Guidance on Terminology Standards for Ireland
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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. -
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. -
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 -
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. -
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. -
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. -
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. -
What Is Medical Coding? What Is Medical Coding? Medical Coding Professionals Provide a Key Step in the Medical Billing Process
Training Certification Continuing Education ICD-10 Jobs Networking Resources Store Log In / Join Certification Overview Medical Coding Certification Medical Billing Certification Medical Auditing Certification Medical Compliance Certification Practice Manager Certification Locate Exam Prepare for Exam Exam Tips Credential Verification FAQ Home > Medical Coding > What is Medical Coding? What is Medical Coding? Medical coding professionals provide a key step in the medical billing process. Every time a patient receives professional health care in a physician’s office, hospital outpatient facility or ambulatory surgical center (ASC), the provider must document the services provided. The medical coder will abstract the information from the documentation, assign the appropriate codes, and create a claim to be paid, whether by a commercial payer, the patient, or CMS. Prepare for certification and a career in medical coding Validate your knowledge, skills, and expertise with medical coding certification Is Medical Coding the same as Medical Billing? No. While the medical coder and medical biller may be the same person or may work closely together to make sure all invoices are paid properly, the medical coder is primarily responsible for abstracting and assigning the appropriate coding on the claims. In order to accomplish this, the coder checks a variety of sources within the patient’s medical record, (i.e. the transcription of the doctor’s notes, ordered laboratory tests, requested imaging studies and other sources) to verify the work that was done. Then the coder must assign CPT® codes, ICD-9 codes and HCPCS codes to both report the procedures that were performed and to provide the medical biller with the information necessary to process a claim for reimbursement by the appropriate insurance agency. -
ICD-10 Faqs FAQ Review
Welcome to ICD-10 FAQ REVIEW Topics for Discussion . ICD-10 Overview . About ICD-10 . Why ICD-10 Matters ICD-10 . General ICD-10 FAQs FAQ Review . Split Claims FAQs . WV ICD-10 Provider Testing FAQs . Resources . Contact 1 ICD-10 Overview . World Health Organization developed ICD-10 in 1994 . Later adopted by Health and Human Services (HHS) and Centers for Disease Control and Prevention (CDC). ICD-10 is a provision of Health Insurance Portability and Accountability Act (HIPAA) regulations. HIPAA covers entities that include health care providers, payers, clearinghouses, billing services and others that must transition to ICD-10. Moving from ICD-9 to ICD-10 – U.S. is the last industrialized nation to adopt ICD-10 . ICD-9 is outdated - limited capacity, capability and unable to serve future needs . ICD-10-CM and ICD-10-PCS code sets . ICD-10-CM replaces ICD-9-CM (Volumes 1 and 2) . ICD-10-PCS replaces ICD-9-CM (Volume 3) . ICD-10 has no direct impact on Current Procedural Terminology (CPT) codes and Healthcare Common Procedure Coding System (HCPCS) 2 ICD-10 Overview (Cont.) . For services rendered on or after October 1, 2015 . All claims must use ICD-10 codes . Claims using ICD-9 codes for services rendered on or after October 1, 2015 will NOT be accepted . For services rendered before October 1, 2015 . All claims must use ICD-9 codes . Systems must accommodate BOTH ICD-9 and ICD-10 codes . Effective with the October 1, 2015 compliance date . Significant code increase from ICD-9 to ICD-10 . Increasing from 14,000 to approximately 69,000 ICD-10-CM codes . -
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 .