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Response to the 2015 ONC Standards AdvisoryMedical Informatics group, 3M Healthcare Data Dictionary3M Health Information Systems5-1. [General] What other characteristics should be considered for including best available standards and implementation specifications in this list?Describing standards and implementation specifications for inclusion, while providing the advantage of interoperability, has the caveat of becoming too fine grained and over-fitting the noise rather than the signal in the data. However, the list provided is sufficiently detailed, and appears to avoid over-fitting the noise in almost all cases. Peer-review and addressing of all submitted comments must be undertaken so that the list does not become too narrow and potentially excludes appropriate candidates. In general, the characteristics outlined are valid and useful. However, there are some clear gaps. One characteristic that is poorly defined within this specification is implementation guides for standard vocabularies which is addressed in 5-4. In addition to adding implementation specifications, a general note about the terminology version(s) should be provided. Please consider the inclusion of terminology versions, either by themselves or by specifying value sets within the implementation specifications. This is especially important for terminologies that do not have concept permanence. Finally, it is important to designate the terminology identifier (Object Identifier-OID) for each standard terminology.Additionally, please consider how narrow these domain specifications should be. If a terminology like Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) can cover large areas of clinical care, it would be better not to specify them to excruciating levels of detail because implementation would be difficult. However, it is important to provide guidance in the implementation of large terminologies (i.e. SNOMED CT) and those with difficult nomenclature (i.e. Logical Identifier Names and Codes-LOINC) so that implementers with minimal terminology expertise are able to understand the intended use of the terminology for each purpose. Another aspect to consider is specifying standard map sets between clinical terminologies, such as the mappings between the substances domain in SNOMED CT and the ingredient, precise ingredient, and multiple ingredient semantic types in RxNorm. This will enable interoperability between the pharmacy and the clinical systems. Centers for Medicare and Medicaid (CMS) is providing such map sets for some administrative/billing terminologies. Additionally, there is collaboration between Regenstrief and the International Health Terminology Standards Development Organization (IHTSDO) for mappings between a subset of LOINC and SNOMED CT concepts. However, additional map sets for clinical data are required for interoperability.In addition to the terminologies and value sets, the correct datatypes must be defined. For example, the standards may specify that coded concepts must follow the CD datatype as specified by the HL7 ISO 21090 Harmonized Datatypes Specification. This will reveal inconsistencies in the specifications. For example, National Provider Identifier is recommended for identifying Care Team Members. When we examine the data type, it becomes obvious that the NPI is not a terminology, it identifies individuals, rather than types of individuals. Hence, the Care Team Member data element is of type Instance Identifier, which consists of an Identifier Scheme (a code that denotes “National Provider Identifier” as the scheme) and the identifier (the actual NPI of an individual). Finally, the standards suggested by the ONC should align with other healthcare initiatives such that compliance with the standards is harmonized with regulations from other governing bodies such as CMS and The Joint Commission (JHACO). There must be a defined use case for each of the standard purposes and clear terminology harmonization across the regulatory initiatives should be a top priority. 5-2. [General] Besides the four standards categories included in this advisory, are there other overall standards categories that should be included?In general, the four standards categories are sufficient in establishing a foundation for standards based exchange. However, more attention needs to be given to the implementation and education around the standards. Within the industry there is wide variation in the understanding and implementation of standards. This variability presents significant challenges in the exchange and understanding of data across systems. Another aspect that should be considered is to make the recommendations intelligent – that is, specify formal models for post-coordination, and how post-coordinated expressions can be compared. This is extremely important because clinical narrative is almost always post-coordinated, and there will never be single terminology codes that capture a complex post-coordinated expression using a single pre-coordinated concept. To do that, terminologies will have to over-fit the noise rather than the data. We understand that the objective of this standards advisory is to recommend pilot or mature standards. However, a future directions section will emphasize the directions for improvement rather than simply specifying the limited capabilities that are currently available. The future directions category may not necessarily identify specific standards (since these are not yet mature or piloted), but it needs to specify focus areas to support future needs. When complex medical data is captured using fine-grained structured data, care must be taken so that the meaningful