Biobanks and electronic medical records: Enabling cost-effective research

Science Translational Medicine

Volumn 6, Issue 234, 2014, Pages

  Bowton, Erica ^a   Field, Julie R ^a   Wang, Sunny ^a   Schildcrout, Jonathan S ^b   Van Driest, Sara L ^a   Delaney, Jessica T ^a   Cowan, James ^a   Weeke, Peter ^a   Mosley, Jonathan D ^a   Wells, Quinn S ^a   Karnes, Jason H ^a   Shaffer, Christian ^a   Peterson, Josh F ^a   Denny, Joshua C ^a   Roden, Dan M ^a,b   Pulley, Jill M ^b  

^a VANDERBILT UNIVERSITY MEDICAL CENTER   (United States)

^b VANDERBILT UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BIOBANK; CLINICAL DATA REPOSITORY; COST BENEFIT ANALYSIS; COST CONTROL; COST EFFECTIVENESS ANALYSIS; DATA ANALYSIS; ELECTRONIC MEDICAL RECORD; GENE TECHNOLOGY; GENETIC ALGORITHM; GENETIC ASSOCIATION; GENETIC DATABASE; HUMAN; INTERMETHOD COMPARISON; NOTE; PHARMACOGENOMICS; PHENOTYPE; PRIORITY JOURNAL; ECONOMICS; ELECTRONIC HEALTH RECORD; ELECTRONIC MEDICAL RECORD SYSTEM; MEDICAL RESEARCH;

BIOLOGICAL SPECIMEN BANKS; BIOMEDICAL RESEARCH; ELECTRONIC HEALTH RECORDS; HUMANS; MEDICAL RECORDS SYSTEMS, COMPUTERIZED;

EID: 84899788364     PISSN: 19466234     EISSN: 19466242     Source Type: Journal    
DOI: 10.1126/scitranslmed.3008604     Document Type: Note

References (40)

