Clinical laboratory utilization management and improved healthcare performance

References

• McDonald JM, Smith JA. Value-added laboratory medicine in an era of managed care. Clin Chem. 1995;41:1256–1262.
   PubMed Web of Science ®Google Scholar
• Beastall GH. Adding value to laboratory medicine: a professional responsibility. Clin Chem Lab Med. 2013;51:221–227.
   PubMed Web of Science ®Google Scholar
• Olsen K. The first 110 years of laboratory automation. J Lab Autom. 2012;17:469–480.
   PubMedGoogle Scholar
• Gibbon GA. A brief history of LIMS. Lab Autom Inf Manag. 1996;32:1–5. DOI:10.1016/1381-141X(95)00024-K
   Google Scholar
• Komorowski M. A history of storage cost (update). 2014 [cited 2018 Dec 7]. Available from: http://www.mkomo.com/cost-per-gigabyte
   Google Scholar
• Naugler C. A perspective on laboratory utilization management from Canada. Clin Chim Acta. 2014;427:142–144.
   PubMed Web of Science ®Google Scholar
• Plebani M, Zaninotto M, Faggian D. Utilization management: a European perspective. Clin Chim Acta. 2014;427:137–141.
   PubMed Web of Science ®Google Scholar
• Huck A, Lewandrowski K. Utilization management in the clinical laboratory: an introduction and overview of the literature. Clin Chim Acta. 2014;427:111–117.
   PubMed Web of Science ®Google Scholar
• Hoffman JR, Cooper RJ. Overdiagnosis of disease: a modern epidemic. Arch Intern Med. 2012;172:1123–1124.
   PubMedGoogle Scholar
• Berwick DM, Hackbarth AD. Eliminating waste in US health care. JAMA. 2012;307:1513–1516.
   PubMed Web of Science ®Google Scholar
• Grady D, Redberg RF. Less is more: how less health care can result in better health. Arch Intern Med. 2010;170:749–750.
   PubMed Web of Science ®Google Scholar
• WHO Regional Office for Europe. Appropriateness in health care services: report on a WHO workshop, Koblenz, Germany 23-25 March 2000. Copenhagen; 2000.
   Google Scholar
• Jenniskens K, de Groot JAH, Reitsma JB, et al. Overdiagnosis across medical disciplines: a scoping review. BMJ Open. 2017;7:e018448.
   PubMed Web of Science ®Google Scholar
• Thomas RE, Vaska M, Naugler C, et al. Interventions to educate family physicians to change test ordering: systematic review of randomized controlled trials. Acad Pathol. 2016;3:237428951663347.
   Web of Science ®Google Scholar
• Thomas RE, Vaska M, Naugler C, et al. Interventions at the laboratory level to reduce laboratory test ordering by family physicians: systematic review. Clin Biochem. 2015;48:1358–1365.
   PubMed Web of Science ®Google Scholar
• Naugler C, Thomas R, Turin TC, et al. Yearly clinical laboratory test expenditures for different medical specialties in a major Canadian city. Am J Clin Pathol. 2015;144:97–102.
   PubMed Web of Science ®Google Scholar
• Barber J, Guo M, Nguyen LT, et al. Sociodemographic correlates of clinical laboratory test expenditures in a major Canadian city. Am J Clin Pathol. 2017;148:91–96.
   PubMed Web of Science ®Google Scholar
• Hauser RG, Shirts BH. Do we now know what inappropriate laboratory utilization is? Am J Clin Pathol. 2014;141:774–783.
   PubMed Web of Science ®Google Scholar
• van Walraven C, Naylor CD. Do we know what inappropriate laboratory utilization is? A systematic review of laboratory clinical audits. JAMA. 1998;280:550–558.
   PubMed Web of Science ®Google Scholar
• Morgen EK, Naugler C. Inappropriate repeats of six common tests in a Canadian city: a population cohort study within a laboratory informatics framework. Am J Clin Pathol. 2015;144:704–712.