information is not lost in the data. Capturing meaningful information would require the use of post-coordination or information models. Standardizing “information” rather than simply “terminology codes” should be the focus of future directions. If future directions are outside the scope of the advisory, they may be published separately and be provided as a reference in the advisory.In addition, the “Purpose” column under the four categories themselves include both semantic and implementation purposes. Since this standards advisory is to standardize clinical data exchange rather than administrative data exchange, ONC needs to promote discussion on whether the objective of the “Purpose” column is to capture and exchange semantically and clinically valid information, or to fulfill implementation requirements, for example: A “vaccine” is a semantic category, which may be considered as a subcategory of “drugs”. However, “Immunizations – Historical” and “Immunizations – Administered” are both implementation specifications. The advisory specifies CVX (Immunizations – Historical) and NDC (Immunizations – administered) for different applications of the same data. Both of these can be covered by specifying RxNorm (Drugs) as the terminology, with application specific value sets as the implementation specification for both the immunization categories. If different terminologies are desired, providing standardized map sets for clinical data solves this issue, and these map sets can be implemented by either the sender or the recipient. 5-3. [General] For sections I through IV, what “purposes” are missing? Please identify the standards or implementations specifications you believe should be identified as the best available for each additional purpose(s) suggested and why. While the list of purposes for terminology standards are appropriate at a high level there are some areas that are missing. The focus of the purposes needs to depict data elements that are important to health, not just health care. Properly capturing features of health that are observed outside of the healthcare system is critical. It is also suggested that the purposes fully align with the common clinical data set presented in the interoperability roadmap.Some purposes are missing a designated standard terminology. The purposes of food allergies, functioning and disability as well as industry and occupation are not coupled with any specific standard terminology. It is confusing to users to have a purpose on this list with no designated standard terminology. At a minimum, it is suggested that the ONC investigates SNOMED CT coverage for food allergies. ONC should review the research presented on ICF and SNOMED CT. SNOMED CT should be evaluated for functioning and disability as well as terminology coverage in ancillary care disciplines such as physical and occupational therapy domains. Finally industry and occupation could be assessed from U.S. Standard Occupation Classification codes and SNOMED CT.The designated purposes neglect areas of health related to preventative medicine, public health, behavioral health, socioeconomic status, attitudes toward health care, advanced directives and genomics. Specifically, the Institute of Medicine (IOM) suggests that alcohol use, tobacco use and exposure, depression, education, financial resource strain, intimate partner violence, physical activity, social connections and social isolation and stress are relevant domains of behavioral health that should be captured within the electronic health record ADDIN EN.CITE <EndNote><Cite><Author>Medicine</Author><Year>2014</Year><RecNum>11</RecNum><DisplayText>(1)</DisplayText><record><rec-number>11</rec-number><foreign-keys><key app="EN" db-id="5w0adwsx8ev904e5xvoppx5j2wws02z959z5" timestamp="1425419695">11</key><key app="ENWeb" db-id="">0</key></foreign-keys><ref-type name="Report">27</ref-type><contributors><authors><author>Institute of Medicine</author></authors></contributors><titles><title>Capturing Social and Behavioral Domains and Measures in Electronic Health Records: Phase 2</title></titles><edition>November 13, 2014</edition><dates><year>2014</year></dates><pub-location> of Medicine</publisher><work-type>Report</work-type><urls></urls></record></Cite></EndNote>(1).Finally there are areas that are not represented within the purposes that are valuable clinical data elements. The suggested (but non exhaustive) list is as follows: Physical assessment observations and valuesCurrently the only standardized assessment observations outlined in the interoperability roadmap are smoking status and vital signs. Clinical observations that are essential to evidence based practice and clinical guidelines should be captured as structured data within the electronic health record. 3M is participating in a nursing terminology initiative in place stemming out of the Minnesota Big Data Nursing conference to model sharable, comparable, nursing data ADDIN EN.CITE <EndNote><Cite><Author>Westra</Author><Year>2015</Year><RecNum>1267</RecNum><DisplayText>(2)</DisplayText><record><rec-number>1267</rec-number><foreign-keys><key app="EN" db-id="fafts9f0pax0x4e025u5fftntafeprsvdxd0" timestamp="1424125163">1267</key><key app="ENWeb" db-id="">0</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Westra, B. L.</author><author>Latimer, G. E.</author><author>Matney, S. A.</author><author>Park, J. I.</author><author>Sensmeier, J.</author><author>Simpson, R. L.</author><author>Swanson, M. J.</author><author>Warren, J. J.</author><author>Delaney, C. W.</author></authors></contributors><auth-address>School of Nursing, University of Minnesota, Minneapolis, MN, USA westr006@umn.edu.
Siemens Healthcare, Malvern, PA, USA.