1. R. J. Carroll, A. E. Eyler, J. C. Denny, Naïve electronic health record phenotype identification for rheumatoid arthritis. AMIA Annu. Symp. Proc. 2011, 189-196 (2011).
2. J. C. Denny, J. F. Peterson, N. N. Choma, H. Xu, R. A. Miller, L. Bastarache, N. B. Peterson, Extracting timing and status descriptors for colonoscopy testing from electronic medical records. J. Am. Med. Inform. Assoc. 17, 383-388 (2010).
3. R. J. Carroll, W. K. Thompson, A. E. Eyler, A. M. Mandelin, T. Cai, R. M. Zink, J. A. Pacheco, C. S. Boomershine, T. A. Lasko, H. Xu, E. W. Karlson, R. G. Perez, V. S. Gainer, S. N. Murphy, E. M. Ruderman, R. M. Pope, R. M. Plenge, A. N. Kho, K. P. Liao, J. C. Denny, Portability of an algorithm to identify rheumatoid arthritis in electronic health records. J. Am. Med. Inform. Assoc. 19, (e1), e162-e169 (2012).
4. W. Sun, A. Rumshisky, O. Uzuner, Evaluating temporal relations in clinical text: 2012 i2b2 challenge. J. Am. Med. Inform. Assoc. 20, 806-813 (2013).
5. J. T. Delaney, A. H. Ramirez, E. Bowton, J. M. Pulley, M. A. Basford, J. S. Schildcrout, Y. Shi, R. Zink, M. Oetjens, H. Xu, J. H. Cleator, E. Jahangir, M. D. Ritchie, D. R. Masys, D. M. Roden, D. C. Crawford, J. C. Denny, Predicting clopidogrel response using DNA samples linked to an electronic health record. Clin. Pharmacol. Ther. 91, 257-263 (2012).
6. A. H. Ramirez, Y. Shi, J. S. Schildcrout, J. T. Delaney, H. Xu, M. T. Oetjens, R. L. Zuvich, M. A. Basford, E. Bowton, M. Jiang, P. Speltz, R. Zink, J. Cowan, J. M. Pulley, M. D. Ritchie, D. R. Masys, D. M. Roden, D. C. Crawford, J. C. Denny, Predicting warfarin dosage in European-Americans and African-Americans using DNA samples linked to an electronic health record. Pharmacogenomics 13, 407-418 (2012).
7. RePORT query form. http://projectreporter.nih.gov/reporter.cfm.
8. P. R. Burton, A. L. Hansell, I. Fortier, T. A. Manolio, M. J. Khoury, J. Little, P. Elliott, Size matters: Just how big is BIG?: Quantifying realistic sample size requirements for human genome epidemiology. Int. J. Epidemiol. 38, 263-273 (2009).
9. A. N. Kho, J. A. Pacheco, P. L. Peissig, L. Rasmussen, K. M. Newton, N. Weston, P. K. Crane, J. Pathak, C. G. Chute, S. J. Bielinski, I. J. Kullo, R. Li, T. A. Manolio, R. L. Chisholm, J. C. Denny, Electronic medical records for genetic research: Results of the eMERGE consortium. Sci. Transl. Med. 3, 79re1 (2011).
10. C. A. McCarty, R. L. Chisholm, C. G. Chute, I. J. Kullo, G. P. Jarvik, E. B. Larson, R. Li, D. R. Masys, M. D. Ritchie, D. M. Roden, J. P. Struewing, W. A. Wolf, M. E. R. G. E. Team eMERGE Team, The eMERGE network: A consortium of biorepositories linked to electronic medical records data for conducting genomic studies. BMC Med. Genomics 4, 13 (2011).
11. O. Gottesman, H. Kuivaniemi, G. Tromp, W. A. Faucett, R. Li, T. A. Manolio, S. C. Sanderson, J. Kannry, R. Zinberg, M. A. Basford, M. Brilliant, D. J. Carey, R. L. Chisholm, C. G. Chute, J. J. Connolly, D. Crosslin, J. C. Denny, C. J. Gallego, J. L. Haines, H. Hakonarson, J. Harley, G. P. Jarvik, I. Kohane, I. J. Kullo, E. B. Larson, C. McCarty, M. D. Ritchie, D. M. Roden, M. E. Smith, E. P. Böttinger, M. S. Williams eMERGE Network, The electronic medical records and genomics (eMERGE) network: past, present, and future. Genet. Med. 15, 761-771 (2013).
12. Wellcome Trust Case Control Consortium, Genome-wide association study of 14,000 cases of seven common diseases and 3000 shared controls. Nature 447, 661-678 (2007).
13. D. M. Roden, J. M. Pulley, M. A. Basford, G. R. Bernard, E. W. Clayton, J. R. Balser, D. R. Masys, Development of a large-scale de-identified DNA biobank to enable personalized medicine. Clin. Pharmacol. Ther. 84, 362-369 (2008).
14. T. L. McGregor, S. L. Van Driest, K. B. Brothers, E. A. Bowton, L. J. Muglia, D. M. Roden, Inclusion of pediatric samples in an opt-out biorepository linking DNA to de-identified medical records: Pediatric BioVU. Clin. Pharmacol. Ther. 93, 204-211 (2013).
15. M. D. Ritchie, J. C. Denny, R. L. Zuvich, D. C. Crawford, J. S. Schildcrout, L. Bastarache, A. H. Ramirez, J. D. Mosley, J. M. Pulley, M. A. Basford, Y. Bradford, L. V. Rasmussen, J. Pathak, C. G. Chute, I. J. Kullo, C. A. McCarty, R. L. Chisholm, A. N. Kho, C. S. Carlson, E. B. Larson, G. P. Jarvik, N. Sotoodehnia, T. A. Manolio, R. Li, D. R. Masys, J. L. Haines, D. M. Roden, Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) QRS Group, Genome- and phenome-wide analyses of cardiac conduction identifies markers of arrhythmia risk. Circulation 127, 1377-1385 (2013).
16. I. J. Kullo, K. Ding, K. Shameer, C. A. McCarty, G. P. Jarvik, J. C. Denny, M. D. Ritchie, Z. Ye, D. R. Crosslin, R. L. Chisholm, T. A. Manolio, C. G. Chute, Complement receptor 1 gene variants are associated with erythrocyte sedimentation rate. Am. J. Hum. Genet. 89, 131-138 (2011).
17. J. C. Denny, M. D. Ritchie, D. C. Crawford, J. S. Schildcrout, A. H. Ramirez, J. M. Pulley, M. A. Basford, D. R. Masys, J. L. Haines, D. M. Roden, Identification of genomic predictors of atrioventricular conduction: Using electronic medical records as a tool for genome science. Circulation 122, 2016-2021 (2010).
