Archive for the ‘Electronic Health Records’ Category
The National Library of Medicine has announced that the April 2017 RxNorm monthly release contains a Prescribable Name (PSN) for all RxNorm normal forms for active human drugs sold in the United States (US) with a few exceptions. Drugs without a PSN include allergenic extracts and certain forms containing three or more ingredients. PSNs are user-friendly synonyms of RxNorm normalized drug names and are meant to be used as display names in e-prescribing systems. Unlike other RxNorm synonyms, there can only be a single PSN associated with an RxNorm concept (i.e., RxNorm Concept Unique Identifier or RXCUI). RxNorm editors create PSNs based upon the drug label on DailyMed. PSNs may contain common ingredient abbreviations and tall man lettering, and their strengths may not be normalized as they are in the RxNorm normalized names.
PSNs were first introduced in the July 2014 release of RxNorm. NLM would like to thank the US Department of Veterans Affairs, Veterans Health Administration (VHA) for help with funding this project, and the National Council for Prescription Drug Programs (NCPDP) for help with organizing content discussions with stakeholders. The addition of PSNs to RxNorm is a major step towards improving the efficiency and accuracy of drug information management in e-prescribing systems.
The National Library of Medicine has announced the addition of CVX (Vaccines Administered) as a new data source to RxNorm. The addition of CVX data to RxNorm helps facilitate the electronic exchange of vaccine information in electronic health records. CVX includes both active and inactive vaccines available in the United States. CVX codes for inactive vaccines allow electronic transmission of historical immunization records. CVX is maintained and developed by the Centers for Disease Control and Prevention (CDC), National Center of Immunization and Respiratory Diseases (NCIRD).
The National Library of Medicine seeks applications for novel informatics and data science approaches that can help individuals gather, manage and use data and information about their personal health. A goal of this program is to advance research and application by patients and the research community through broadly sharing the results via publication, and through open source mechanisms for data or resource sharing. To bring the benefits of big data research to consumers and patients, new biomedical informatics and data science approaches are needed, shaped to meet the needs of consumers and patients, whose health literacy, language skills, technical sophistication, education and cultural traditions affect how they find, understand and use personal health information. Data science approaches are needed to help individuals at every step, from harvesting to storing to using data and information in a personal health library.
Application deadlines are May 1, 2017, and March 19, 2018. Eligible applicants include higher education institutions, government entities, faith-based or community-based organizations, and other institutions. Applicants must base their proposed work on an informed profile of the intended users, and, the work should be developed through interaction with the user. The strongest projects will provide approaches that incorporate health data and information from more than one source, such as diagnostic images and links to full-text articles or genome sequence data linked to a family health history. An application should be centered on the problem area being addressed and the intended audience, propose a possible solution that employs novel data science or informatics, and undertake a pilot that will result in evidence of the degree of success and/or needed next steps. Applicants should expect to involve the intended users in their work. The number of awards will be contingent upon NIH appropriations and the submission of a sufficient number of meritorious applications. Up to $250,000 direct costs may be requested in any single year. The total project period may not exceed four years.
MedlinePlus Connect is a National Library of Medicine (NLM) service linking patient portals and electronic health record systems to context-relevant information from MedlinePlus. The Connect service returns relevant information for a patient’s specific diagnosis, medication, or lab test. In particular, since 2011 Connect has supported requests for lab test information using LOINC (Logical Observation Identifiers Names and Codes).
In April 2016, NLM released an enhancement to the responses to lab test queries. The response now names the source of the information and provides a short snippet of the content in addition to the hyperlinked title of the content page. This contextual information was added to help end-users understand the differences between multiple links which will be useful as NLM expands its collection of lab test content. For example, responses will now include links to MedlinePlus health topics that are focused on lab tests. For a look at the new format, visit the NLM Technical Bulletin.
In January the Centers for Disease Control and Prevention and the National Library of Medicine announced that public health departments can now use funding from the CDC Preventive Health and Health Services (PHHS) Block Grant to access journals, publications, the latest evidence and additional resources through the Public Health Information Access Project (PHIAP) of the National Library of Medicine. The mechanism was developed through the Centers for Surveillance, Epidemiology and Laboratory Services at the Centers for Disease Control working with partners inside CDC and outside the agency. The goal of the project is to provide low-cost access to high-value, evidence-based resources to improve public health practice in state public health departments. Costs must be tied to state work plans. To obtain access to library services for your state health department, refer to the list of state block grant contacts about including this item in the state work plan.
On April 6 the National Library of Medicine (NLM) Value Set Authority Center (VSAC), in collaboration with the Office of the National Coordinator for Health Information Technology (ONC) and Centers for Medicare & Medicaid Services (CMS), published the 2016 annual update for the electronic clinical quality measure (eCQM) value sets for eligible hospitals and eligible professionals. Providers will use these updated eCQM value sets to electronically report 2017 quality data for CMS quality reporting programs. CMS updates these electronic reporting specifications annually to improve alignment with current clinical guidelines and code systems so that they remain relevant and actionable within the clinical care setting. CMS has re-specified all of the updated measures using Quality Data Model (QDM) 4.2 based-HQMF version R 2.1.