M Health Information Systems, Salt Lake City, UT, USA.
School of Nursing, University of Minnesota, Minneapolis, MN, USA.
HIMSS, Chicago, IL, USA.
Cerner Corporation, Kansas City, MO, USA.
Fairview Lakes Medical Center, Wyoming, MN, USA.
Warren Associates, LLC, Plattsmouth, NE, USA.</auth-address><titles><title>A national action plan for sharable and comparable nursing data to support practice and translational research for transforming health care</title><secondary-title>J Am Med Inform Assoc</secondary-title><alt-title>Journal of the American Medical Informatics Association : JAMIA</alt-title></titles><periodical><full-title>Journal of American Medical Informatics Association</full-title><abbr-1>J Am Med Inform Assoc</abbr-1><abbr-2>JAMIA</abbr-2><abbr-3>Jamia</abbr-3></periodical><dates><year>2015</year><pub-dates><date>Feb 10</date></pub-dates></dates><isbn>1527-974X (Electronic)
1067-5027 (Linking)</isbn><accession-num>25670754</accession-num><urls><related-urls><url>;(2). The goal is to identify routine assessment observations at the point of care for all types of physiologic assessments and model them with LOINC as the question and SNOMED CT and the value set answers. A presentation was given at the recent LOINC meeting (Feb. 12th) to discuss the first puterized Provider Order Entries (CPOE)The granularity and scope of CPOE is variable across systems and organizations. Work needs to be done to investigate the efforts in defining standardized terminology content that is appropriate for CPOE.Patient activity orders (such as ambulation) are required by The Joint Commission (JCAHO) Nursing care and safety orders (such as turn every four hours, falls prevention, safety risk) are critical to decreasing length of hospital stay. Additional content such as nutrition orders should also be captured using standard terminology.We would recommend examination into the current coverage for orders in clinical terminologies such as LOINC and SNOMED CT Goals and OutcomesJCAHO has outlined National Patient Safety Goals for 2015 that span the ambulatory, behavioral, critical access hospital, home care and hospital settings. All of these safety goals need to be evaluated to ensure terminology content coverage ADDIN EN.CITE <EndNote><Cite><Author>Commission</Author><Year>2015</Year><RecNum>12</RecNum><DisplayText>(3)</DisplayText><record><rec-number>12</rec-number><foreign-keys><key app="EN" db-id="5w0adwsx8ev904e5xvoppx5j2wws02z959z5" timestamp="1425591851">12</key></foreign-keys><ref-type name="Web Page">12</ref-type><contributors><authors><author>The Joint Commission</author></authors></contributors><titles><title>2015 National Patient Safety Goals </title><alt-title>2015 National Patient Safety Goals</alt-title></titles><volume>2015</volume><number>02/24/2015</number><dates><year>2015</year><pub-dates><date>3/5/15</date></pub-dates></dates><urls><related-urls><url>;(3). Improvements in physical outcomes of procedures is critical in providing clinical care. For example increased tolerance of exercise, compliance of nutritional regime or improvements in range of motion after knee surgery etc. must be documented to evaluate the clinical effectiveness of interventions. Patient health goal tracking should be collected as codified standardized structured data so that the data can be shared across providers and used to trend patient progress and attitudes towards health over time. Today, the current terminologies available for recording of patient sensitive outcomes in nursing are semantically inconsistent. For example: 1) the Clinical Care Classification System records nursing outcomes as the Problem + “improved”, “deteriorated” or “stabilized”; 2) the Omaha System records outcomes on a five point Likert scale; and 3) the Nursing Outcomes Classification (NOC) has different type scales specific to outcomes.5-4. [General] For sections I through IV, is a standard or implementation specification missing that should either be included alongside another standard or implementation specification already associated with a purpose?It is obvious that implementation specifications are absent from Section I: Vocabulary/code sets/terminology. If ONC cannot suggest practical ways for organizations to implement the myriad standards listed, it will lead to implementation difficulties as well as inconsistent implementations. Implementation specifications must include standard value sets and possibly map sets. 3M has been assisting organizations nationwide in the adoption and implementation of standard terminologies for nearly two decades. During this time 3M has mapped millions of legacy codes to standard terminologies. Compliance with the terminology standards creates a predicament for many organizations because the coding systems and terminologies themselves have complex characteristics, and there is no recommended, comprehensive implementation strategy to follow. These challenges in implementing standard terminologies need to be addressed with appropriate implementation guides. Large terminologies are often difficult to implement and maintain. Since no one terminology covers all of health care and one terminology can be used for multiple purposes, the ONC must provide clear guidance on what subsets of terminology are appropriate for each purpose. For example, The National Library of Medicine (NLM) releases the SNOMED CT Core Problem list to represent common clinical findings that would appear on a patient problem list. Additionally, Regenstrief releases a top result and order code lists for LOINC codes. It should also be noted that, while these lists categorize smaller lists of codes for organizations to manage; it is still difficult for organizations to maintain multiple lists of codes across different versions of terminology over time. Another specific challenge that needs to be addressed is the level of granularity at which clinical content should be represented. 