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Published in: International Journal of Bipolar Disorders 1/2015

Open Access 01-12-2015 | Review

Big data are coming to psychiatry: a general introduction

Authors: Scott Monteith, Tasha Glenn, John Geddes, Michael Bauer

Published in: International Journal of Bipolar Disorders | Issue 1/2015

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Abstract

Big data are coming to the study of bipolar disorder and all of psychiatry. Data are coming from providers and payers (including EMR, imaging, insurance claims and pharmacy data), from omics (genomic, proteomic, and metabolomic data), and from patients and non-providers (data from smart phone and Internet activities, sensors and monitoring tools). Analysis of the big data will provide unprecedented opportunities for exploration, descriptive observation, hypothesis generation, and prediction, and the results of big data studies will be incorporated into clinical practice. Technical challenges remain in the quality, analysis and management of big data. This paper discusses some of the fundamental opportunities and challenges of big data for psychiatry.
Literature
go back to reference Altman RB, Ashley EA. Using “big data” to dissect clinical heterogeneity. Circulation. 2015;131:232–3.PubMedCrossRef Altman RB, Ashley EA. Using “big data” to dissect clinical heterogeneity. Circulation. 2015;131:232–3.PubMedCrossRef
go back to reference Austin PC. An introduction to propensity score methods for reducing the effects of confounding in observational studies. Multivar Behav Res. 2011;46:399–424.CrossRef Austin PC. An introduction to propensity score methods for reducing the effects of confounding in observational studies. Multivar Behav Res. 2011;46:399–424.CrossRef
go back to reference Bauer M, Glenn T, Alda M, Sagduyu K, Marsh W, Grof P, et al. Drug treatment patterns in bipolar disorder: analysis of long-term self-reported data. Int J Bipolar Disord. 2013a;1:5.PubMedCentralPubMedCrossRef Bauer M, Glenn T, Alda M, Sagduyu K, Marsh W, Grof P, et al. Drug treatment patterns in bipolar disorder: analysis of long-term self-reported data. Int J Bipolar Disord. 2013a;1:5.PubMedCentralPubMedCrossRef
go back to reference Bauer R, Glenn T, Alda M, Sagduyu K, Marsh W, Grof P, et al. Antidepressant dosage taken by patients with bipolar disorder: factors associated with irregularity. Int J Bipolar Disord. 2013b;9(1):26.CrossRef Bauer R, Glenn T, Alda M, Sagduyu K, Marsh W, Grof P, et al. Antidepressant dosage taken by patients with bipolar disorder: factors associated with irregularity. Int J Bipolar Disord. 2013b;9(1):26.CrossRef
go back to reference Ben-Ari A, Hammond K. Text mining the EMR for modeling and predicting suicidal behavior among US veterans of the 1991 Persian Gulf War. In: 2015 48th Hawaii international conference on system sciences (HICSS), IEEE; 2015. p. 3168–75. Ben-Ari A, Hammond K. Text mining the EMR for modeling and predicting suicidal behavior among US veterans of the 1991 Persian Gulf War. In: 2015 48th Hawaii international conference on system sciences (HICSS), IEEE; 2015. p. 3168–75.
go back to reference Bhugra D, Easter A, Mallaris Y, Gupta S. Clinical decision making in psychiatry by psychiatrists. Acta Psychiatr Scand. 2011;124:403–11.PubMedCrossRef Bhugra D, Easter A, Mallaris Y, Gupta S. Clinical decision making in psychiatry by psychiatrists. Acta Psychiatr Scand. 2011;124:403–11.PubMedCrossRef
go back to reference Bollier D, Firestone CM, Bollier D, Firestone CM. The promise and peril of big data. Washington: Aspen Institute, Communications and Society Program; 2010. Bollier D, Firestone CM, Bollier D, Firestone CM. The promise and peril of big data. Washington: Aspen Institute, Communications and Society Program; 2010.
