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Table 2 IGNITE network strategies for data collection, distribution and use in patient care

From: The IGNITE network: a model for genomic medicine implementation and research

  University of Florida University of Maryland Indiana University Vanderbilt University Duke University Icahn School of Medicine at Mt. Sinai
Type of Genomic Data Collected Multiple pharmacogenomic variantsa Pathogenic/likely pathogenic variants in monogenic diabetes genes Multiple pharmacogenomic variantsa Multiple germline and somatic pharmacogenomic variantsa Family health history pedigree and personal risk assessment report Test for variants of APOL1 gene that increase kidney failure risk in adults of African ancestry
Sample/Data Collection Methodb Blood or sputum, QuantStudio, Luminex xTAG, GenMark or ViiA 7 Blood, Ion Torrent, Sanger Sequencing Blood or sputum, QuantStudio Blood, Illumina-ADME array; transitioning to QuantStudio for future testing Patient enters data into web-based data collection ool Blood or sputum
TaqMan PCR
Sample/Data Storage and Securityc Clinical data in EHR; research data/samples in biorepository/IDR; secure facilities DNA in secure freezer; data in binary (.BAM) and VCF files, text, spreadsheets, chromatograms, in secure software DNA secured via limited access room and locked freezers; data in secured database and Eskanzi EHR Data stored on individual site servers; Veterans Affairs site data on FISMA compliant server Cloud server/risk assessment report and health pedigree in patient EHR; secured server Clinical data in EHR; secured server
Test Results and/or Data Distribution to Providers or Patientsb Via EHR as lab results and CDS in EHR to providers, and/or secured communication to provider with clinical guidance Clinical consult note in EHR, patient provided custom report, consult note, letters for patient and family members Via EHR for physician; samples available upon request from biobank Identifiable data integratedinto EHR for clinical decision making. Via EHR (provider report); via web-based tool (patient report) Through CDS in EHR to primary care clinicians; in person and in writing to patients
Use of Genomic Information in Process of Care CDS alert and/or PGx consult used to inform drug therapy changes Results may change diagnosis (to MODY or other monogenic diabetes type), treatment plan or follow up frequency Results used to help guide patient care and therapy choices CDS alert at order entry will indicate drug therapy alternative (active CDS) or PGx consultant will send message to provider (passive CDS). Risk assessment report of elevated familial risk based on guidelines for a finite number of conditions and diseases given to providers/patients CDS alerts to providers to help risk stratify hypertension patients; low-literacy materials to patients to guide care choices, activation and adherence
Expected Impact on Clinical Decision Making Optimized drug therapy decision making with incorporation of genetic information in clinical decision making process Potential change in treatment modality Improved therapy decision making as a result of patient-specific genetic information Changes in drug prescribing in individuals with SNPs that indicate lack of efficacy or increased toxicity. Improved FHH in primary care; enhanced adherence to guidelines; promotion of patient-provider communication Increased attention to blood pressure control and renal disease screening for clinicians and patients, improved patient-clinician communication
Potential Benefit to Patient Optimal drug therapy selection for improved efficacy and/or safety and reduced risk of adverse outcomes Optimal, cost effective, glucose control; provision of more accurate diabetes risk assessment and diagnosis Optimal drug therapy selection for improved efficacy and/or safety and reduced risk of adverse outcomes Optimal drug therapy selection for improved efficacy and/or safety and reduced risk of adverse outcomes Education on FHH collection; improved patient-provider communication; improved preventive care/screeningbased on FHH Better quality of care, improved knowledge/health behaviors, lower blood pressure, improved renal surveillance, better health outcomes and quality of life.
  1. CAP College of American Pathologists, CLIA clinical laboratory improvement amendment, EHR electronic health record, HIPAA health insurance portability and accountability act, FISMA Federal Information Security Management Act of 2002, IDR integrated data repository, CDS clinical decision support, PGx pharmacogenetics, FHH family health history, VCF variant calling format
  2. aPharmacogenomic variants tested include germline and/or somatic testing of multiple clinically relevant single nucleotide polymorphisms (e.g., CYP2D6, CYP2C19, TPMT, IL28B [IFNL3], CYP2C9, VKORC1, SLCO1B1, ABCC4, CYP2B6, CYP3A4/5, CYP4F2, DPYD, G6PD, HLA-B, ITPA)
  3. bClinical data/samples are collected, stored and processed according to appropriate clinical compliance and/or security standards (e.g., CAP-CLIA accredited laboratory, HIPAA-compliant server) for all sites
  4. cDe-identified genomic data also deposited into the database of Genotypes and Phenotypes (dbGaP) when appropriate