medical concepts is complicated by the broad use of synonyms and nonstandard terms in medical documents. Objective: We present a machine learning model for concept recognition in large unstructured text, which optimizes the use of ontological structures and can identify previously unobserved synonyms for concepts in the ontology. Methods: We present a neural dictionary model that can be used to predict if a phrase is synonymous to a concept in a reference ontology. Our model, called the Neural Concept Recognizer (NCR), uses a convolutional neural network to encode input phrases and then rank medical concepts based on the similarity in that space. It uses the hierarchical structure provided by the biomedical ontology as an implicit prior embedding to better learn embedding of various terms. -
Health Level 7 an Overview
Health Level 7 An Overview W. Ed Hammond, Ph.D., FACMI Chair, HL7 © 2009 Health Level Seven ®, Inc. All Rights Reserved. HL7 and Health Level Seven are registered trademarks of Health Level Seven, Inc. Reg. U.S. Pat & TM Office. What does the name HL7 mean? “Health”“Health” represents represents thethe domaindomain ofof focus.focus. HL7’sHL7’s domaindomain includesincludes clinicalclinical andand administrativeadministrative data.data. "Level"Level Seven"Seven" refersrefers toto thethe highesthighest levellevel ofof thethe InternationalInternational OrganizationOrganization for for StandardizationStandardization (ISO)(ISO) communicationscommunications modelmodel forfor OpenOpen SystemsSystems InterconnectionInterconnection (OSI)(OSI) –– i.e., i.e., thethe applicationapplication levellevel.. Health Level Seven is an American National Standards Institute (ANSI - accredited Standards Developing Organizations (SDOs). © 2009 Health Level Seven ®, Inc. All Rights Reserved. HL7 and Health Level Seven are registered trademarks of Health Level Seven, Inc. Reg. U.S. Pat & TM Office. The Organization HL7 is headquartered in Ann Arbor, MI, and, like most of the other SDOs, is a not- for-profit volunteer organization. Its members—providers, vendors, payers, consultants, government groups and others who have an interest in the development and advancement of clinical and administrative standards for healthcare—develop the standards and other products. © 2009 Health Level Seven ®, Inc. All Rights Reserved. HL7 and Health Level Seven are registered trademarks of Health Level Seven, Inc. Reg. U.S. Pat & TM Office. What does HL7 do? Health Level Seven adheres to a strict and well-defined set of operating procedures that ensures consensus, openness and balance of interest on all matters, including balloting of standards. Health Level Seven develops specifications, the most widely used being a messaging standard that enables disparate healthcare applications to exchange key sets of clinical and administrative data.