DOCSLIB.ORG

Umls® Knowledge Sources

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Umls® Knowledge Sources 2/13/2006 UMLS® KNOWLEDGE SOURCES February Release 2006AA DOCUMENTATION Section 0: Preface 0.1 Purpose of This Documentation 0.2 Release Schedule 0.3 Audience 0.4 How to Use This Documentation 0.5 What's New for This Version of the UMLS Section 1: Introduction to the UMLS 1.1 Purpose of the UMLS 1.2 Conditions of Use of the UMLS 1.3 Brief Description of the UMLS Knowledge Sources and Associated Tools 1.4 Getting Started 1.5 Sources of Additional Information about the UMLS Section 2: Metathesaurus 2.0 Introduction 2.1 Source Vocabularies 2.2 Concepts, Concept Names, and their Identifiers 2.3 Relationships and Relationship Identifiers 2.4 Attributes and Attribute Identifiers 2.5 Data About the Metathesaurus 2.6 Concept Name Indexes 2.7 File Formats - Metathesaurus Rich Release Format (RRF) and Original Release Format (ORF) 2.8 Character Sets Section 3: Semantic Network 3.0 Introduction 3.1 Overview 3.2 Semantic Network ASCII Relational Format 3.3 Semantic Network ASCII Unit Record Format 3.4 Hierarchies for Semantic Types and Relations in the Semantic Network Section 4: SPECIALIST Lexicon and Lexical Tools Section 5: Using the UMLS Knowledge Source Server (UMLSKS) via the Internet 5.0 Background 5.1 Downloading UMLS Knowledge Sources 5.2 System Architecture 5.3 Querying the UMLSKS 5.4 Gaining Access to the UMLSKS 5.5 UMLSKS Documentation 1 Section 6: MetamorphoSys - the UMLS install and customization program 6.0 Introduction 6.1 MetamorphoSys Requirements 6.2 Starting MetamorphoSys 6.3 Using MetamorphoSys 6.4 Select Default Subset 6.5 Option Tabs 6.6 File Menu 6.7 Edit Menu 6.8 Options (for Advanced Users) 6.9 Reset Menu 6.10 Done; Begin Subset 6.11 API Documentation 6.12 Version Validation 6.13 Getting Help 6.14 Acknowledgments Section 7: UMLS DVD 7.0 Introduction 7.1 Hardware and Software requirements 7.2 Installing from DVD Appendix A. License for Use of the UMLS Metathesaurus A.1 Appendix to the License Agreement for Use of the UMLS®Metathesaurus Appendix B. Metathesaurus Metadata B.1 Columns and Data Elements B.1.1 Columns and Data Elements in Rich Release Format (RRF) B.1.2 Columns and Data Elements in Original Release Format (ORF) B.2 Attribute Names B.3 Abbreviations Used in Data Elements B.4 Source Vocabularies B.5 Source and Term Type Default Order of Precedence and Suppressibility B.6 Release Metadata Documentation Index Section 0 Preface 0.1 Purpose of This Documentation The Unified Medical Language System® (UMLS®) documentation describes the UMLS Knowledge Sources and related tools that are produced and distributed by the National Library of Medicine, a part of the National Institutes of Health in the U.S. Department of Health and Human Services. This documentation explains: - the purpose, content, and file structure of the current versions of the three UMLS Knowledge Sources - the Metathesaurus®, the Semantic Network, and the SPECIALIST Lexicon; - why and how to use associated UMLS programs, including: (a) MetamorphoSys, the install program for the three UMLS Knowledge Sources; it also provides a variety of output options, including Rich Release and Original Release Formats, and a choice of preferred character set, to produce custom subsets of the Metathesaurus. (b) the Lexical Programs, which help to deal with inflectional variation (e.g., treat, treats, treating, treatment) in 2 the English language; to convert American English to British English and vice versa, and to map text to concepts in the Metathesaurus; - how to access the UMLS resources via the UMLS Knowledge Source Server via (a) download, (b) an application programming interface (API), or (c) a Web browser. - the DVD-ROM distribution format for the UMLS Knowledge Sources and associated UMLS programs, which is available on request. 0.2 Release Schedule This documentation is updated for each release of the UMLS. It may be updated between releases if errors or omissions are found. The current document refers to the 2005AC version which was released in November 2005. The next UMLS version will be 2006AA, scheduled to be released in January 2006. 0.3 Audience This documentation and the UMLS resources it describes are intended for system developers, informatics researchers, librarians, and other information professionals. The documentation assumes that you are familiar with database concepts and the Internet. If you intend to use the UMLS Knowledge Sources in software applications, it assumes that you have experience with building and using complex databases. If you intend to use any of the UMLS programs, it assumes basic familiarity with Java. Neither the UMLS resources nor this documentation are intended for "end" users, such as individual health professionals or members of the general public - unless they are also software developers. 