   PubMedGoogle Scholar
• Naugler CT, Guo M. Mean abnormal result rate: proof of concept of a new metric for benchmarking selectivity in laboratory test ordering. Am J Clin Pathol. 2016;145:568–573.
   PubMed Web of Science ®Google Scholar
• Corallo AN, Croxford R, Goodman DC, et al. A systematic review of medical practice variation in OECD countries. Health Policy. 2014;114:5–14.
   PubMed Web of Science ®Google Scholar
• Brack AP, Guo M, Ma I, et al. Use of the Mean Abnormal Result Rate (MARR) to gauge changes in family physicians’ selectivity of laboratory test ordering, 2010-2015. Am J Clin Pathol. 2017;148:436–440.
   PubMed Web of Science ®Google Scholar
• Naugler C, Ma I. More than half of abnormal results from laboratory tests ordered by family physicians could be false-positive. Can Fam Physician. 2018;64:202–203.
   PubMed Web of Science ®Google Scholar
• Mohammed EA, Naugler C. Open-source software for demand forecasting of clinical laboratory test volumes using time-series analysis. J Pathol Inform. 2017;8:7.
   PubMedGoogle Scholar
• Naugler C, Hemmelgarn B, Quan H, et al. Implementation of an intervention to reduce population-based screening for vitamin D deficiency: a cross-sectional study. C Open. 2017;5:E36–E39.
   PubMedGoogle Scholar
• Ma I, Guo M, Viczko J, et al. Evaluation of a provincial intervention to reduce redundant hemoglobin A1c testing. Clin Biochem. 2017;50:1253–1255.
   PubMed Web of Science ®Google Scholar
• Chen R, Snyder M. Promise of personalized omics to precision medicine. Wires Syst Biol Med. 2013;5:73–82.
   PubMed Web of Science ®Google Scholar
• Plebani M, Lippi G. Personalized (laboratory) medicine: a bridge to the future. Clin Chem Lab Med. 2013;51:703–706.
   PubMed Web of Science ®Google Scholar
• Ahmed MU, Saaem I, Wu PC, et al. Personalized diagnostics and biosensors: a review of the biology and technology needed for personalized medicine. Crit Rev Biotechnol. 2014;34:180–196.
   PubMed Web of Science ®Google Scholar
• Davey JW, Hohenlohe PA, Etter PD, et al. Genome-wide genetic marker discovery and genotyping using next-generation sequencing. Nat Rev Genet. 2011;12:499–510.
   PubMed Web of Science ®Google Scholar
• Goretti E, Wagner DR, Devaux Y. miRNAs as biomarkers of myocardial infarction: a step forward towards personalized medicine? Trends Mol Med. 2014;20:716–725.
   PubMed Web of Science ®Google Scholar
• Lin S-Y, Hsu W-H, Lin C-C, et al. Mass spectrometry-based proteomics in chest medicine, gerontology, and nephrology: subgroups omics for personalized medicine. BioMedicine. 2014;4:25.
   PubMedGoogle Scholar
• Meade C, Bonhomme NF. Newborn screening: adapting to advancements in whole-genome sequencing. Genet Test Mol Biomarkers. 2014;18:597–598.
   PubMed Web of Science ®Google Scholar
• Kostrzewa M. Application of the MALDI Biotyper to clinical microbiology: progress and potential. Expert Rev Proteomics. 2018;15:193–202.
   PubMed Web of Science ®Google Scholar
• Yao Q, Xu Y, Yang H, et al. Global prioritization of disease candidate metabolites based on a multi-omics composite network. Sci Rep. 2015;5:17201.
   PubMed Web of Science ®Google Scholar
• Johnson CH, Ivanisevic J, Siuzdak G. Metabolomics: beyond biomarkers and towards mechanisms. Nat Rev Mol Cell Biol. 2016;17:451–459.
   PubMed Web of Science ®Google Scholar
• Cui L, Lu H, Lee YH. Challenges and emergent solutions for LC-MS/MS based untargeted metabolomics in diseases. Mass Spectrom Rev. 2018:37:772–792.