go back to reference Bourgeois FC, Olson KL, Mandl KD. Patients treated at multiple acute health care facilities: quantifying information fragmentation. Arch Intern Med. 2010;170:1989–95.PubMedCrossRef Bourgeois FC, Olson KL, Mandl KD. Patients treated at multiple acute health care facilities: quantifying information fragmentation. Arch Intern Med. 2010;170:1989–95.PubMedCrossRef
go back to reference Boyd D, Crawford K. Critical questions for big data: provocations for a cultural, technological, and scholarly phenomenon. Inf Commun Soc. 2012;15:662–79.CrossRef Boyd D, Crawford K. Critical questions for big data: provocations for a cultural, technological, and scholarly phenomenon. Inf Commun Soc. 2012;15:662–79.CrossRef
go back to reference Buneman P, Khanna S, Tan, WC. Data provenance: some basic issues. In: FST TCS 2000: foundations of software technology and theoretical computer science. Berlin: Springer; 2000. p. 87–93. Buneman P, Khanna S, Tan, WC. Data provenance: some basic issues. In: FST TCS 2000: foundations of software technology and theoretical computer science. Berlin: Springer; 2000. p. 87–93.
go back to reference Castro VM, Minnier J, Murphy SN, Kohane I, Churchill SE, Gainer V, et al. Validation of electronic health record phenotyping of bipolar disorder cases and controls. Am J Psychiatry. 2015;172:363–72.PubMedCrossRef Castro VM, Minnier J, Murphy SN, Kohane I, Churchill SE, Gainer V, et al. Validation of electronic health record phenotyping of bipolar disorder cases and controls. Am J Psychiatry. 2015;172:363–72.PubMedCrossRef
go back to reference Celi LA, Mark RG, Stone DJ, Montgomery RA. “Big data” in the intensive care unit. Closing the data loop. Am J Respir Crit Care Med. 2013;187:1157–60.PubMedCrossRef Celi LA, Mark RG, Stone DJ, Montgomery RA. “Big data” in the intensive care unit. Closing the data loop. Am J Respir Crit Care Med. 2013;187:1157–60.PubMedCrossRef
go back to reference Chan KS, Fowles JB, Weiner JP. Review: electronic health records and the reliability and validity of quality measures: a review of the literature. Med Care Res Rev. 2010;67:503–27.PubMedCrossRef Chan KS, Fowles JB, Weiner JP. Review: electronic health records and the reliability and validity of quality measures: a review of the literature. Med Care Res Rev. 2010;67:503–27.PubMedCrossRef
go back to reference Cohen R, Elhadad M, Elhadad N. Redundancy in electronic health record corpora: analysis, impact on text mining performance and mitigation strategies. BMC Bioinform. 2013;14:10.CrossRef Cohen R, Elhadad M, Elhadad N. Redundancy in electronic health record corpora: analysis, impact on text mining performance and mitigation strategies. BMC Bioinform. 2013;14:10.CrossRef
go back to reference Cook BL, Zuvekas SH, Carson N, Wayne GF, Vesper A, McGuire TG. Assessing racial/ethnic disparities in treatment across episodes of mental health care. Health Serv Res. 2014;49:206–29.PubMedCentralPubMedCrossRef Cook BL, Zuvekas SH, Carson N, Wayne GF, Vesper A, McGuire TG. Assessing racial/ethnic disparities in treatment across episodes of mental health care. Health Serv Res. 2014;49:206–29.PubMedCentralPubMedCrossRef
go back to reference De Domenico M, Lima A, Musolesi M. Interdependence and predictability of human mobility and social interactions. Pervasive Mob Comput. 2013;9:798–807.CrossRef De Domenico M, Lima A, Musolesi M. Interdependence and predictability of human mobility and social interactions. Pervasive Mob Comput. 2013;9:798–807.CrossRef