0.4 How to Use This Documentation 0.4.0 If you are an experienced UMLS user If you have done substantive work with preceding versions of the UMLS resources go directly to Section 0.5, which describes what has been changed for this new version - in the documentation and in the UMLS resources themselves. Section 0.5 will point you to the parts of the documentation that describe any changes to data files, content, or format introduced in this release. 0.4.1 If you are a novice UMLS user If you are new to the UMLS, Section 0.5 won't be particularly relevant (or understandable!), but you should read the rest of Section 0 and all of Section 1 before moving on to other parts of the documentation. Please read this brief overview, which explains what you will find in each section of the documentation. Section 1. Introduction to the UMLS The section explains the purpose of the UMLS, explains the conditions under which you may use the different UMLS components and how these relate to Open Access/Open Source principles, provides a brief description of each of the UMLS components and the relationships between them, describes how to get a feel for what is in each of the UMLS Knowledge Sources, and provides a list of additional reference materials about the UMLS. Section 2. Metathesaurus This section describes the content and structure of the Metathesaurus, a very large concept-oriented database that incorporates many different biomedical and health-related vocabularies, classifications, and coding systems. The Metathesaurus provides a consistent categorization of these concepts by assigning basic semantic types and makes all information from these terminologies accessible in common, fully-specified file formats. The Metathesaurus contains coding systems and vocabularies designated as U.S. standards under the Administrative Simplification provisions of the Health Insurance Portability and Accountability Act of 1996 (HIPAA) and as target U.S. government-wide standards by the Consolidated Health Informatics eGov initiative. Section 3. Semantic Network 3 This section describes the content and structure of the Semantic Network, a small database that includes information about the set of basic semantic types, or categories, to which Metathesaurus concepts may be assigned. The Semantic Network defines the relationships that may hold between these semantic types, as well as broad groupings of semantic types, such as all types that denote disorders (Disease or Syndrome, Acquired Abnormality, Neoplastic Process, etc.). Section 4. SPECIALIST Lexicon and Lexical Programs This section describes the content and structure of (1) the SPECIALIST Lexicon, a database of syntactic, morphological, and orthographic information for commonly occurring English language words and biomedical vocabulary that is useful for natural language processing applications; and (2) lexical programs, which are designed to assist in detecting and abstracting away from the inflectional, case, and word order variations encountered in natural language. One of these, MMTx (Metamap Transfer), is specifically designed to map arbitrary terms to concepts in the Metathesaurus or, equivalently, to discover Metathesaurus concepts within free text. Section 5. UMLS Knowledge Source Server This section describes how to access the UMLS resources from the UMLS Knowledge Source Server via download, application programmer interface, and interactive Web browser. Section 6. MetamorphoSys: the UMLS install and customization program This section describes MetamorphoSys, the install program for all the UMLS Knowledge Sources and the customization program for the Metathesaurus. UMLS users must use MetamorphoSys to install the Knowledge Sources. MetamorphoSys allows users to output data in either the 7-bit ASCII (the default) or Unicode UTF-8 character set. MetamorphoSys provides two file format options (Rich Release or Original Release Format) for the Metathesaurus, and provides a number of other options to customize it in specific applications. Section 7. UMLS DVD This section gives technical specifications for the UMLS DVD-ROM, an alternative method for distribution of UMLS content. The DVD-ROM is available on request to UMLS licensees. Appendices Appendix A includes the text of the License Agreement for Use of the UMLS Metathesaurus and Appendix. Appendix B includes additional information about the Metathesaurus data elements and the source vocabularies in the current Metathesaurus. 0.5 What's New for This Version of the UMLS 0.5.0 Metathesaurus The Metathesaurus now contains more than 1 million concepts and 5 million unique concept names from more than 100 different source vocabularies. In the 2006AA release 22 source vocabularies were updated including HCPCS, Altlink, CPT, and UMDNS. 0.5.1 MetamorphoSys Filter Changes With the 2006AA version of MetamorphoSys, several Filter names have changed. Users who use a configuration file from a previous version may recieve an error notice. Filters that have changed include: The Attributes To Exclude Filter, The Relationships To Exclude Filter, and The Semantic Types To Exclude Filter. 4 MRCXT File removed Users who require the MRCXT file will need to create that file after creating a subset. The information formerly contained in MRCXT is found in MRHIER.RRF.