3M has published and presented findings of challenges in normalizing clinical data from disparate systems one of the common themes is addressing the varying levels of granularity between code systems (standard and legacy alike). This has also been presented by recent literature. In a 2014 study of the content within Consolidated Clinical Document Architecture (C-CDA) samples D’Amore et al. note that “medication allergies should be encoded at the ingredient level (e.g.,‘aspirin’) or drug class level (e.g., ‘sulfonamides’), but some samples reported allergens at the semantic clinical drug level (e.g., ‘aspirin 81 mg oral tablet’). While the latter representation is syntactically correct, it is clinically questionable to say that someone is allergic to a specific form and dose of aspirin. To reconcile such terminology issues, receivers of C-CDA documents would need to perform substantial manual reconciliation or apply intricate normalizing logic to the hierarchy of potential RxNorm codesPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5EJmFwb3M7QW1vcmU8L0F1dGhvcj48WWVhcj4yMDE0PC9Z
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ADDIN EN.CITE.DATA (4).” It is important to note that RxNorm does not include concept for drug classes such as “Penicillins.” So, terminology for Medication Allergens purpose is underspecified. We recommend adding SNOMED CT as the terminology, and a value set derived from the SNOMED CT substance domain as the implementation specification for Medication Allergens.One standard that is noticeably absent from the Radiology Interventions and Procedures purpose is LOINC. Several large organizations use LOINC to encode radiology, and it is considered a mature standard thus meets the criteria for inclusion.5-5. [General] For sections I through IV, should any of the standards or implementation specifications listed thus far be removed from this list as the best available? If so, why?In Section I: Vocabulary/code sets/terminology, lab tests should be broken out into two line items, lab orders and lab results, which should both have LOINC as the standard. Please see 5-4 for comment about content coverage for RxNorm for Medication Allergens.The ONC should also cautiously consider the use of proprietary terminologies such as CPT and CDT which require licensing and royalties. The use of terminologies which require licensing and fees impact the development and dissemination of health information technology applications and the sharing of data across entities. If the ONC supports the sharing of clinical data encoded with these terminologies, guidance should be provided on the content sharing processes as it applies to licensing and use of these terminologies. 5-6. [Section I] Should more detailed value sets for race and ethnicity be identified as a standard or implementation specification?The 1997 Federal Register Notice on race and ethnicity by the Office of Management and Budget (OMB) classifies race into five categories (American Indian or Alaska Native, Asian, Black or African American, Native Hawaiian or other Pacific Islander, and White), and ethnicity into two categories (Hispanic or Latino, and Not Hispanic or Latino). This classification may be adequate for statistical purposes within the scope of OMB, but these classifications are underspecified for use in healthcare. In fact, the Bureau of Census also uses more categories for race/ethnicity compared to the OMB classifications. Furthermore, the OMB classifications of race and ethnicity are not conformant with the HL7 ISO 21090 Harmonized Datatypes Specification and other standard terminology specifications. A terminology must be uniquely identified by a terminology or codesystem identifier such as an OID registered with a standards registry such as the HL7 OID Registry. The OMB classifications are not formally registered as codesystems, and the closest identifiers available for these are the value sets defined by the CDC PHIN VADS (Centers for Disease Control and Prevention’s Public Health Information Network Vocabulary Access and Distribution System), which are aligned with HL7 version 2 and version 3 tables, as well as specifications defined by the Federal Health Information Model (FHIM) project.Hence, race and ethnicity need to be clearly defined from four aspects – definitions, conformant terminology design, conformant value set design, and the individual concepts themselves. Race is defined as a biological category based on distinguishing genotypical and phenotypical characteristics of a group of individuals or an individual, which are inherited genetically from parents to children, and