Table 2 |
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CDS infrastructure needs and available resources |
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Infrastructure Need |
Available Resources |
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Centrally managed repositories of computer-processable medical knowledge |
Initiatives that can serve as models for creating authoritative knowledge on how genomic interventions should be used in clinical practice (e.g., U.S. Preventive Services Task Force [44], U.S. Evaluation of Genomic Applications in Practice and Prevention initiative [45]) |
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Centrally managed repositories of structured experimental data relevant to genomic medicine (e.g., PharmGKB for pharmacogenetic and pharmacogenomic experimental data and curated knowledge [46]; NCBI dbGaP for data from studies evaluating the interaction between genotypes and phenotypes [47]; and NCBI GEO for high-throughput, experimental genomic data [48]) |
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Various formalisms for representing medical knowledge in a computer-processable format [49,50] (e.g., Arden Syntax [42], GELLO [41], GLIF [52], PROforma [53], SAGE [54], SEBASTIAN [55]) |
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Large-scale efforts at managing computer-processable medical knowledge (Intermountain Healthcare [56], Partners HealthCare [57]) |
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Standardization of CDS information provided for specific aspects of genomic medicine |
Standard mechanisms for defining CDS information to be provided in specified contexts (e.g., HL7 refined message information models [49], openEHR Archetypes [58], HL7 Decision Support Service semantic profiles [59]) |
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Standardized representation of patient data |
Standardized information models and terminologies for both genomic and traditional patient data [49,60] (e.g., HL7 data standards, including HL7 Clinical Genomics data standards [60] and emerging HL7 virtual medical record standard [62]; openEHR Archetypes [58]; SNOMED CT [38]; LOINC [39]; BSML [60]; MAGE-ML [63]; National Cancer Institute/caBIG Common Data Elements [61]) |
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Resources that enable mapping between different terminologies (e.g., Unified Medical Language System [65], National Cancer Institute Enterprise Vocabulary Services [66], HL7 Common Terminology Services standard [67]) |
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Standard approaches for leveraging computer-processable medical knowledge |
Various approaches for using computer-processable medical knowledge resources to provide automated CDS [31] (e.g., Arden Syntax [42], SAGE [54], PRODIGY [68], GLIF [69], SEBASTIAN [55], First DataBank Drug Information Framework [70], HL7 Decision Support Service [59]) |
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Standard approach for locating and retrieving patient data |
Standardized approaches for resolving patient identities across systems (e.g., HL7 Entity Identification Service draft standard [72] and corresponding OMG technical specification [73]) and for locating and retrieving patient data across systems (e.g., HL7 Retrieve, Locate, and Update Service draft standard [74] and corresponding OMG technical specification [75]) |
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Regional and national initiatives for secure health data exchange (e.g., U.K. National Health Service Connecting for Health [76], U.S. Nationwide Health Information Network prototypes [77], caBIG [78], Indiana Health Information Exchange [79]) |
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All infrastructure components |
Initiatives to share machine-processable medical knowledge (e.g., Morningside Initiative [80], U.S. federal CDS Collabatory [81]) |
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Efforts at specifying functional requirements of EHR systems (e.g., HL7 EHR System Functional Model standard [82], CCHIT EHR certification criteria [83]) |
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Efforts at coordinating the use of available health information technology standards (e.g., U.S. Health Information Technology Standards Panel [84], Integrating the Healthcare Enterprise [85]) |
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BSML = Bioinformatic Sequence Markup Language; caBIG = cancer Biomedical Informatics Grid; CCHIT = Certification Commission for Healthcare Information Technology; dbGaP = database of Genotype and Phenotype; EHR = electronic health record; GEO = Gene Expression Omnibus; GLIF = Guideline Interchange Format; HL7 = Health Level 7; LOINC = Logical Observation Identifiers Names and Codes; MAGE-ML = microarray and gene expression markup language; NCBI = National Center for Biotechnology Information; OMG = Object Management Group; PharmGKB = Pharmacogenetics and Pharmacogenomics Knowledge Base; PRODIGY = Prescribing RatiOnally with Decision-support In General-practice studY; SAGE = Standards-Based Active Guideline Environment; SEBASTIAN = System for Evidence Based Advice through Simultaneous Transaction with an Intelligent Agent across a Network; SNOMED CT = Systematized Nomenclature of Medicine, Clinical Terms |
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Kawamoto et al. BMC Medical Informatics and Decision Making 2009 9:17 doi:10.1186/1472-6947-9-17 |
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