Load more

Recommended publications
  • Case-Finding for Common Mental Disorders of Anxiety and Depression in Primary Care: an External Validation of Routinely Collected Data
    John, A., McGregor, J., Fone, D., Dunstan, F., Cornish, R., Lyons, R., & Lloyd, K. R. (2016). Case-finding for common mental disorders of anxiety and depression in primary care: an external validation of routinely collected data. BMC Medical Informatics and Decision Making, 16, [35]. https://doi.org/10.1186/s12911-016-0274-7 Publisher's PDF, also known as Version of record License (if available): CC BY Link to published version (if available): 10.1186/s12911-016-0274-7 Link to publication record in Explore Bristol Research PDF-document This is the final published version of the article (version of record). It first appeared online via BioMed Central at http://bmcmedinformdecismak.biomedcentral.com/articles/10.1186/s12911-016-0274-7. Please refer to any applicable terms of use of the publisher. University of Bristol - Explore Bristol Research General rights This document is made available in accordance with publisher policies. Please cite only the published version using the reference above. Full terms of use are available: http://www.bristol.ac.uk/red/research-policy/pure/user-guides/ebr-terms/ John et al. BMC Medical Informatics and Decision Making (2016) 16:35 DOI 10.1186/s12911-016-0274-7 RESEARCH ARTICLE Open Access Case-finding for common mental disorders of anxiety and depression in primary care: an external validation of routinely collected data Ann John1,2*, Joanne McGregor1, David Fone2,3, Frank Dunstan3, Rosie Cornish4, Ronan A. Lyons1,2 and Keith R. Lloyd1 Abstract Background: The robustness of epidemiological research using routinely collected primary care electronic data to support policy and practice for common mental disorders (CMD) anxiety and depression would be greatly enhanced by appropriate validation of diagnostic codes and algorithms for data extraction.
    [Show full text]
  • SNOMED CT and Clinical Coding
    SNOMED CT and Clinical Coding Presented by: The Terminology and Classifications Delivery Service, NHS Digital This presentation is designed to provide an overview of what a SNOMED CT generated discharge summary may look like and how SNOMED CT, ICD-10 and OPCS-4 can work together to fulfil different needs. 1 Setting the context National Information Board (NIB) • Published Personalised Health and Care 2020 - A Framework for Action • Endorses the move to adopt a single clinical terminology – SNOMED CT – to support direct management of care • “Actively collaborate to ensure that all primary care systems adopt SNOMED CT by the end of December 2016…… • ….And the entire health system should adopt SNOMED CT by April 2020. • During this time, we must also work with local authorities to understand and address the implications of this for social care.” Reference https://www.gov.uk/government/publications/personalised-health- and-care-2020 2 SCCI0034 Amd 35/2016 and Addendum: SNOMED CT SNOMED CT was approved at the SCCI Board in October 2016 http://www.content.digital.nhs.uk/isce/publication/scci0034 • Systems used by, or communicating coded clinical data to, General Practice service providers must use SNOMED CT as the clinical terminology within the system before 1 April 2018. SNOMED CT must be utilised in place of the Read codes before 1 April 2018 • Systems used by all other providers of health related services where the flow of information for the direct management of patient care comes into the NHS should use SNOMED CT 3 3 The case for SNOMED
    [Show full text]
  • The Healthcare System in Saudi Arabia and Its Challenges: the Case of Diabetes Care Pathway