hence does not change over the life of an individual. Ethnicity is defined as a socio-cultural category of a group of individuals or an individual based on environmental attributes like physical location, culture, nationality, language, religion, food and so on, are influenced by the environment in which a person lives, and hence may change over time. Some concepts may appear to be both a race and ethnicity, e.g. Icelander. However, in such cases, one must clearly define Icelander race (a subtype of Norse/Northern Germanic race) and Icelander ethnicity (a subtype of Northern European or Scandinavian ethnicity) as two separate concepts, which often (but not always) apply to an individual together. Identifying the race and ethnicity of an individual at a finer level of granularity is necessary for assessing their genetic (e.g., increased risk of colon cancer in Ashkenazi Jewish population) and environmental (e.g., increased rick of stomach cancer in Japanese population) risks for certain diseases, respectively. It must also be noted that an individual may have multiple races or ethnicities, and clinical information systems must support multiple concepts for race or ethnicity.However, a detailed classification of ethnicity and race is an exhaustive process, especially when the races and ethnicities are from distant parts of the world and the terminology editors and medical practitioners in the United States may not be aware of the subtleties. On the other hand, SNOMED CT has a more comprehensive (though incomplete and sometimes inaccurate) classification of ethnicity compared to any administrative classification currently prevalent in the United States. However, SNOMED CT currently has a high level and non-exhaustive classification of race. Classification of race and ethnicity in SNOMED CT can be expected to grow in the future as more countries become members of IHTSDO, and are interested in classifying the races and ethnicities that are of interest to them. In addition, the hierarchical classification in SNOMED CT allows one to infer that the Icelander race is a subcategory (specialization) of the Caucasian race, and that Norwegian ethnicity is a subcategory of Scandinavian ethnicity. This provides the healthcare provider or the healthcare administrative staff the flexibility to record data at any level of granularity, which may then be rolled up using the SNOMED CT hierarchy from the “Clinical Documentation value set level of granularity” to the level of granularity desired for specific applications such as “US Bureau of Census value set granularity” or “OMB value set level of granularity”. Hence, the ideal approach for the definition of race and ethnicity for clinical usage in the United States will be defining US-realm-specific value sets for race and ethnicity that are derived from specific versions of SNOMED CT and are updated over time. The preceding definitions of terminology (e.g. SNOMED CT International Release or SNOMED CT US Edition) and value sets provide how such extensible definitions can be formally specified. SNOMED CT is formally defined as a terminology and is registered with the HL7 OID Registry, in contrast with the OMB classifications. In addition, any value set that is defined based on SNOMED CT for race (e.g. Race Value Set for US Healthcare Interoperability) and ethnicity (e.g. Ethnicity Value Set for US Healthcare Interoperability) need to be formally specified according to the upcoming HL7 Value Set Definition Specification, and be distributed through the National Library of Medicine’s Value Set Authority Center.5-7. [Section I] Should more traditionally considered “administrative” standards (e.g., ICD-10) be removed from this list because of its focus on clinical health information interoperability purposes?There are valuable use-cases where mortality and morbidity are expressed and analyzed using administrative standards such as ICD-10-CM and ICD-9-CM Volume 1 (Diagnosis), and cases where procedures are reported using administrative classifications such as ICD-10-PCS, ICD-9-CM Volume III (Procedure), and Current Procedural Terminology (CPT). Additionally, many well established methodologies such as (APR DRGs) are built on these administrative standards and used widely across health care. Clear specifications must be provided about the intent and scope of these terminologies, so that these terminologies are not extrapolated for understanding the clinical conditions and treatments performed to a patient. Administrative terminologies are designed to aggregate or classify medical data into categories with high level granularity to support administrative functions such as billing or statistical analysis, and are not reliable for medical documentation and treatment. Meaningful and comprehensive clinical definitions can be created using proper post-coordination and information models that use clinical terminologies (such as SNOMED CT for diagnoses and procedures). However, most electronic medical record systems, messaging engines and messaging standards (such as HL7 v2) do not support medical information models or post-coordinated expressions. Phasing out administrative terminologies in medical records is feasible only when post-coordinated expressions and information models are standardized and are supported by various components that are involved in documentation, storage, transmission and exchange of medical records. Due to these constraints, administrative terminologies should not be prematurely prohibited from use in medical records. Instead, their applicability, scope and limitations must be clearly identified in ONC specifications, with clear instructions not to extrapolate clinical information for healthcare delivery from administrative terminologies. 