   PubMed Web of Science ®Google Scholar
• Li S, Todor A, Luo R. Blood transcriptomics and metabolomics for personalized medicine. Comput Struct Biotechnol J. 2016;14:1–7.
   PubMed Web of Science ®Google Scholar
• Chen R, Mias GI, Li-Pook-Than J, et al. Personal omics profiling reveals dynamic molecular and medical phenotypes. Cell. 2012;148:1293–1307.
   PubMed Web of Science ®Google Scholar
• Meyer UA, Zanger UM, Schwab M. Omics and drug response. Annu Rev Pharmacol Toxicol. 2013;53:475–502.
   PubMed Web of Science ®Google Scholar
• Tebani A, Afonso C, Marret S, et al. Omics-based strategies in precision medicine: toward a paradigm shift in inborn errors of metabolism investigations. Ijms. 2016;17:1555.
   Google Scholar
• Malentacchi F, Mancini I, Brandslund I, et al. Is laboratory medicine ready for the era of personalized medicine? A survey addressed to laboratory directors of hospitals/academic schools of medicine in Europe. Drug Metab Pers Ther. 2015;30:121–128.
   PubMedGoogle Scholar
• Abbott M, Paulin H, Sidhu D, et al. Laboratory tests, interpretation, and use of resources: a program to introduce the basics. Can Fam Physician. 2014;60:e167–e172.
   PubMed Web of Science ®Google Scholar
• Ogino S, Nishihara R, VanderWeele TJ, et al. Review article. Epidemiology. 2016;27:602–611.
   PubMed Web of Science ®Google Scholar
• Churko JM, Mantalas GL, Snyder MP, et al. Overview of high throughput sequencing technologies to elucidate molecular pathways in cardiovascular diseases. Circ Res. 2013;112:1613–1623.
   PubMed Web of Science ®Google Scholar
• Nikiforova MN, Wald AI, Melan MA, et al. Targeted next-generation sequencing panel (GlioSeq) provides comprehensive genetic profiling of central nervous system tumors. Neuro Oncol. 2016;18:379–387.
   PubMed Web of Science ®Google Scholar
• Bisschop C, ter Elst A, Bosman LJ, et al. Rapid BRAF mutation tests in patients with advanced melanoma. Melanoma Res. 2017;28:1.
   Google Scholar
• Metzker ML. Sequencing technologies – the next generation. Nat Rev Genet. 2010;11:31–46.
   PubMed Web of Science ®Google Scholar
• Liu L, Li Y, Li S, et al. Comparison of next-generation sequencing systems. J Biomed Biotechnol. 2012;2012:251364.
   Google Scholar
• Head SR, Komori HK, LaMere SA, et al. Library construction for next-generation sequencing: overviews and challenges. Biotechniques. 2014;56:61–64.
   PubMed Web of Science ®Google Scholar
• Levy SE, Myers RM. Advancements in next-generation sequencing. Annu Rev Genomics Hum Genet. 2016;17:95–115.
   PubMed Web of Science ®Google Scholar
• Alekseyev YO, Fazeli R, Yang S, et al. A next-generation sequencing primer-how does it work and what can it do? Acad Pathol. 2018;5:237428951876652.
   Web of Science ®Google Scholar
• Collins FS, Morgan M, Patrinos A. The human genome project: lessons from large-scale biology. Science. 2003;300:286–290.
   PubMed Web of Science ®Google Scholar
• 1000 Genomes Project Consortium, Abecasis GR, Auton A, Brooks LD, et al. An integrated map of genetic variation from 1,092 human genomes. Nature. 2012;491:56–65.
   PubMed Web of Science ®Google Scholar
• Serratì S, De Summa S, Pilato B, et al. Next-generation sequencing: advances and applications in cancer diagnosis. Onco Targets Ther. 2016;9:7355–7365.
   PubMed Web of Science ®Google Scholar
• Kamps R, Brandão R, Bosch B, et al. Next-generation sequencing in oncology: genetic diagnosis, risk prediction and cancer classification. Ijms. 2017;18:308.