    Journal of Health Informatics in Developing Countries www.jhidc.org Vol. 10 No. 1, 2016 Submitted: October 6, 2015 Accepted: January 17, 2016 The Healthcare System in Saudi Arabia and its Challenges: The Case of Diabetes Care Pathway Sarah Hamad ALKADI King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia Abstract. The advances of Information Technology (IT) play an important role globally in improving quality and capacity of healthcare sector. IT helps the health professions in managing resources and increasing productivity effectively. Although the conversion from paper to electronic patient records (EPR) conveys many benefits for both caregivers and caretakers, but also has brought many challenges in different aspects. Hospitals have implemented EPR to different degrees. They have used a set of standards in order to insure that data is accurately and consistently processed. Even though, the standardization of how data are captured, exchanged and used includes a set of complications that should be discovered to provide better health data quality for patients with multiple healthcare providers. Therefore, through an analysis of the EPR systems utilization in Saudi Arabia and the diabetes care pathway, three factors have been determined. These factors affect the workflow of the implementation and utilization of health information system (HIS) in terms of capturing, sharing and using its data efficiently. Keywords. HIS, EPR, information sharing, social factors, standards, health information management, diabetes care pathway, health informatics, data capturing, data sharing, Saudi Arabia. 1. Introduction The technology investment in health sector has importance in the management of healthcare services delivery in the developing countries. It is necessary to enhance the utilization as well as the implementation of HIS through standardizing the medical data in order to have a better data quality and more reliable system.
    [Show full text]
  • NCCHCA Finance Essentials Coding and Documentation –The CFO’S Favorite Subject!
    North Carolina Community Health Care Association NCCHCA Finance Essentials Coding and Documentation –The CFO’s Favorite Subject! September 10, 2019 Meri Harrington, CPC, CEMC Brown Consulting Associates, Inc. Today’s Agenda Unique Revenue Concerns • Service Coding • Upcoming Changes and E/M Visit Codes • FQHC Guidelines • Approach and Outcomes • Stories Told by Your Data • Diagnosis Coding and Reporting • Risk Adjustment Programs • Overview of Various Models • Anatomy of a risk score • Roles & Responsibilities • Integrated Behavioral Health – The Finest New Frontier • Care Models • Evidence‐Based Medicine • Integrated Behavioral Health © Brown Consulting Associates, Inc. 2019 2 © Brown Consulting Associates, Inc., 2019 Brown Consulting Associates, Inc. Bonnie R. Hoag, RN, CCS‐P, is the founder and a principal owner of Brown Consulting Associates, Inc., (BCA) which was established in 1989. Bonnie has served as a national physician office consultant and seminar speaker for a variety of firms, including St. Anthony Publishing and Consulting in Alexandria, Virginia and Medical Learning Inc. in Minneapolis, Minnesota. Bonnie has presented seminars to groups including, Montana Medical Association, Idaho Medical Association, Iowa Medical Society, and National Association of Community Health Centers and others. Since 1990 she and other BCA consultants have provided unique training to Federally Qualified Health Centers (FQHCs) and Rural Health Clinics (RHCs) throughout the U.S. Nearly 50 percent of BCA’s clinic client‐base is FQHC facilities. She has provided FQHC/RHC seminars for HRSA, National Health Service Corp and various Regional Primary Care Associations. Bonnie is honored to serve on the board of directors of a large community health center in her community. With her guidance, Brown Consulting Associates, Inc.
    [Show full text]
  • 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.