5-8. [Section I] Should “Food allergies” be included as a purpose in this document or is there another approach for allergies that should be represented instead? Are there standards that can be called “best available” for this purpose?All allergy types should be included as purposes in this document. However, merely specifying an “allergy” or an “allergen” is insufficient – the data must specify-at a minimum-the allergen, allergic reaction and allergy severity (though the severity can vary in the same individual between different instances). This requires that the items in the purpose field have clear definitions in this advisory – such as allergen (substance) vs allergy (disease state).In a recent use case delivered to the IHTSDO, 3M provided examples of the variation in the representation of allergy data that exists within the electronic health record today. 3M’s experience with allergy data has mostly centered on establishing alerts for medical providers. Clinically, there are distinct differences in hypersensitivities, pseudo-allergies or intolerances and true allergic reactions. However, these term is loosely used by clinicians and laypeople to denote any such ‘reaction’. It has been 3M’s experience that these ‘reactions’ are defined in many different ways. The representation of allergy disorders, allergic reactions, allergen substance and severity are captured in an inconsistent manner. In addition to food allergies and medication allergies, ONC should consider expanding the allergy purpose to include environmental allergens. Other allergies should also be included, such as those similar to environmental allergens (e.g., latex, animal dander, bee stings). SNOMED CT has the best coverage for food, environmental or drug allergies and allergens. However, we understand that RxNorm may sometimes be used for drug allergens. D’Amore noted that omission or misuse of allergic reaction and allergy sensitivity was a chief trouble spot within Consolidated Clinical Document Architecture (C-CDA) documents PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5EJmFwb3M7QW1vcmU8L0F1dGhvcj48WWVhcj4yMDE0PC9Z
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ADDIN EN.CITE.DATA (4). Allergy information is critical to patient care and effort that aligns work being done across standards development organizations such as HL7 Patient Care, IHTSDO and others should be spearheaded by the ONC. 5-9. [Section I] Should this purpose category be in this document? Should the International Classification of Functioning, Disability and Health (ICF) be included as a standard? Are there similar standards that should be considered for inclusion? In 2010, the World Health Organization (WHO) and the IHTSDO signed a collaboration agreement to harmonize WHO classifications and SNOMED CT. The Authors were members of a joint working group, set up by WHO and IHTSDO, through their Joint Advisory Group (JAG), to collect and discuss relevant information on the topic of the harmonization between the International Classification of Functioning, Disability and Health (ICF) and SNOMED CT. Findings from a gap analysis between ICF and SNOMED CT demonstrated that ICF is semantically, hierarchically, and lexically different from SNOMED CT ADDIN EN.CITE <EndNote><Cite><Author>Karlsson D.1</Author><Year>2013</Year><RecNum>13</RecNum><DisplayText>(5)</DisplayText><record><rec-number>13</rec-number><foreign-keys><key app="EN" db-id="5w0adwsx8ev904e5xvoppx5j2wws02z959z5" timestamp="1425594615">13</key><key app="ENWeb" db-id="">0</key></foreign-keys><ref-type name="Report">27</ref-type><contributors><authors><author>Karlsson D.1, Gongolo F. 2, Robinson M.M. 3, Millar J. 4 </author><author>1 Link?ping University, Sweden, 2Friuli Venezia Giulia Central Health Directorate, Italy, 3World</author><author>Health Organization 4International Health Terminology Standards Development Organisation </author></authors><secondary-authors><author>WHO - FAMILY OF INTERNATIONAL CLASSIFICATIONS NETWORK ANNUAL MEETING 2013</author></secondary-authors></contributors><titles><title>ICF-SNOMED CT Harmonization a gap analysis</title></titles><dates><year>2013</year><pub-dates><date>12 – 18 October 2013</date></pub-dates></dates><pub-location>Beijing, China</pub-location><work-type>Poster</work-type><urls><related-urls><url>;(5). The major finding was a 40% gap and it was impossible to map SNOMED CT to ICF. Therefore, ICF should not be included as standard within the interoperability roadmap at this time. There is a newly formed working group within the IHTSDO developing a function and abilities subset of SNOMED CT. Because of this important step towards a principle-based convergence of domain vocabularies using SNOMED CT, we feel that the United States should be involved in defining