   Google Scholar
• Lianos GD, Glantzounis GK, Bali CD, et al. Identification of novel genes by whole-exome sequencing can improve gastric cancer precision oncology. Futur Oncol. 2017;13:883–892.
   PubMed Web of Science ®Google Scholar
• Xie B, Yuan Z, Yang Y, et al. MOBCdb: a comprehensive database integrating multi-omics data on breast cancer for precision medicine. Breast Cancer Res Treat. 2018;169:625–632.
   PubMed Web of Science ®Google Scholar
• Rehm HL, Bale SJ, Bayrak-Toydemir P, et al. ACMG clinical laboratory standards for next-generation sequencing. Genet Med. 2013;15:733–747.
   PubMed Web of Science ®Google Scholar
• Xuan J, Yu Y, Qing T, et al. Next-generation sequencing in the clinic: promises and challenges. Cancer Lett. 2013;340:284–295.
   PubMed Web of Science ®Google Scholar
• Matthijs G, Souche E, Alders M, et al. Guidelines for diagnostic next-generation sequencing. Eur J Hum Genet. 2016;24:2–5.
   PubMed Web of Science ®Google Scholar
• Roy S, LaFramboise WA, Nikiforov YE, et al. Next-generation sequencing informatics: challenges and strategies for implementation in a clinical environment. Arch Pathol Lab Med. 2016;140:958–975.
   PubMed Web of Science ®Google Scholar
• Gargis AS, Kalman L, Lubin IM. Assuring the quality of next-generation sequencing in clinical microbiology and public health laboratories. Kraft CS, editor. J Clin Microbiol. 2016;54:2857–2865.
   PubMed Web of Science ®Google Scholar
• Pant S, Weiner R, Marton MJ. Navigating the rapids: the development of regulated next-generation sequencing-based clinical trial assays and companion diagnostics. Front Oncol. 2014;4:78.
   PubMedGoogle Scholar
• Kim J, Park W-Y, Kim NKD, et al. Good laboratory standards for clinical next-generation sequencing cancer panel tests. J Pathol Transl Med. 2017;51:191–204.
   PubMed Web of Science ®Google Scholar
• Kirschner MMJ, Schemionek M, Schubert C, et al. Dissecting genomic aberrations in myeloproliferative neoplasms by multiplex-PCR and next generation sequencing. Mills K, editor. PLoS One. 2015;10:e0123476.
   PubMed Web of Science ®Google Scholar
• Theunissen TEJ, Sallevelt SCEH, Hellebrekers DMEI, et al. Rapid resolution of blended or composite multigenic disease in infants by whole-exome sequencing. J Pediatr. 2017;182:371–374.e2.
   PubMed Web of Science ®Google Scholar
• Daoud H, Luco SM, Li R, et al. Next-generation sequencing for diagnosis of rare diseases in the neonatal intensive care unit. Cmaj. 2016;188:E254–E260.
   PubMed Web of Science ®Google Scholar
• Sun J, Zhu K, Zheng W, et al. A comparative study of disease genes and drug targets in the human protein interactome. BMC Bioinformatics. 2015;16:S1.
   PubMed Web of Science ®Google Scholar
• Kamel-Reid S, Chong G, Ionescu DN, et al. EGFR tyrosine kinase mutation testing in the treatment of non-small-cell lung cancer. Curr Oncol. 2012;19:e67–e74.
   PubMed Web of Science ®Google Scholar
• Costa-Cabral S, Brough R, Konde A, et al. CDK1 is a synthetic lethal target for KRAS mutant tumours. Sobol RW, editor. PLoS One. 2016;11:e0149099.
   PubMed Web of Science ®Google Scholar
• Román M, Baraibar I, López I, et al. KRAS oncogene in non-small cell lung cancer: clinical perspectives on the treatment of an old target. Mol Cancer. 2018;17:33.
   PubMed Web of Science ®Google Scholar
• Chappell L, Russell AJC, Voet T. Single-cell (multi)omics technologies. Annu Rev Genomics Hum Genet. 2018;19:15–41.