18. J. P. A. Ioannidis, T. A. Trikalinos, M. J. Khoury, Implications of small effect sizes of individual genetic variants on the design and interpretation of genetic association studies of complex diseases. Am. J. Epidemiol. 164, 609-614 (2006).
19. E. Evangelou, J. P. A. Ioannidis, Meta-analysis methods for genome-wide association studies and beyond. Nat. Rev. Genet. 14, 379-389 (2013).
20. M. I. McCarthy, G. R. Abecasis, L. R. Cardon, D. B. Goldstein, J. Little, J. P. A. Ioannidis, J. N. Hirschhorn, Genome-wide association studies for complex traits: Consensus, uncertainty and challenges. Nat. Rev. Genet. 9, 356-369 (2008).
21. G. M. Cooper, J. A. Johnson, T. Y. Langaee, H. Feng, I. B. Stanaway, U. I. Schwarz, M. D. Ritchie, C. M. Stein, D. M. Roden, J. D. Smith, D. L. Veenstra, A. E. Rettie, M. J. Rieder, A genome-wide scan for common genetic variants with a large influence on warfarin maintenance dose. Blood 112, 1022-1027 (2008).
22. E. Link, S. Parish, J. Armitage, L. Bowman, S. Heath, F. Matsuda, I. Gut, M. Lathrop, R. Collins, SEARCH Collaborative Group, SLCO1B1 variants and statin-induced myopathy - A genome-wide study. N. Engl. J. Med. 359, 789-799 (2008).
23. S. Mallal, E. Phillips, G. Carosi, J.-M. Molina, C. Workman, J. Tomazic, E. Jägel-Guedes, S. Rugina, O. Kozyrev, J. F. Cid, P. Hay, D. Nolan, S. Hughes, A. Hughes, S. Ryan, N. Fitch, D. Thorborn, A. Benbow, PREDICT-1 Study Team, HLA-B*5701 screening for hypersensitivity to abacavir. N. Engl. J. Med. 358, 568-579 (2008).
24. J. C. Denny, L. Bastarache, M. D. Ritchie, R. J. Carroll, R. Zink, J. D. Mosley, J. R. Field, J. M. Pulley, A. H. Ramirez, E. Bowton, M. A. Basford, D. S. Carrell, P. L. Peissig, A. N. Kho, J. A. Pacheco, L. V. Rasmussen, D. R. Crosslin, P. K. Crane, J. Pathak, S. J. Bielinski, S. A. Pendergrass, H. Xu, L. A. Hindorff, R. Li, T. A. Manolio, C. G. Chute, R. L. Chisholm, E. B. Larson, G. P. Jarvik, M. H. Brilliant, C. A. McCarty, I. J. Kullo, J. L. Haines, D. C. Crawford, D. R. Masys, D. M. Roden, Systematic comparison of phenome-wide association study of electronic medical record data and genome-wide association study data. Nat. Biotechnol. 31, 1102-1110 (2013).
25. M. Garcia-Closas, N. Rothman, J. Lubin, Misclassification in case-control studies of gene-environment interactions: Assessment of bias and sample size. Cancer Epidemiol. Biomarkers Prev. 8, 1043-1050 (1999).
26. M. Jiang, J. C. Denny, B. Tang, H. Cao, H. Xu, Extracting semantic lexicons from discharge summaries using machine learning and the C-Value method. AMIA Annu. Symp. Proc. 2012, 409-416 (2012).
27. The impact of sequestration on NIH (2012). www.aamc.org/research/adhocgp/ aamcimpactofsequestrationonnih.pdf
28. F. S. Collins, The case for a US prospective cohort study of genes and environment. Nature 429, 475-477 (2004).
29. I. S. Kohane, Using electronic health records to drive discovery in disease genomics. Nat. Rev. Genet. 12, 417-428 (2011).
30. G. E. Henderson, R. J. Cadigan, T. P. Edwards, I. Conlon, A. G. Nelson, J. P. Evans, A. M. Davis, C. Zimmer, B. J. Weiner, Characterizing biobank organizations in the U.S.: Results from a national survey. Genome Med. 5, 3 (2013).
31. W. Ollier, T. Sprosen, T. Peakman, UK Biobank: From concept to reality. Pharmacogenomics 6, 639-646 (2005).
32. L. J. Palmer, UK Biobank: bank on it. Lancet 369, 1980-1982 (2007).
33. Z. Chen, J. Chen, R. Collins, Y. Guo, R. Peto, F. Wu, L. LiChina Kadoorie Biobank (CKB) collaborative group, China Kadoorie Biobank of 0.5 million people: Survey methods, baseline characteristics and long-term follow-up. Int. J. Epidemiol. 40, 1652-1666 (2011).
34. H. Xu, S. P. Stenner, S. Doan, K. B. Johnson, L. R. Waitman, J. C. Denny, MedEx: A medication information extraction system for clinical narratives. J. Am. Med. Inform. Assoc. 17, 19-24 (2010).
35. S. B. Trinidad, S. M. Fullerton, J. M. Bares, G. P. Jarvik, E. B. Larson, W. Burke, Genomic research and wide data sharing: Views of prospective participants. Genet. Med. 12, 486-495 (2010).
36. K. B. Brothers, E. W. Clayton, Parental perspectives on a pediatric human non-subjects biobank. AJOB Prim. Res. 3, 21-29 (2012).
37. J. M. Pulley, M. M. Brace, G. R. Bernard, D. R. Masys, Attitudes and perceptions of patients towards methods of establishing a DNA biobank. Cell Tissue Bank. 9, 55-65 (2008).
38. C. M. Simon, E. Newbury, J. L'heureux, Protecting participants, promoting progress: Public perspectives on community advisory boards (CABs) in biobanking. J. Empir. Res. Hum. Res. Ethics 6, 19-30 (2011).
39. J. Murphy, J. Scott, D. Kaufman, G. Geller, L. LeRoy, K. Hudson, Public perspectives on informed consent for biobanking. Am. J. Public Health 99, 2128-2134 (2009).
40. C. T. Scott, T. Caulfield, E. Borgelt, J. Illes, Personal medicine - The new banking crisis. Nat. Biotechnol. 30, 141-147 (2012).