The Quest for Interoperability
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A Method for Constructing a New Extensible Nomenclature for Clinical Coding Practices in Sub-Saharan Africa
MEDINFO 2017: Precision Healthcare through Informatics 965 A.V. Gundlapalli et al. (Eds.) © 2017 International Medical Informatics Association (IMIA) and IOS Press. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0). doi:10.3233/978-1-61499-830-3-965 A Method for Constructing a New Extensible Nomenclature for Clinical Coding Practices in Sub-Saharan Africa Sven Van Laere, Marc Nyssen, Frank Verbeke Department of Public Health (GEWE), Research Group of Biostatistics and Medical Informatics (BISI), Vrije Universiteit Brussel (VUB), Laarbeeklaan 103, 1090 Brussels, Belgium Abstract The word nomenclature has to be used with care in the context Clinical coding is a requirement to provide valuable data for of sub-Saharan Africa. By the word “nomenclature”, usually billing, epidemiology and health care resource allocation. In they understand: “a coding system to provide codes that are sub-Saharan Africa, we observe a growing awareness of the used in invoices, to specify the health services that were pro- need for coding of clinical data, not only in health insurances, vided for particular patients”. We define nomenclature in a but also in governments and the hospitals. Presently, coding broader way, also taking into account the clinical definition of systems in sub-Saharan Africa are often used for billing pur- health services. poses. In this paper we consider the use of a nomenclature to In this paper we will present a way to build this new nomen- also have a clinical impact. -
Healthcare Terminologies and Classifications
Healthcare Terminologies and Classifications: An Action Agenda for the United States American Medical Informatics Association and American Health Information Management Association Terminology and Classification Policy Task Force Acknowledgements AHIMA and AMIA Terminology and Classification Policy Task Force Members Keith E. Campbell, MD, PhD The American Health Chair, AHIMA and AMIA Terminologies and Classifications Policy Task Force Information Management Chief Technology Officer, Informatics, Inc., and Assistant Clinical Professor; Association (AHIMA) is the Department of Medical Informatics and Clinical Epidemiology, Oregon Health and premier association of health Science University information management Suzanne Bakken, RN, DNSc, FAAN (HIM) professionals. AHIMA’s Alumni Professor of Nursing and Professor of Biomedical Informatics School of 51,000 members are dedicated to Nursing and Department of Medical Informatics, Columbia University the effective management of personal health information Sue Bowman, RHIA, CCS needed to deliver quality Director of Coding Policy and Compliance, American Health Information healthcare to the public. Management Association Founded in 1928 to improve the quality of medical records, Christopher Chute, MD, PhD AHIMA is committed to Professor and Chair of Biomedical Informatics, Mayo Foundation advancing the HIM profession in an increasingly electronic and Don Detmer, MD, MA President and Chief Executive Officer, American Medical Informatics Association global environment through leadership in advocacy, Jennifer Hornung Garvin, PhD, RHIA, CPHQ, CCS, CTR, FAHIMA education, certification, and Medical Informatics Postdoctoral Fellow Center for Health Equity Research and lifelong learning. To learn more, Promotion, Philadelphia Veterans Administration Medical Center go to www.ahima.org. Kathy Giannangelo, MA, RHIA, CCS, CPHIMS Director, Practice Leadership, AHIMA Gail Graham, RHIA The American Medical Director, Health Data and Informatics Department of Veterans Affairs Informatics Association (AMIA) Stanley M. -
A Reason for Visit Classification for Ambulatory Care
DATA EVALUATION AND METHODS RESEARCH Series 2 Number 78 A Reasonfor Visit Classification for AmbulatoryCare This report presents a classification system developed to code rea- sons for seeking ambulatory medical care. DHEW Publication No. (PHS) 79-1352 U.S. DEPARTMENT OF HEALTH, EDUCATION, AND WELFARE Public Health Service Office of the Assistant Secretary for Health National Center for Health Statistics Hyattsville, Md. February 1979 Library of Congress Cataloging in Publication Data Schneider, Don. A reason for visit classification for ambulatory care. (Vital and health statistics: Series 2, Data evaluation and methods research; no. 78) (DHEW publication; no. (PHS) 79-1352) Includes bibliographical references and index. 1. Nosology. 2. Ambulatory medical care. I. Appleton, Linda, joint author. II. McLemore, Thomas, ,joint author. III. Title. IV. Series: United States. National Center for Health Sta- tistics. Vital and health statistics: Series 2, Data evaluation and methods research; no. 78. V. Series: United States. Dept. of Health, Education and Welfare. DHEW publication; no. (PHS) 79-1352. [DNLM: 1. Ambulatory care. 2. Classification. W2 A N148vb no. 78] RA409.U45 no. 78 [RB115] 312’.07’23s [616’.001’2] 78-11549 NATIONAL CENTER FOR HEALTH STATISTICS DOROTHY P. RICE, Director ROBERT A. ISRAEL, Deputy Director JACOB J. FELDMAN, Ph.D., Associate Director for Analysis GAIL F. FISHER, Ph.D., Associate Director for the Cooperative Health Statistics System ELIJAH L. WHITE, Associate Director for Data Systems JAMES T. BAIRD, JR., Ph.D., Associate .Directorfor International Statistics ROBERT C, HUBER, Associate Director for Management MONROE G. SIRKEN, Ph. D., Associate Director for Mathematiccd Statistics PETER L. HURLEY, Associate Director for Operations JAMES M. -