    [Show full text]
  • Sharing Valuesets, Codes, and Maps (SVCM)
    Integrating the Healthcare Enterprise 5 IHE IT Infrastructure (ITI) Technical Framework Supplement 10 Sharing Valuesets, Codes, and Maps (SVCM) HL7® FHIR® Release 4 Using Resources at FMM Level 3 - Normative 15 Revision 1.2 – Trial Implementation 20 Date: June 4, 2020 Author: ITI Technical Committee Email: [email protected] 25 Please verify you have the most recent version of this document. See here for Trial Implementation and Final Text versions and here for Public Comment versions. Copyright © 2020: IHE International, Inc. IHE IT Infrastructure Technical Framework Supplement –Sharing Valuesets, Codes, and Maps (SVCM) ______________________________________________________________________________ Foreword This is a supplement to the IHE IT Infrastructure Technical Framework V16.0. Each supplement 30 undergoes a process of public comment and trial implementation before being incorporated into the volumes of the Technical Frameworks. This supplement is published on June 4, 2020 for trial implementation and may be available for testing at subsequent IHE Connectathons. The supplement may be amended based on the results of testing. Following successful testing it will be incorporated into the IT Infrastructure 35 Technical Framework. Comments are invited and may be submitted at http://www.ihe.net/ITI_Public_Comments.. This supplement describes changes to the existing technical framework documents. “Boxed” instructions like the sample below indicate to the Volume Editor how to integrate the relevant section(s) into the relevant Technical Framework volume. 40 Amend Section X.X by the following: Where the amendment adds text, make the added text bold underline. Where the amendment removes text, make the removed text bold strikethrough. When entire new sections are added, introduce with editor’s instructions to “add new text” or similar, which for readability are not bolded or underlined.
    [Show full text]
  • Pathology Bound Code List and Its Replacement User Consultation V1.1 22/12/2015
    Document filename: Results of Request Submission Portal User Consultation Directorate / Programme Architecture, Project Diagnostic Data Standards and Service Innovation Document Reference Service Head Laura Sato Status Approved Owner Laura Sato Version 1.1 Author Kat Randle/Wendy Version issue date 22/12/2015 Tarbox Pathology Bound Code List and its replacement User Consultation Copyright ©2015 Health and Social Care Information Centre Pathology Bound Code List and its replacement User Consultation V1.1 22/12/2015 Document Management Revision History Version Date Summary of Changes 0.1 27 October 2015 First draft 0.2 06 November 2015 Further update following development 0.3 13 November 2015 Diagram updates 0.4 04December 2015 Further updates 1.0 07 December 2015 Final update 1.1 22 December 2015 For approval Reviewers This document must be reviewed by the following people: Reviewer name Title / Responsibility Date Version Laura Sato Head of Diagnostics 07/12/2015 V1.0 Data Service Ian Arrowsmith Head of SNOMED CT 17/12/2015 V1.0 implementation Deborah Drake Terminology Specialist 17/12/2015 V1.0 Approved by This document must be approved by the following people: Name Signature Title Date Version Head of Diagnostics Laura Sato 05/01/2016 V1.1 Data Service Glossary of Terms Term / Abbreviation What it stands for HSCIC Health and Social Care Information Centre IHTSDO International Health Terminology Standards Development Organisation LOINC Logical Observation Identifiers Names and Codes NLMC National Laboratory Medicine Catalogue PBCL Pathology Bounded Code List SNOMED CT Systematized Nomenclature of Medicine Clinical Terms TRUD Technology Reference Update UKTC UK Terminology Centre Document Control: Page 2 of 36 Copyright ©2015 Health and Social Care Information Centre Pathology Bound Code List and its replacement User Consultation V1.1 22/12/2015 The controlled copy of this document is maintained in the HSCIC corporate network.
    [Show full text]
  • Transitioning from Read to SNOMED CT
    Guidance for Primary Care: Transitioning from Read to SNOMED CT Version 1 Published December 2016 Copyright © 2016 Health and Social Care Information Centre. The Health and Social Care Information Centre is a non-departmental body created by statute, also known as NHS Digital. Guidance for Primary Care: Transitioning from Read to SNOMED CT Contents 1. Introduction 4 2. Overview 5 Purpose of this document 5 Audience 5 Scope 5 Feedback 5 3. Summary 6 Hints and Tips 7 4. The Transition to SNOMED CT 8 Mapping Read data to SNOMED CT 8 SNOMED CT content 8 5. Differences in term text between Read and SNOMED CT 10 Terms ending in NOS / NEC 10 Abbreviations 11 Duplicate Terms 11 Word Order 12 Plural nouns 12 Spelling errors 12 Outdated Terms 12 Terms beginning [X] 13 Terms beginning [SO] 13 Terms beginning [M] 14 6. Known data quality issues in Read coding choices 15 Occupation Terms 15 7M... | Subsidiary classification of methods of operation 15 7Q... | Drugs 16 Read Code Administration terms 16 Mental Disorder terms 16 ‘Grouper Terms’ that don’t mean what you think 16 Causes of injury and poisoning terms 17 And/Or Terms 18 ‘Referral to clinic A’ type terms 18 Symptoms, signs and ill-defined conditions terms 19 Copyright © 2016 Health and Social Care Information Centre. 2 Guidance for Primary Care: Transitioning from Read to SNOMED CT 7. Considerations for Queries 21 Present and not present 21 Terms that should be children but are not 21 Duplicate Terms 22 Synonyms that are not synonyms 22 Copyright © 2016 Health and Social Care Information Centre.