Access to the VSAC suite of tools requires a free Unified Medical Language System® Metathesaurus License.
- Application Programming Interface (API): Programmatically retrieve value sets. Find VSAC API documentation in the VSAC Support Center.
- VSAC Web Page: Browse and download specific eCQM value sets. Filter by specific CMS eMeasure ID, QDM Category, or Meaningful Use Measure type (EH or EP). Accessible from the Search Value Sets tab on the VSAC Web page.
- Data Element Catalog: Data element names (value set names) required for capture in electronic health record (EHR) technology certified under the 2014 Edition of the ONC Standards and Certification Criteria.
- VSAC Collaboration Tool: Interactive and centralized collaboration among VSAC authors and collaborators. Find VSAC Collaboration documentation in the VSAC Support Center.
The updated eCQM measure specifications are available in the CMS eCQM Library and the Electronic Clinical Quality Improvement (eCQI) Resource Center.
The National Library of Medicine (NLM) Value Set Authority Center (VSAC) has just launched VSAC Collaboration; a tool to support communication, knowledge management and document management by value set authors and stewards. VSAC Collaboration provides a central site where value set authors can post value sets for collaborative discussion. In that site, teams can share threaded discussions about the value sets, view recent value set expansions posted by site members, organize their value sets by usage and by team’s workflow needs, and receive activity and change notifications from VSAC.
VSAC Collaboration Tool training webinars and slides are available. Access to the VSAC and to the VSAC Collaboration Tool requires a free Unified Medical Language System® Metathesaurus License.
The next session of the National Library of Medicine Informatics Lecture Series will be held on November 4, at 11:00am-12:00pm PST, with the feature presentation Use of Clinical Big Data to Inform Precision Medicine. The speaker will be Joshua Denny, MD, Associate Professor in the Departments of Biomedical Informatics and Medicine at Vanderbilt University Medical Center. This talk will be broadcast live and archived.
At Vanderbilt, Dr. Denny and his team have linked phenotypic information from de-identified electronic health records (EHRs) to a DNA repository of nearly 200,000 samples, creating a ‘virtual’ cohort. This approach allows study of genomic basis of disease and drug response using real-world clinical data. Finding the right information in the EHR can be challenging, but the combination of billing data, laboratory data, medication exposures, and natural language processing has enabled efficient study of genomic and pharmacogenomic phenotypes. The Vanderbilt research team has put many of these discovered pharmacogenomic characteristics into practice through clinical decision support. The EHR also enables the inverse experiment – starting with a genotype and discovering all the phenotypes with which it is associated – a phenome-wide association study (PheWAS). Dr. Denny’s research team has used PheWAS to replicate more than 300 genotype-phenotype associations, characterize pleiotropy, and discover new associations. They have also used PheWAS to identify characteristics within disease subtypes.
Dr. Denny is part of the NIH-supported Electronic Medical Records and Genomics (eMERGE) network, Pharmacogenomics Research Network (PGRN), and Implementing Genomics in Practice (IGNITE) networks. He is a past recipient of the American Medical Informatics Association New Investigator Award, Homer Warner Award, and Vanderbilt Chancellor’s Award for Research. Dr. Denny remains active in clinical care and in teaching students. He is also a member of the National Library of Medicine Biomedical Library and Informatics Review Committee.
The National Library of Medicine has announced the release of the first video tutorial for the RxClass Web application. The five-minute Searching and Navigating Through Drug Classes Using RxClass Application tutorial describes the RxClass major interface elements and functionalities. RxClass allows users to explore drug classes and their members, links the drug classes to drug information in RxNorm, provides a browser interface for navigating the hierarchies of drug classes, and includes a search mechanism for locating specific drug classes or drugs. The tutorial is available from a link on the Learning Resources for NLM Clinical Terminology Artifacts and Tooling and the NLM Distance Education Resources pages.
NLM has also announced the release of the first video tutorial featuring the Value Set Authority Center (VSAC) REST API. The API allows remote retrieval of value set information through URL-based calls that contain functions and corresponding parameters. The API is based on the IHE Sharing Value Sets (SVS) Technical Framework. The new two-minute tutorial Authentication with the Value Set Authority Center (VSAC) SVS API demonstrates how to perform proper authentication when submitting requests to the VSAC REST API. The authentication process uses UMLS credentials (username and password) and consists of two steps. First request a Ticket Granting Ticket (TGT), then request the Service Ticket (ST). The TGT is valid for eight hours, while the ST is valid for five minutes and can be used to submit only one API request. Users must generate a new ST for each new API request. The tutorial is available from a link on the VSAC Support Center, Learning Resources for NLM Clinical Terminology Artifacts and Tooling, and the NLM Distance Education Resources pages.
NIH encourages the use of common data elements (CDEs) in clinical research, patient registries, and other human subject research in order to improve data quality and opportunities for comparison and combination of data from multiple studies and with electronic health records. The NIH Common Data Element Resource Portal provides access to information about NIH-supported CDEs, as well as tools and resources to assist investigators developing protocols for data collection. In addition, the session recording and presentation slides for the 90-minute webinar “NIH Common Data Element (CDE) Initiatives – Overview,” held on September 8, are available for viewing.