go back to reference Dormuth CR, Patrick AR, Shrank WH, Wright JM, Glynn RJ, Sutherland J, Brookhart MA. Statin adherence and risk of accidents: a cautionary tale. Circulation. 2009;119:2051–7.PubMedCentralPubMedCrossRef Dormuth CR, Patrick AR, Shrank WH, Wright JM, Glynn RJ, Sutherland J, Brookhart MA. Statin adherence and risk of accidents: a cautionary tale. Circulation. 2009;119:2051–7.PubMedCentralPubMedCrossRef
go back to reference FitzHenry F, Murff HJ, Matheny ME, Gentry N, Fielstein EM, Brown SH, et al. Exploring the frontier of electronic health record surveillance: the case of postoperative complications. Med Care. 2013;51:509–16.PubMedCentralPubMedCrossRef FitzHenry F, Murff HJ, Matheny ME, Gentry N, Fielstein EM, Brown SH, et al. Exploring the frontier of electronic health record surveillance: the case of postoperative complications. Med Care. 2013;51:509–16.PubMedCentralPubMedCrossRef
go back to reference Gardner RC, Burke JF, Nettiksimmons J, Kaup A, Barnes DE, Yaffe K. Dementia risk after traumatic brain injury vs nonbrain trauma: the role of age and severity. JAMA Neurol. 2014;71:1490–7.PubMedPubMedCentralCrossRef Gardner RC, Burke JF, Nettiksimmons J, Kaup A, Barnes DE, Yaffe K. Dementia risk after traumatic brain injury vs nonbrain trauma: the role of age and severity. JAMA Neurol. 2014;71:1490–7.PubMedPubMedCentralCrossRef
go back to reference Ghassemi M, Marshall J, Singh N, Stone DJ, Celi LA. Leveraging a critical care database: selective serotonin reuptake inhibitor use prior to ICU admission is associated with increased hospital mortality. Chest. 2014;145:745–52.PubMedCentralPubMedCrossRef Ghassemi M, Marshall J, Singh N, Stone DJ, Celi LA. Leveraging a critical care database: selective serotonin reuptake inhibitor use prior to ICU admission is associated with increased hospital mortality. Chest. 2014;145:745–52.PubMedCentralPubMedCrossRef
go back to reference Giordano SH, Kuo YF, Duan Z, Hortobagyi GN, Freeman J, Goodwin JS. Limits of observational data in determining outcomes from cancer therapy. Cancer. 2008;112:2456–66.PubMedCrossRef Giordano SH, Kuo YF, Duan Z, Hortobagyi GN, Freeman J, Goodwin JS. Limits of observational data in determining outcomes from cancer therapy. Cancer. 2008;112:2456–66.PubMedCrossRef
go back to reference Glenn T, Monteith S. New measures of mental state and behavior based on data collected from sensors, smartphones, and the Internet. Curr Psychiatry Rep. 2014;16:523.PubMedCrossRef Glenn T, Monteith S. New measures of mental state and behavior based on data collected from sensors, smartphones, and the Internet. Curr Psychiatry Rep. 2014;16:523.PubMedCrossRef
go back to reference Goldman D, Fastenau J, Dirani R, Helland E, Joyce G, Conrad R, et al. Medicaid prior authorization policies and imprisonment among patients with schizophrenia. Am J Manag Care. 2014;20:577–86.PubMed Goldman D, Fastenau J, Dirani R, Helland E, Joyce G, Conrad R, et al. Medicaid prior authorization policies and imprisonment among patients with schizophrenia. Am J Manag Care. 2014;20:577–86.PubMed
go back to reference Gonzalez MC, Hidalgo CA, Barabasi AL. Understanding individual human mobility patterns. Nature. 2008;453:779–82.PubMedCrossRef Gonzalez MC, Hidalgo CA, Barabasi AL. Understanding individual human mobility patterns. Nature. 2008;453:779–82.PubMedCrossRef
go back to reference Grether JK, Anderson MC, Croen LA, Smith D, Windham GC. Risk of autism and increasing maternal and paternal age in a large north American population. Am J Epidemiol. 2009;170:1118–26.PubMedCrossRef Grether JK, Anderson MC, Croen LA, Smith D, Windham GC. Risk of autism and increasing maternal and paternal age in a large north American population. Am J Epidemiol. 2009;170:1118–26.PubMedCrossRef