function and ability concepts within SNOMED CT.5-10. [Section I] Should the MVX code set be included and listed in tandem with CVX codes?CVX (Vaccines Administered, HL7 table 0292) and MVX (Manufactures of Vaccines, HL7 table 0227) are HL7 terminologies maintained by CDC’s National Center for Immunization and Respiratory Diseases. CVX encodes the type of vaccine, including those that are currently used in the US (active status, e.g. Inactivated Polio Vaccine), not used in the US anymore (inactive status, e.g. Oral Polio Vaccine, currently used in other countries but not in the US), and vaccines that are not yet available and possibly under research (‘never active’ status, e.g. leprosy vaccine, HIV vaccine, malaria vaccine). MVX contains a list of US vaccine manufactures, which is a finite list, and includes the concept “Other”. There is a use for recording the manufacturer of the vaccine using MVX codes in addition to the type of vaccine administered (CVX). However, both can be addressed using more fine-grained codes such as NDCs or RxNorm. Please see response to 5-11.5-11. [Section I] Public health stakeholders have noted the utility of NDC codes for inventory management as well as public health reporting when such information is known/recorded during the administration of a vaccine. Should vaccines administered be listed as a separate purpose with NDC as the code set?CVX and MVX terminologies provide a much higher level of granularity compared to fine-grained pharmacy terminologies such as NDC and RxNorm. This is analogous to the difference between administrative terminologies (e.g. ICD-9-CM, ICD-10-CM, ICD-10-PCS, CPT, etc.) and clinical terminologies (e.g. SNOMED CT, LOINC). If a CVX code indicates that an individual has received an influenza vaccine, it is not possible to infer what strains constituted the vaccine, unless the time (year) and location (country) of administration is also recorded. In addition, it is not possible to identify what branded preparation was used, when a single manufacturer (MVX) may have more than one vaccine against the same disease.However, medication terminologies such as NDC and RxNorm provide a much finer level of granularity about the vaccine type, manufacturer and the branded preparation. In addition, it would reduce the burden if both medications administered and vaccines administered can be recorded using a single medication administration system (such as the electronic medication administration record) rather than using two separate systems. Hence, we recommend the use of NDC or RxNorm codes to identify the semantic branded drug (RxNorm semantic type SBD) or branded packaging (RxNorm semantic type BPCK) to capture the vaccine (medication) administered with the finest level of granularity. It must be noted that RxNorm supports additional semantic types at a higher level of granularity such as Semantic Clinical Drug (SCD) and Generic Pack (GPCK) when the specific brand name is not available or needs to be harmonized across brands. The Semantic Clinical Drug and Semantic Branded Drug are in turn linked to ingredients, which may be specific influenza strains in case of the US seasonal flu vaccine from a specific year, various pneumococcal strains (in case of a branded vaccine such as Prevnar 13), or the different inactivated viruses used in the Measles Mumps and Rubella (MMR) vaccine.We recommend using the RxNorm RXCUI codes rather than NDC codes, since RxNorm codes have concept permanence whereas NDC codes may change their meanings over time. RxNorm includes mapping to NDC codes, and the RxCUIs can be mapped to NDCs or mapped/rolled up to higher levels of granularity such as CVX or MVX as needed by the sender or the receiver of the information to support specific use cases.5-12. [Section I] Is there a best available standard to represent industry and occupation that should be considered for inclusion in the 2016 Advisory? The Standard Occupation Codes (SOC) ADDIN EN.CITE <EndNote><Cite><Author>Statistics</Author><Year>2015</Year><RecNum>10</RecNum><DisplayText>(6)</DisplayText><record><rec-number>10</rec-number><foreign-keys><key app="EN" db-id="5w0adwsx8ev904e5xvoppx5j2wws02z959z5" timestamp="1425417201">10</key></foreign-keys><ref-type name="Web Page">12</ref-type><contributors><authors><author>U.S. Bureau of Labor Statistics </author></authors></contributors><titles><title>Standard Occupational Classification </title></titles><volume>2015</volume><number>02/27/15</number><dates><year>2015</year></dates><pub-location> States Department of Labor</publisher><urls></urls></record></Cite></EndNote>(6) are used by Federal statistical agencies to classify workers into occupational categories. It is our recommendation that ONC stay aligned with this standard list of codes. Even though we recommend this as the standard, we also suggest that the code set be evaluated and expanded for use within healthcare. Currently, CDA-2 uses the National Uniform Claim Committee Health Care Taxonomy (NUCC) codes, therefore, there needs to be an evaluation of the NUCC codes to determine the ones needed within SOC codes. Additionally, it is worthwhile to investigate the overlap and coverage of SNOMED CT occupation content when determining the appropriate approach to capturing industry and occupation data. Special attention to industries that have a known health risk should be identified and examines with scrutiny in order to assess the effect that job type has on health status. 