Health & Coding Terminological Systems
Health & Coding Terminological Systems Hamideh Sabbaghi, MS Ophthalmic Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran Definition of Code Code is considered as word, letter, or number which has been used as passwords instead of words or phrases. Coding System 1. Classification system 2. Nomenclature system Classification System A well-known system of corrections for naming different stages of the disease. Nomenclature System A medical list of a specific system of preferred terms for naming disease. WHO- FIC • Main/reference classification • Related classifications to the main/ reference classification • Driven classification from the main/ reference classification Main/reference classification • ICD- 10 (1990, WHA) • ICD- 11 (2007, WHO) • http://who.int/classifications/apps/icd/icd10online/ ICD with a commonest usage can be used for: • Identification of health trend, mortality and morbidity statistics. • Clinical and health research purposes. Main/reference classification • ICD-9-CM (International Classification of Diseases, Ninth Revision, Clinical Modification) • ICF (International Classification of Function, Disability and Health) • ICHI (International Classification of Health Intervention) Related classifications to the main/ reference classification • ATC/DDD (The Anatomical Therapeutic chemical classification system with Defined Daily Doses) • ATCvet (The Anatomical Therapeutic Chemical Classification System for veterinary medicinal products) • ICECI (International Classification of External Causes -
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 .................................................................................................. -
Clinical Vocabularies for Global Real World Evidence (RWE) | Evidera
Clinical Vocabularies for Global RWE Analysis Don O’Hara, MS Senior Research Associate, Real-World Evidence, Evidera Vernon F. Schabert, PhD Senior Research Scientist, Real-World Evidence, Evidera Introduction significant volume of real-world evidence (RWE) analyses continue to be conducted with data A repurposed from healthcare administrative Don O’Hara Vernon F. Schabert databases. The range of sources represented by those databases has grown in response to demand for richer description of patient health status and outcomes. information for improved quality and coordination Data availability, including the range of available data of care, often using standardized messaging systems sources, has grown unevenly across the globe in response such as Health Level 7 (HL7). These messages are to country-specific market and regulatory dynamics. only as good as the standardization of codes between Nonetheless, as demand globalizes for RWE insights from message senders and receivers, which motivates the databases, those demands increase pressure on analysts encoding of facts using common code sets. The second to find ways to bridge differences between local data is the increased availability of common data models to sources to achieve comparable insights across regions. standardize the extraction and analysis of these data for RWE and drug safety purposes. While common data One of the challenges in bridging differences across models make compromises on the structure of tables databases is the codes used to represent key clinical and fields extracted from healthcare systems such as facts. Historically, RWE database studies have leveraged electronic medical records (EMR) and billing systems, local code sets for cost-bearing healthcare services they can improve consistency and replicability of analyses such as drugs, procedures, and laboratory tests. -
Ministry of Labour, Health and Social Affairs of Georgia