go back to reference Halamka JD. Early experiences with big data at an academic medical center. Health Aff (Millwood). 2014;33:1132–8.CrossRef Halamka JD. Early experiences with big data at an academic medical center. Health Aff (Millwood). 2014;33:1132–8.CrossRef
go back to reference Hargittai E. Is bigger always better? Potential biases of big data derived from social network sites. Ann Am Acad Pol Soc Sci. 2015;659:63–76.CrossRef Hargittai E. Is bigger always better? Potential biases of big data derived from social network sites. Ann Am Acad Pol Soc Sci. 2015;659:63–76.CrossRef
go back to reference Harpaz R, DuMouchel W, Shah NH, Madigan D, Ryan P, Friedman C. Novel data-mining methodologies for adverse drug event discovery and analysis. Clin Pharmacol Ther. 2012;91:1010–21.PubMedCentralPubMedCrossRef Harpaz R, DuMouchel W, Shah NH, Madigan D, Ryan P, Friedman C. Novel data-mining methodologies for adverse drug event discovery and analysis. Clin Pharmacol Ther. 2012;91:1010–21.PubMedCentralPubMedCrossRef
go back to reference Hersh WR, Weiner MG, Embi PJ, Logan JR, Payne PR, Bernstam EV, et al. Caveats for the use of operational electronic health record data in comparative effectiveness research. Med Care. 2013;51(8 Suppl 3):S30–7.PubMedCentralPubMedCrossRef Hersh WR, Weiner MG, Embi PJ, Logan JR, Payne PR, Bernstam EV, et al. Caveats for the use of operational electronic health record data in comparative effectiveness research. Med Care. 2013;51(8 Suppl 3):S30–7.PubMedCentralPubMedCrossRef
go back to reference Hill G. Looking at data from a different perspective: an interview with Sean Patrick Murphy. Big Data Innovation Magazine; 2013. Hill G. Looking at data from a different perspective: an interview with Sean Patrick Murphy. Big Data Innovation Magazine; 2013.
go back to reference Hoertel N, Le Strat Y, Lavaud P, Dubertret C, Limosin F. Generalizability of clinical trial results for bipolar disorder to community samples: findings from the National Epidemiologic Survey on Alcohol and Related Conditions. J Clin Psychiatry. 2013;74:265–70.PubMedCrossRef Hoertel N, Le Strat Y, Lavaud P, Dubertret C, Limosin F. Generalizability of clinical trial results for bipolar disorder to community samples: findings from the National Epidemiologic Survey on Alcohol and Related Conditions. J Clin Psychiatry. 2013;74:265–70.PubMedCrossRef
go back to reference Holowka DW, Marx BP, Gates MA, Litman HJ, Ranganathan G, Rosen RC, et al. PTSD diagnostic validity in Veterans Affairs electronic records of Iraq and Afghanistan veterans. J Consult Clin Psychol. 2014;82:569–79.PubMedCrossRef Holowka DW, Marx BP, Gates MA, Litman HJ, Ranganathan G, Rosen RC, et al. PTSD diagnostic validity in Veterans Affairs electronic records of Iraq and Afghanistan veterans. J Consult Clin Psychol. 2014;82:569–79.PubMedCrossRef
go back to reference Huybrechts KF, Schneeweiss S, Gerhard T, Olfson M, Avorn J, Levin R, et al. Comparative safety of antipsychotic medications in nursing home residents. J Am Geriatr Soc. 2012;60:420–9.PubMedCentralPubMedCrossRef Huybrechts KF, Schneeweiss S, Gerhard T, Olfson M, Avorn J, Levin R, et al. Comparative safety of antipsychotic medications in nursing home residents. J Am Geriatr Soc. 2012;60:420–9.PubMedCentralPubMedCrossRef
go back to reference Ioannidis JP. Informed consent, big data, and the oxymoron of research that is not research. Am J Bioeth. 2013;13:40–2.PubMedCrossRef Ioannidis JP. Informed consent, big data, and the oxymoron of research that is not research. Am J Bioeth. 2013;13:40–2.PubMedCrossRef
go back to reference Ioannidis JP, Allison DB, Ball CA, