International Journal of Functional Informatics and Personalised Medicine http://www.inderscience.com/browse/index.php?journalID=295&year=2010&vol=3&issue=4 Inderscience Publishers Ltd en-uk International Journal of Functional Informatics and Personalised Medicine 1756-2104 1756-2112 © 2010 Inderscience Publishers Ltd editor@inderscience.com https://www.inderscience.com/images/files/coverImgs/ijfipm_scoverijfipm.jpg http://www.inderscience.com/browse/index.php?journalID=295&year=2010&vol=3&issue=4 http://www.inderscience.com/link.php?id=40210 The desire for standardised, reusable questions has been expressed in a variety of domains, including Public Health and Emergency Preparedness and Response. Reusable questions will enable the collection of interoperable data and facilitate efficient aggregation and timely analysis. The metadata required to describe such reusable objects is multi-layered, including attributes that describe the question existing independent of any data collection context, plus metadata elements that describe its relationships to the form and its elements, the deployment of the form for data collection, and finally the context in which the question was answered. Contrary to common standard interpretation, this building and variable set of metadata does not cause the question or its underlying data element to become a different object, but rather it becomes a more refined version of the same object whose full description must be made available when the answer data is analysed. Questions on public health forms: the metadata required to describe standard data elements deployed in dynamic contexts
Kristi Eckerson, Tim Morris
International Journal of Functional Informatics and Personalised Medicine, Vol. 3, No. 4 (2010) pp. 260 - 272
The desire for standardised, reusable questions has been expressed in a variety of domains, including Public Health and Emergency Preparedness and Response. Reusable questions will enable the collection of interoperable data and facilitate efficient aggregation and timely analysis. The metadata required to describe such reusable objects is multi-layered, including attributes that describe the question existing independent of any data collection context, plus metadata elements that describe its relationships to the form and its elements, the deployment of the form for data collection, and finally the context in which the question was answered. Contrary to common standard interpretation, this building and variable set of metadata does not cause the question or its underlying data element to become a different object, but rather it becomes a more refined version of the same object whose full description must be made available when the answer data is analysed.

]]> 10.1504/IJFIPM.2010.040210 International Journal of Functional Informatics and Personalised Medicine, Vol. 3, No. 4 (2010) pp. 260 - 272 Kristi Eckerson Tim Morris Research and Health Sciences Division, Emory University, 1784 North Decatur Road, Suite #520, Atlanta, Georgia 30322, USA. ' Research and Health Sciences Division, Emory University, 1784 North Decatur Road, Suite #520, Atlanta, Georgia 30322, USA reusable questions metadata context standards public health forms dynamic data collection definition public health records interoperability standardised questions. 2011-05-21T23:20:50-05:00 3 4 260 272 2011-05-21T23:20:50-05:00 http://www.inderscience.com/link.php?id=40211 In many areas of practice and research, clinical observations are recorded on data collection forms by asking and answering questions, yet without being represented in accepted terminology standards these results cannot be easily shared among clinical care and research systems. LOINC contains a well-developed model for representing variables, answer lists and the collections that contain them. We have successfully added many assessments and other collections of variables to LOINC in this model. By creating a uniform representation and distributing it worldwide at no cost, LOINC aims to lower the barriers to interoperability among systems and make this valuable data available across settings when and where it is needed. LOINC®: a universal catalogue of individual clinical observations and uniform representation of enumerated collections
Daniel J. Vreeman, Clement J. McDonald, Stanley M. Huff
International Journal of Functional Informatics and Personalised Medicine, Vol. 3, No. 4 (2010) pp. 273 - 291
In many areas of practice and research, clinical observations are recorded on data collection forms by asking and answering questions, yet without being represented in accepted terminology standards these results cannot be easily shared among clinical care and research systems. LOINC contains a well-developed model for representing variables, answer lists and the collections that contain them. We have successfully added many assessments and other collections of variables to LOINC in this model. By creating a uniform representation and distributing it worldwide at no cost, LOINC aims to lower the barriers to interoperability among systems and make this valuable data available across settings when and where it is needed.

