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Table 2 CDS infrastructure needs and available resources

From: A national clinical decision support infrastructure to enable the widespread and consistent practice of genomic and personalized medicine

Infrastructure Need Available Resources
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])
  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])
  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])
  Large-scale efforts at managing computer-processable medical knowledge (Intermountain Healthcare [56], Partners HealthCare [57])
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])
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])
  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])
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])
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])
  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])
All infrastructure components Initiatives to share machine-processable medical knowledge (e.g., Morningside Initiative [80], U.S. federal CDS Collabatory [81])
  Efforts at specifying functional requirements of EHR systems (e.g., HL7 EHR System Functional Model standard [82], CCHIT EHR certification criteria [83])
  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])
  1. 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