WWW.MOH.GOV.GE Ministry of Labour, Health and Social Affairs of Georgia Georgia Health Management Information System Strategy “Healthy Georgia, Connected to You” 2011 Table of Contents Executive Summary . 5 Goals and Objectives. 6 Governance. 7 Operational.Aspects. 9 HMIS Standards. .10 Message.Standards. .10 Vocabulary.Standards.for.Medical.Care. .11 Diagnosis.-.ICD.10,.Medcin. .12 Treatments.-.CPT. .13 Drugs.–RXNorm,.Multum,.Medispan,.First.Data.Bank. .13 Lab.–.LOINC,.SNOMED . .13 Administrative.Standards . .13 Citizens/Patients. .14 Provider.Credentialing,.Licensing.and.Unique.Identifiers. .14 National.Drug.Database . .14 Health.Data.Dictionary . .14 HMIS.Key.Indicators.and.Metrics. .15 HMIS.Core.Data.Sets. .15 HMIS Functionality . .16 Overview. .16 What.is.not.an.HMIS.component . .19 Software.Acquisition.versus.Development. .19 Selective.review.of.relevant.systems.that.are.already.available.in.Georgia . .23 Hesperus . .23 Vaccinations.system . .23 Electronic.registration.for.births.and.deaths.system. .23 TB.system,.AIDS.system,. .23 Surveillance.system.(DETRA).–.Infectious.Disease. .24 EU.project.for.MD’s.in.villages.to.be.equipped.with.400.PC’s . .24 SIMS. .24 Electronic Medical Record (EMR) . .25 Personal.and.Health.Information. .26 Results.Management. .26 Order.Management. .26 Decision.Support. .26 Reporting . .26 Electronic.Communication.and.Connectivity. .26 Patient.Support . .27 Administrative.Processes . .28 3 Financial Information System Functionality. .29 Georgian Health Data Repository (GHDR) . .32 Populating.the.Georgian.Health.Data.Repository.(GHDR) . .33 Extract,.Transform.Load. .34 Data.Domains.(Categories). .34 Data.Analysis.and.Presentation. .35 Reporting . .35 Dashboards . .36 GHDR.Uses. .36 Georgian.Healthcare.Statistics. .36 Monitoring.Healthcare.Costs. .36 Public.Health.Surveillance .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ...36 Decision.Support:..Improving.Patient.Care . -
Ata Lements for Mergency Epartment Ystems
D ata E lements for E mergency D epartment S ystems Release 1.0 U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES CDCCENTERS FOR DISEASE CONTROL AND PREVENTION D ata E lements for E mergency D epartment S ystems Release 1.0 National Center for Injury Prevention and Control Atlanta, Georgia 1997 Data Elements for Emergency Department Systems, Release 1.0 (DEEDS) is the result of contributions by participants in the National Workshop on Emergency Department Data, held January 23-25, 1996, in Atlanta, Georgia, subsequent review and comment by individuals who read Release 1.0 in draft form, and finalization by a multidisciplinary writing committee. DEEDS is a set of recommendations published by the National Center for Injury Prevention and Control of the Centers for Disease Control and Prevention: Centers for Disease Control and Prevention David Satcher, MD, PhD, Director National Center for Injury Prevention and Control Mark L. Rosenberg, MD, MPP, Director Division of Acute Care, Rehabilitation Research, and Disability Prevention Richard J. Waxweiler, PhD, Director Acute Care Team Daniel A. Pollock, MD, Leader Production services were provided by the staff of the Office of Communication Resources, National Center for Injury Prevention and Control, and the Management Analysis and Services Office: Editing Valerie R. Johnson Cover Design and Layout Barbara B. Lord Use of trade names is for identification only and does not constitute endorsement by the U.S. Department of Health and Human Services. This document and subsequent revisions can be found at the National Center for Injury Prevention and Control Web site: http://www.cdc.gov/ncipc/pub-res/deedspage.htm Suggested Citation: National Center for Injury Prevention and Control. -
International Classification of Diseases- 10Th Revision (ICD-10)
Massachusetts Deaths 1999 Frequently Asked Questions: International Classification of Diseases- 10th Revision (ICD-10) Effective with data year 1999, the International Classification of Diseases, Tenth Revision (ICD-10) is used to code and classify causes of death. This change in coding systems will affect the comparison of mortality data between 1999 and previous years. Definitions and Concepts What is ICD-10? ICD-10 is an abbreviation for the International Classification of Diseases- Tenth revision. The International Classification of Diseases is a classification system developed by the World Health Organization (WHO). The United States uses the ICD in accordance with an international agreement. The purpose of an international classification system is to promote international comparability in collecting, classifying, and tabulating mortality statistics. Why has the ICD been revised? The ICD is revised to reflect changes in medical classification practices. The ICD was first implemented in 1900, and has undergone revisions approximately every ten years, except for the Ninth revision which was in effect between 1979-1998. There has been an increase in the number of specific cause of death codes from about 4,000 codes in ICD-9 to about 8,000 codes in ICD-10. Beginning with 1999, mortality data are coded according to the Tenth revision of the ICD. Can I compare data classified in ICD-10 to data classified in ICD-9? Differences in the coding between ICD-9 and ICD-10 make direct comparisons between the two classification systems difficult for three reasons: 1) there have been changes made in the codes that are assigned to causes of death; 2) there have been changes to the rules used to determine the underlying cause of death; and 3) there have been changes in the codes that comprise the leading cause of death categories.