]]> 10.1504/IJFIPM.2010.040211 International Journal of Functional Informatics and Personalised Medicine, Vol. 3, No. 4 (2010) pp. 273 - 291 Daniel J. Vreeman Clement J. McDonald Stanley M. Huff Indiana University School of Medicine, 410 W. 10th Street, Suite 2000, Indianapolis, IN 46202, USA; and Regenstrief Institute, Inc, 410 W. 10th Street, Suite 2000, Indianapolis, IN 46202, USA. ' Lister Hill National Centre for Biomedical Communications, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bldg. 38-A, Rm. 7N704, Bethesda, MD 20894, USA. ' University of Utah, 26 South 2000 East, Room 5775 HSEB, Salt Lake City, UT 84112, USA; and Intermountain Healthcare, 4646 W. Lake Park Blvd., Salt Lake City, UT 84120, USA clinical observations framework health information technology patient data patient assessments data sets public health forms clinical care research systems standards terminology healthcare technology data collection forms variables answer lists uniform representation interoperability. 2011-05-21T23:20:50-05:00 3 4 273 291 2011-05-21T23:20:50-05:00 http://www.inderscience.com/link.php?id=40212 The United States Health Information Knowledgebase (USHIK) is an online, publicly accessible registry/repository of healthcare metadata originally developed by Center for Medicare and Medicaid Services (CMS) and the Department of Defense (DoD) and currently maintained by the Agency for Healthcare Research and Quality (AHRQ). It contains metadata for various healthcare standards, measures, forms and other data sets. Its users include researchers, Standards Development Organisations (SDOs), clinicians, Electronic Health Record (EHR) developers and users, and various Federal- and state-level government entities. USHIK provides the capability to visually organise summary metadata, analyse metadata sets and interactively compare metadata sets. This functionality can be used for analysing and harmonising standards, measures and other healthcare data sets. United States Health Information Knowledgebase (USHIK)
Chuck Penoza, Robin Barnes, Martin Chaparro, Jerry Carney, Brad Levin, Matthew Chudy, Sheri LaBonte
International Journal of Functional Informatics and Personalised Medicine, Vol. 3, No. 4 (2010) pp. 292 - 313
The United States Health Information Knowledgebase (USHIK) is an online, publicly accessible registry/repository of healthcare metadata originally developed by Center for Medicare and Medicaid Services (CMS) and the Department of Defense (DoD) and currently maintained by the Agency for Healthcare Research and Quality (AHRQ). It contains metadata for various healthcare standards, measures, forms and other data sets. Its users include researchers, Standards Development Organisations (SDOs), clinicians, Electronic Health Record (EHR) developers and users, and various Federal- and state-level government entities. USHIK provides the capability to visually organise summary metadata, analyse metadata sets and interactively compare metadata sets. This functionality can be used for analysing and harmonising standards, measures and other healthcare data sets.

]]> 10.1504/IJFIPM.2010.040212 International Journal of Functional Informatics and Personalised Medicine, Vol. 3, No. 4 (2010) pp. 292 - 313 Chuck Penoza Robin Barnes Martin Chaparro Jerry Carney Brad Levin Matthew Chudy Sheri LaBonte Data Consulting Group Inc., 965 Jefferson, Detroit, Michigan, 48207, USA. ' Data Consulting Group Inc., 965 Jefferson, Detroit, Michigan, 48207, USA. ' Data Consulting Group Inc., 965 Jefferson, Detroit, Michigan, 48207, USA. ' Data Consulting Group Inc., 965 Jefferson, Detroit, Michigan, 48207, USA. ' Data Consulting Group Inc., 965 Jefferson, Detroit, Michigan, 48207, USA. ' Data Consulting Group Inc., 965 Jefferson, Detroit, Michigan, 48207, USA. ' Data Consulting Group Inc., 965 Jefferson, Detroit, Michigan, 48207, USA USHIK United States Health Information Knowledgebase USA AHRQ Agency for Healthcare Research and Quality 11179 metadata registry healthcare standards healthcare measures quality measures harmonisation meaningful use patient safety HITSP healthcare technology information technology informatics healthcare metadata healthcare data sets. 2011-05-21T23:20:50-05:00 3 4 292 313 2011-05-21T23:20:50-05:00 http://www.inderscience.com/link.php?id=40213 We report the development and implementation of a methodology for standardising clinical data elements. The methodology, piloted using Tuberculosis (TB) and Acute Coronary Syndromes (ACS) domains, relies on clinicians for natural language definitions and on informaticists for computable specifications. Data elements are represented using the ISO 11179 standard, UML class, and activity diagrams. Over 2000 candidate data elements were compiled for each domain. Initial sets of 21 data elements for ACS and 139 for TB, plus 300 valid values, were standardised and made publicly available. The methodology is now used in HL7 for data element definition in other clinical areas. Standardising clinical data elements
Meredith Nahm, Anita Walden, Brian McCourt, Karen Pieper, Emily Honeycutt, Carol D. Hamilton, Robert A. Harrington, Jane Diefenbach, Bron Kisler, Mead Walker, W. Ed Hammond
International Journal of Functional Informatics and Personalised Medicine, Vol. 3, No. 4 (2010) pp. 314 - 341
We report the development and implementation of a methodology for standardising clinical data elements. The methodology, piloted using Tuberculosis (TB) and Acute Coronary Syndromes (ACS) domains, relies on clinicians for natural language definitions and on informaticists for computable specifications. Data elements are represented using the ISO 11179 standard, UML class, and activity diagrams. Over 2000 candidate data elements were compiled for each domain. Initial sets of 21 data elements for ACS and 139 for TB, plus 300 valid values, were standardised and made publicly available. The methodology is now used in HL7 for data element definition in other clinical areas.