5-13. [Section I] If a preferred or specific value set exists for a specific purpose and the standard adopted for that purpose, should it be listed in the “implementation specification” column or should a new column be added for value sets?Value sets are created to support specific applications, and hence must be treated as implementation specifications for terminologies for specific domains of content. For example, RxNorm can be the terminology, with specific value sets defined to capture immunization information.The advisory should also specify the correct data type to be used for coded data, such as the CD datatype from ISO 21090 Datatypes specification, which requires a code system identifier, code system version identifier, and concept code to uniquely identify a coded concept. The CD datatype optionally specifies the value set from which the coded concept was selected. The datatype should be provided as an implementation specification for the entire Terminologies category so that the implementers implement terminologies consistently. Some systems merely send a concept code without identifying the code system or the code system version, which hinders interoperability.On a related note, the recommendations for “Sex” list the “HL7 v3 Value Set for Administrative Gender” as the terminology in section I. A value set is not a terminology, but an implementation specification defined based on one or more terminologies. This data element needs to be correctly defined using the underlying terminology and value set.5-14. [Section II] Several laboratory related standards for results, ordering, and electronic directory of services (eDOS) are presently being updated within HL7 processes. Should they be considered the best available for next year’s 2016 Advisory once finalized?The LOI and LRI implementation guides have undergone multiple ballot reconciliations over the past two years. The ONC S&I work group “a LOINC order code” is wrapping up collaborations with an advisory document to ONC, which is considered part of the ongoing discussions described earlier.5-15. [Section II] Are there best available standards for the purpose of “Patient preference/consent?” Should the NHIN Access Consent Specification v1.0 and/or IHE BPPC be considered?We recommend that ONC review NHIN Access Consent Specification v1.0, IHE BPPC and HL7 CDA R2 Consent Directives R1 to select an appropriate standard for patient preference and consent directives for protected health information.5-16. [Section II] For the specific purpose of exchanging behavioral health information protected by 42 CFR Part 2, does an alternative standard exist to the DS4P standard?We are not aware of an alternative to HL7 DS4P v1 specification for the purpose of limiting access while exchanging behavioral health information.5-17. [Section II] For the 2015 list, should both Consolidated CDA? Release 1.1 and 2.0 be included for the “summary care record” purpose or just Release 2.0? For the 2015 incentive year, it’s would be hardship for everyone to transfer over from CDA 1.1 to 2.0. It would be a large impact on implementers to enforce a change midyear. However, several new document types have been added to CDA 2.0, such as care plan and transfer summary, and end users should be encouraged the move to 2.0 as rapidly as possible in 2015 and 2.0 be mandated for 2016. 5-18. [Section IV] Should specific HL7 message types be listed? Or would they be applicable to other purposes as well? If so, which ones and why?Section IV lists functionality at a higher level of granularity than what is supported by HL7 messages. Hence, we recommend that the appropriate standard listed under these functional categories be consulted for the appropriate HL7 or other implementation standard for message and document specifications to fulfill the high level functions. ADDIN EN.REFLIST 1.Medicine Io. Capturing Social and Behavioral Domains and Measures in Electronic Health Records: Phase 2. Report. : Institute of Medicine, 2014.Westra BL, Latimer GE, Matney SA, Park JI, Sensmeier J, Simpson RL, et al. A national action plan for sharable and comparable nursing data to support practice and translational research for transforming health care. J Am Med Inform Assoc. mission TJ. 2015 National Patient Safety Goals 2015 [updated 3/5/15; cited 2015 02/24/2015]. Available from: 'Amore JD, Mandel JC, Kreda DA, Swain A, Koromia GA, Sundareswaran S, et al. Are Meaningful Use Stage 2 certified EHRs ready for interoperability? Findings from the SMART C-CDA Collaborative. Journal of the American Medical Informatics Association : JAMIA. 2014;21(6):1060-8.Karlsson D.1 GF, Robinson M.M. 3, Millar J. 4 , 1 Link?ping University S, 2Friuli Venezia Giulia Central Health Directorate, Italy, 3World, Organisation HOIHTSD. ICF-SNOMED CT Harmonization a gap analysis. Poster. Beijing, China: 2013 12 – 18 October 2013. Report No.Statistics USBoL. Standard Occupational Classification : United States Department of Labor; 2015 [cited 2015 02/27/15]. ................
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