    [Show full text]
  • Health Informatics Standards: a View from Mid-America
    Review Paper c.J. McDonald, P.R. Review Paper Dexter, B. Takesue, J.M Overhage Regenstrieflnstitute for Health Care, Health Informatics Standards: Indiana University Medical Center, Indianapolis, Indiana, USA A View From Mid-America 1. Perspective behavior. Highway speed limits are a cently, everyone used their own idio­ familiar example. Most health syncratic codes to identify laboratory 'Those who develop standards face informatics message standards are tests and clinical measurements. Fur­ a number of problems and confusions. enabling. They provide a way to trans­ ther, health-care also deals with free For voluntary health informatics stan­ mit whatever information has been text, containing information which we dards efforts, the real problem might collected (e.g., a chestX-:ray report or cannot yet resolve into discrete items. be described as a reverse tragedy of a set of vital signs) to another medical A further challenge for medical data the commons[!]. In contrast to farin­ facility. By themselves they will not standards is the strict need to maintain ers on English commons, having more induce a particular behavior, such as privacy while simultaneously allowing information systems (cows) browsing the mandatory collection of a particu­ access by many health-care profes­ on the same informational commons lar set ofclinical variables wanted by a sionals, and the accompanying neces­ provides the most economic gain for regulatory agency. As a conse­ sity of carrying patient identifying in­ all. The tragedy is that for early adopt­ quence, regulatory agencies may dis­ formation along with the medical data. miss a voluntary informatics stan­ Banks only need to know account ers of standards the cost of putting their systems into the standard com­ dard and write their own very spe­ numbers, not individual persons.
    [Show full text]
  • Identifying Clinical Features in Primary Care Electronic Health Record Studies: Methods for Codelist Development
    Open Access Research BMJ Open: first published as 10.1136/bmjopen-2017-019637 on 22 November 2017. Downloaded from Identifying clinical features in primary care electronic health record studies: methods for codelist development Jessica Watson,1 Brian D Nicholson,2 Willie Hamilton,3 Sarah Price3 To cite: Watson J, ABSTRACT Strengths and limitations of this study Nicholson BD, Hamilton W, et al. Objective Analysis of routinely collected electronic health Identifying clinical features in record (EHR) data from primary care is reliant on the ► This paper presents rigorous reproducible methods primary care electronic health creation of codelists to define clinical features of interest. record studies: methods for for codelist generation to increase transparency and To improve scientific rigour, transparency and replicability, codelist development. BMJ Open replicability in electronic health record studies. we describe and demonstrate a standardised reproducible 2017;7:e019637. doi:10.1136/ ► Clear a priori definition of the feature of interest methodology for clinical codelist development. bmjopen-2017-019637 ensures clinical relevance and enables future Design We describe a three-stage process for developing researchers to assess the applicability of existing ► Prepublication history and clinical codelists. First, the clear definition a priori of codelists to future research questions. additional material for this the clinical feature of interest using reliable clinical paper are available online. To ► Generation of auditable, replicable and modifiable resources. Second, development of a list of potential codes view these files, please visit syntax for codelists enables replication and ‘future- using statistical software to comprehensively search all the journal online (http:// dx. doi. proofs’ codelists. available codes.