   PubMed Web of Science ®Google Scholar
• Cheok MH, Pottier N, Kager L, et al. Pharmacogenetics in acute lymphoblastic leukemia. Semin Hematol. 2009;46:39–51.
   PubMed Web of Science ®Google Scholar
• Johnson JA. Pharmacogenetics in clinical practice: how far have we come and where are we going? Pharmacogenomics. 2013;14:835–843.
   PubMed Web of Science ®Google Scholar
• Sawyer SL, Hartley T, Dyment DA, et al. Utility of whole-exome sequencing for those near the end of the diagnostic odyssey: time to address gaps in care. Clin Genet. 2016;89:275–284.
   PubMed Web of Science ®Google Scholar
• Lefterova MI, Suarez CJ, Banaei N, et al. Next-generation sequencing for infectious disease diagnosis and management. J Mol Diagnostics. 2015;17:623–634.
   PubMed Web of Science ®Google Scholar
• Deurenberg RH, Bathoorn E, Chlebowicz MA, et al. Application of next generation sequencing in clinical microbiology and infection prevention. J Biotechnol. 2017;243:16–24.
   PubMed Web of Science ®Google Scholar
• Sibley CD, Church DL, Surette MG, et al. Pyrosequencing reveals the complex polymicrobial nature of invasive pyogenic infections: microbial constituents of empyema, liver abscess, and intracerebral abscess. Eur J Clin Microbiol Infect Dis. 2012;31:2679–2691.
   PubMed Web of Science ®Google Scholar
• Wilson MR, Naccache SN, Samayoa E, et al. Actionable diagnosis of neuroleptospirosis by next-generation sequencing. N Engl J Med. 2014;370:2408–2417.
   PubMed Web of Science ®Google Scholar
• Chen L, Peirano G, Lynch T, et al. Molecular characterization by using next-generation sequencing of plasmids containing bla NDM-7 in Enterobacteriaceae from Calgary, Canada. Antimicrob Agents Chemother. 2016;60:1258–1263.
   Web of Science ®Google Scholar
• Lynch T, Chen L, Peirano G, et al. Molecular evolution of a Klebsiella pneumoniae ST278 isolate harboring blaNDM-7 and involved in nosocomial transmission. J Infect Dis. 2016;214:798–806.
   PubMed Web of Science ®Google Scholar
• Rasko DA, Webster DR, Sahl JW, et al. Origins of the E. coli strain causing an outbreak of hemolytic-uremic syndrome in Germany. N Engl J Med. 2011;365:709–717.
   PubMed Web of Science ®Google Scholar
• Peterson J, Garges S, Giovanni M, NIH HMP Working Group J, et al. The NIH human microbiome project. Genome Res. 2009;19:2317–2323.
   PubMed Web of Science ®Google Scholar
• van Nood E, Vrieze A, Nieuwdorp M, et al. Duodenal infusion of donor feces for recurrent Clostridium difficile. N Engl J Med. 2013;368:407–415.
   PubMed Web of Science ®Google Scholar
• Chang JY, Antonopoulos DA, Kalra A, et al. Decreased diversity of the fecal microbiome in recurrent Clostridium difficile-associated diarrhea. J Infect Dis. 2008;197:435–438.
   PubMed Web of Science ®Google Scholar
• Coughlin SS. Toward a road map for global -omics: a primer on -omic technologies. Am J Epidemiol. 2014;180:1188–1195.
   PubMed Web of Science ®Google Scholar
• Zhou L, Wang K, Li Q, et al. Clinical proteomics-driven precision medicine for targeted cancer therapy: current overview and future perspectives. Expert Rev Proteomics. 2016;13:367–381.
   PubMed Web of Science ®Google Scholar
• Jean Beltran PM, Federspiel JD, Sheng X, et al. Proteomics and integrative omic approaches for understanding host–pathogen interactions and infectious diseases. Mol Syst Biol. 2017;13:922.
   PubMed Web of Science ®Google Scholar
• Seng P, Drancourt M, Gouriet F, et al. Ongoing revolution in bacteriology: routine identification of bacteria by matrix‐assisted laser desorption ionization time‐of‐flight mass spectrometry. Clin Infect Dis. 2009;49:543–551.