]]> 10.1504/IJFIPM.2010.040213 International Journal of Functional Informatics and Personalised Medicine, Vol. 3, No. 4 (2010) pp. 314 - 341 Meredith Nahm Anita Walden Brian McCourt Karen Pieper Emily Honeycutt Carol D. Hamilton Robert A. Harrington Jane Diefenbach Bron Kisler Mead Walker W. Ed Hammond Clinical Research Informatics, DTMI Biomedical Informatics Core, Duke Translational Medicine Institute, Durham, NC, USA; Academic Programs, Duke Center for Health Informatics, Duke University Medical Center, Durham, NC, USA. ' DTMI Biomedical Informatics Core, Duke Translational Medicine Institute, Duke University Medical Center, Durham, NC, USA. ' Clinical Research Informatics, Duke Clinical Research Institute, Duke University Medical Center, Durham, NC, USA. ' Clinical Trials Statistical Operations, Statistics Group, Duke Clinical Research Institute, Duke University Medical Center, Durham, NC, USA. ' Outcomes Research and Assessment Group, Statistics Group, Duke Clinical Research Institute, Duke University Medical Center, Durham, NC, USA. ' Health and Development Sciences, Family Health International, Durham, NC, USA; Department of Medicine, Duke University Medical Center, Durham, NC, USA. ' Duke Clinical Research Institute, Department of Medicine, Division of Cardiology, Duke University Medical Center, Durham, NC, USA. ' PharmaStat LLC, Arlington, VA, USA. ' Strategic Initiatives, Clinical Data Interchange Standards Consortium, Austin, Texas, USA. ' Patient Safety Work Group, Health Level 7, USA. ' Duke Center for Health Informatics Department of Community and Family Medicine Department of Biomedical Engineering Fuqua School of Business, Duke University, Durham, NC, USA standards EMR clinical definitions interoperability clinical data elements HL7 domain analysis modelling standardisation tuberculosis TB acute coronary syndromes ISO 11179 UML class activity diagrams data element definition. 2011-05-21T23:20:50-05:00 3 4 314 341 2011-05-21T23:20:50-05:00 http://www.inderscience.com/link.php?id=40214 Patient registries are a valuable research tool for understanding disease and can support new therapies. Diverse registry models, sponsors, and data requirements complicate efforts for the standardisation of registry Questions And Answer Sets (QAS). Bottom-up standardisation can be achieved by facilitating the re-use of existing questions through the use of searchable metadata coded using controlled terminologies. This paper describes the Patient Registry Item Specifications and Metadata for Rare Diseases (PRISM) library of registry questions representing a variety of rare diseases. PRISM uses the Dublin Core (DC) and the Systematised Nomenclature of Medicine Clinical Terms (SNOMED CT). The use of SNOMED CT to support retrieval and re-use of Question and Answer Sets for patient registries
Rachel L. Richesson, Denise Shereff, Christine Spisla, Narciso Albarracin, Debra Konicek, James E. Andrews
International Journal of Functional Informatics and Personalised Medicine, Vol. 3, No. 4 (2010) pp. 342 - 365
Patient registries are a valuable research tool for understanding disease and can support new therapies. Diverse registry models, sponsors, and data requirements complicate efforts for the standardisation of registry Questions And Answer Sets (QAS). Bottom-up standardisation can be achieved by facilitating the re-use of existing questions through the use of searchable metadata coded using controlled terminologies. This paper describes the Patient Registry Item Specifications and Metadata for Rare Diseases (PRISM) library of registry questions representing a variety of rare diseases. PRISM uses the Dublin Core (DC) and the Systematised Nomenclature of Medicine Clinical Terms (SNOMED CT).

]]> 10.1504/IJFIPM.2010.040214 International Journal of Functional Informatics and Personalised Medicine, Vol. 3, No. 4 (2010) pp. 342 - 365 Rachel L. Richesson Denise Shereff Christine Spisla Narciso Albarracin Debra Konicek James E. Andrews University of South Florida College of Medicine, 3650 Spectrum Blvd. Suite 100, Tampa, FL 33612, USA. ' University of South Florida College of Medicine, 3650 Spectrum Blvd. Suite 100, Tampa, FL 33612, USA. ' STS Division (formerly SNOMED Terminology Solutions), College of American Pathologists, 500 Lake Cook Road, Suite 550, Deerfield, Illinois 60015, USA. ' ONTOADAPTIVE, LLC, 1016 W. Jackson Blvd., Chicago, IL 60607, USA. ' STS Division (formerly SNOMED Terminology Solutions), College of American Pathologists, 500 Lake Cook Road, Suite 550, Deerfield, Illinois 60015, USA. ' School of Information, University of South Florida, Tampa, Florida, USA metadata clinical research questions registry QAS question and answer sets library standards rare diseases Dublin Core SNOMED CT controlled vocabularies controlled terminologies encoding indexing patient registries PAG patient advocacy groups health advocacy organisations standardisation clinical terms QAS retrieval QAS re-use. 2011-05-21T23:20:50-05:00 3 4 342 365 2011-05-21T23:20:50-05:00