    [Show full text]
  • Validation of Autism Spectrum Disorder Diagnoses Recorded in the Clinical Practice Research Datalink, 1990–2014
    Journal name: Clinical Epidemiology Article Designation: Original Research Year: 2017 Volume: 9 Clinical Epidemiology Dovepress Running head verso: Hagberg and Jick Running head recto: Validation of ASD in the CPRD open access to scientific and medical research DOI: http://dx.doi.org/10.2147/CLEP.S139107 Open Access Full Text Article ORIGINAL RESEARCH Validation of autism spectrum disorder diagnoses recorded in the Clinical Practice Research Datalink, 1990–2014 Katrina Wilcox Hagberg Background: Prior studies have reported that the validity of autism spectrum disorder (ASD) Susan S Jick diagnoses recorded in the Clinical Practice Research Datalink (CPRD) was high; however, diag- nostic criteria and screening practices have changed since the last study was published in 2004. Boston Collaborative Drug Surveillance Program, Boston Objectives: 1) To calculate the positive predictive value (PPV) of ASD diagnoses recorded University School of Public Health, in the CPRD compared to original medical records and 2) to describe characteristics of cases Lexington, MA, USA and use of clinical codes that support the ASD diagnosis as recorded in the electronic data by general practitioners over time. Methods: We identified children with a code for ASD (autism spectrum disorder, autism, Asperger’s, or pervasive developmental disorder) in the CPRD from 1990 to 2014. We evaluated For personal use only. presence of codes in the electronic medical record indicating the presence of developmental delay, speech delay, behavioral problems, and other supporting clinical codes (e.g., therapy, referrals, etc.). We also evaluated changes in recording of these clinical codes over time. We compared the information present in the electronic medical record to original medical records for a sample of cases and calculated PPVs of ASD diagnoses recorded in the CPRD.
    [Show full text]
  • Implementing the SCCI Standard: SNOMED CT V 0.7 Draft 13/09/2016
    Document filename: Implementing the SCCI Standard SNOMED CT Classifications and Terminology Directorate / Programme Project SCCI ISN Development Service Document Reference <insert> Project Manager Denise Downs Status Draft Owner Lynn Bracewell Version 0.7 Author Denise Downs Version issue date 13/09/2016 Implementing the SCCI Standard: SNOMED CT An up-to-date version of this document can be found at on the UKTC web pages. Copyright ©2016 Health and Social Care Information Centre Page 1 of 44 The Health and Social Care Information Centre is a non-departmental body created by statute, also known as NHS Digital. Implementing the SCCI Standard: SNOMED CT v 0.7 Draft 13/09/2016 Document Management Revision History Version Date Summary of Changes 0.1 16/03/2016 Document Creation 0.2 02/04/2016 Address review feedback 0.3 03/06/2016 Further development to include primary care requirements 0.4 20/06/2016 Incorporating feedback following SCCI discussions on the standard 0.5 11/07/2016 Incorporating feedback from internal reviewers 0.6 15/08/2016 Incorporating feedback from internals Incorporating comments from externals responding to the burden 0.7 12/09/2016 assessment, and rebranding. Includes clinical safety statement. Reviewers This document must be reviewed by the following people: Reviewer name Title / Responsibility Date Version 0.1 Terminology Ian Spiers Implementation 01-Aug-2016 0.5 Specialist 0.7 0.2 Senior Terminology Andrew Perry Implementation 01-Aug-2016 0.5 Specialist 0.7 Head of SNOMED CT 0.4 Ian Arrowsmith 23-Jun-2016 Implementation 0.7 Principal Classifications Hazel Brear 01-Jul-2016 0.3 Specialist Senior Terminology Stuart Abbott 23-Jun-2016 0.3 Specialist Principal Terminology Ed Cheetham 12-Aug-2016 0.5 Specialist 08-July-206 0.4 Gerry Firkin SCCI advisor 12-Aug-2016 0.5 CCIO, Cambridge 26-Aug-2016 Sections of 0.6 Afzal Chaudhry University Hospitals 09-Sept-2016 0.7 NHS Digital, Clinical Clinical safety Hannah McCann 13-Sept-2016 Safety Engineer section of 0.7 Copyright © 2016 Health and Social Care Information Centre.
    [Show full text]