   PubMed Web of Science ®Google Scholar
• Kostrzewa M, Nagy E. How MALDI-TOF mass spectrometry can aid diagnosis of hard-to-identify pathogenic bacteria. Expert Rev Mol Diagn. 2016;16:509–511.
   PubMed Web of Science ®Google Scholar
• Verroken A, Defourny L, le Polain de Waroux O, et al. Clinical impact of MALDI-TOF MS identification and rapid susceptibility testing on adequate antimicrobial treatment in sepsis with positive blood cultures. Rottman M, editor. PLoS One. 2016;11:e0156299.
   PubMed Web of Science ®Google Scholar
• Schubert S, Kostrzewa M. MALDI-TOF MS in the microbiology laboratory: current trends. Curr Issues Mol Biol. 2017;23:17–20.
   PubMed Web of Science ®Google Scholar
• Theparee T, Das S, Thomson RB. Total laboratory automation and matrix-assisted laser desorption ionization-time of flight mass spectrometry improve turnaround times in the clinical microbiology laboratory: a retrospective analysis. Patel R, editor. J Clin Microbiol. 2018;56:e01242–e01217.
   PubMed Web of Science ®Google Scholar
• Tebani A, Abily-Donval L, Afonso C, et al. Clinical metabolomics: the new metabolic window for inborn errors of metabolism investigations in the post-genomic era. Ijms. 2016;17:1167.
   Google Scholar
• Wishart DS. Advances in metabolite identification. Bioanalysis. 2011;3:1769–1782.
   PubMed Web of Science ®Google Scholar
• Wang Z, Gerstein M, Snyder M. RNA-Seq: a revolutionary tool for transcriptomics. Nat Rev Genet. 2009;10:57–63.
   PubMed Web of Science ®Google Scholar
• Barzon L, Lavezzo E, Militello V, et al. Applications of next-generation sequencing technologies to diagnostic virology. Int J Mol Sci. 2011;12:7861–7884.
   PubMed Web of Science ®Google Scholar
• Torres M, Fraile L, Echevarria J, et al. Human papillomavirus (HPV) genotyping: automation and application in routine laboratory testing. Open Virol J. 2012;6:144–150.
   PubMedGoogle Scholar
• Brown JR, Roy S, Ruis C, et al. Norovirus whole-genome sequencing by sure select target enrichment: a robust and sensitive method. Tang Y-W, editor. J Clin Microbiol. 2016;54:2530–2537.
   PubMed Web of Science ®Google Scholar
• Thomson E, Ip CLC, Badhan A, et al. Comparison of next-generation sequencing technologies for comprehensive assessment of full-length hepatitis C viral genomes. J Clin Microbiol. 2016;54:2470–2484.
   PubMed Web of Science ®Google Scholar
• Durski KN, Singaravelu S, Teo J, et al. Development, use, and impact of a global laboratory database during the 2014 ebola outbreak in West Africa. J Infect Dis. 2017;215:1799–1806.
   PubMed Web of Science ®Google Scholar
• Vaught J. Biobanking comes of age: the transition to biospecimen science. Annu Rev Pharmacol Toxicol. 2016;56:211–228.
   PubMed Web of Science ®Google Scholar
• Shea KE, Wagner EL, Marchesani L, et al. Efficiently maintaining a national resource of historical and contemporary biological collections: the NHLBI biorepository model. Biopreserv Biobank. 2017;15:17–19.
   PubMed Web of Science ®Google Scholar
• Paskal W, Paskal AM, Dębski T, et al. Aspects of modern biobank activity – comprehensive review. Pathol Oncol Res. 2018;24:771–785.
   PubMed Web of Science ®Google Scholar
• Caixeiro NJ, Byun HL, Descallar J, et al. Health professionals’ opinions on supporting a cancer biobank: identification of barriers to combat biobanking pitfalls. Eur J Hum Genet. 2016;24:626–632.
   PubMed Web of Science ®Google Scholar
• Andry C, Duffy E, Moskaluk CA, et al. Biobanking-budgets and the role of pathology biobanks in precision medicine. Acad Pathol. 2017;4:237428951770292.
   Web of Science ®Google Scholar
• Ellis H, Joshi M-B, Lynn AJ, et al. Consensus-driven development of a terminology for biobanking, the duke experience. Biopreserv Biobank. 2017;15:126–133.
   PubMed Web of Science ®Google Scholar
• Vaught J. Developments in biospecimen research. Br Med Bull. 2015;114:29–38.
   PubMed Web of Science ®Google Scholar
• Felmeister AS, Masino AJ, Rivera TJ, et al. The biorepository portal toolkit: an honest brokered, modular service oriented software tool set for biospecimen-driven translational research. BMC Genomics. 2016;17:434.
   PubMed Web of Science ®Google Scholar
• Ellervik C, Vaught J. Preanalytical variables affecting the integrity of human biospecimens in biobanking. Clin Chem. 2015;61:914–934.
   PubMed Web of Science ®Google Scholar
• Lee J-E, Kim Y-Y. Impact of preanalytical variations in blood-derived biospecimens on omics studies: toward precision biobanking? Omi A J Integr Biol. 2017;21:499–508.
   Web of Science ®Google Scholar
• Broes S, Lacombe D, Verlinden M, et al. Toward a tiered model to share clinical trial data and samples in precision oncology. Front Med. 2018;5:6.
   Web of Science ®Google Scholar
• N.C.I. NCI Best Practices for Biospecimen Resources [Internet]. 2016. Available from: https://biospecimens.cancer.gov/bestpractices/2016-NCIBestPractices.pdf
   Google Scholar
• Ostrom QT, Devine K, Fulop J, et al. Brain tumor biobanking in the precision medicine era: building a high-quality resource for translational research in neuro-oncology. Neuro-Oncology Pract. 2017;4:220–228.
   PubMed Web of Science ®Google Scholar
• Collins R. What makes UK Biobank special? Lancet. 2012;379:1173–1174.
   PubMed Web of Science ®Google Scholar
• Trehearne A. Genetics, lifestyle and environment. UK Biobank is an open access resource following the lives of 500,000 participants to improve the health of future generations. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz. 2016;59:361–367.
   PubMed Web of Science ®Google Scholar
• Crosslin DR, Tromp G, Burt A, et al. Controlling for population structure and genotyping platform bias in the eMERGE multi-institutional biobank linked to electronic health records. Front Genet. 2014;5:352.
   PubMed Web of Science ®Google Scholar
• Naugler C, Zhang J, Henne D, et al. Association of vitamin D status with socio-demographic factors in Calgary, Alberta: an ecological study using Census Canada data. BMC Public Health. 2013;13:316.
   PubMed Web of Science ®Google Scholar
• Ngo JT, Parkins MD, Gregson DB, et al. Population-based assessment of the incidence, risk factors, and outcomes of anaerobic bloodstream infections. Infection. 2013;41:41–48.
   PubMed Web of Science ®Google Scholar
• de Koning L, Henne D, Woods P, et al. Sociodemographic correlates of 25-hydroxyvitamin D test utilization in Calgary, Alberta. BMC Health Serv Res. 2014;14:339.
   PubMed Web of Science ®Google Scholar
• McBrien KA, Manns BJ, Hemmelgarn BR, et al. The association between sociodemographic and clinical characteristics and poor glycaemic control: a longitudinal cohort study. Diabet Med. 2016;33:1499–1507.
   PubMed Web of Science ®Google Scholar
• Shysh AC, Nguyen LT, Guo M, et al. The incidence of acute myeloid leukemia in Calgary, Alberta, Canada: a retrospective cohort study. BMC Public Health. 2018;18:94.
   Web of Science ®Google Scholar
• Somayaji R, Naugler C, Guo M, et al. Examining sociodemographic risk factors for Chlamydia trachomatis infection: a population-based cohort study. Future Microbiol. 2017;12:1363–1370.
   PubMed Web of Science ®Google Scholar
• Griener TP, Naugler C, Chan WW, et al. Sociodemographic correlates of urine culture test utilization in Calgary, Alberta. BMC Urol. 2018;18:2.
   PubMed Web of Science ®Google Scholar
• Ugarte-Torres A, Gillrie MR, Griener TP, et al. Eggerthella lenta bloodstream infections are associated with increased mortality following empiric Piperacillin-Tazobactam (TZP) monotherapy: a population-based cohort study. Clin Infect Dis. 2018;67:221–228.
   PubMed Web of Science ®Google Scholar
• Manca C, Hill C, Hujer AM, et al. Leading antibacterial laboratory research by integrating conventional and innovative approaches: the laboratory center of the antibacterial resistance leadership group. Clin Infect Dis. 2017;64:S13–S17.
   PubMed Web of Science ®Google Scholar
• Naugler C. Estrogen receptor testing and 10-year mortality from breast cancer: a model for determining testing strategy. J Pathol Inform. 2012;3:19.
   PubMedGoogle Scholar
• Hamada T, Keum N, Nishihara R, et al. Molecular pathological epidemiology: new developing frontiers of big data science to study etiologies and pathogenesis. J Gastroenterol. 2017;52:265–275.
   PubMed Web of Science ®Google Scholar
• Higgins MW. The Framingham Heart Study: review of epidemiological design and data, limitations and prospects. Prog Clin Biol Res. 1984;147:51–64.
   PubMedGoogle Scholar
• Namboodiri KK. Framingham Heart Study: review of genetic data and design, limitations and prospects. Prog Clin Biol Res. 1984;147:65–78.
   PubMedGoogle Scholar
• Ayers LW, Silver S, Orenstein JM, et al. The AIDS and Cancer Specimen Resource. In 2011 [cited 2018 Jun 13]. p. 193–203. Available from: http://link.springer.com/10.1007/978-1-59745-423-0_8
   Google Scholar
• Sarzotti-Kelsoe M, Needham LK, Rountree W, et al. The center for HIV/AIDS vaccine immunology (CHAVI) multi-site quality assurance program for cryopreserved human peripheral blood mononuclear cells. J Immunol Methods. 2014;409:21–30.
   PubMed Web of Science ®Google Scholar
• Schwiebert LM, Estell K, Meadows T, et al. Development and maintenance of a biospecimen repository for clinical samples derived from pulmonary patients. Clin Transl Sci. 2014;7:336–341.
   PubMed Web of Science ®Google Scholar
• Chuong KH, Hwang DM, Tullis DE, et al. Navigating social and ethical challenges of biobanking for human microbiome research. BMC Med Ethics. 2017;18:1.
   PubMed Web of Science ®Google Scholar
• Garratt LW, Kicic A, Robertson C, et al. The AREST CF experience in biobanking - more than just tissues, tubes and time. J Cyst Fibros. 2017;16:622–627.
   PubMed Web of Science ®Google Scholar
• Barnes RO, Shea KE, Watson PH. The Canadian tissue repository network biobank certification and the college of American pathologists biorepository accreditation programs: two strategies for knowledge dissemination in biobanking. Biopreserv Biobank. 2017;15:9–16.
   PubMed Web of Science ®Google Scholar
• Vaught J, Kelly A, Hewitt R. A review of international biobanks and networks: success factors and key benchmarks. Biopreserv Biobank. 2009;7:143–150.
   PubMed Web of Science ®Google Scholar
• Litton J-E. Launch of an infrastructure for health research: BBMRI-ERIC. Biopreserv Biobank. 2018;16:233–241.
   PubMed Web of Science ®Google Scholar
• McCall SJ, Branton PA, Blanc VM, et al. The college of American pathologists biorepository accreditation program: results from the first 5 years. Biopreserv Biobank. 2018;16:16–22.
   PubMed Web of Science ®Google Scholar
• O'Donoghue S, Matzke L, Watson P. ISBER best practice-based education: ISBER-Canadian tissue repository network introduction to biobanking. Biopreserv Biobank. 2018;16:13–15.
   PubMed Web of Science ®Google Scholar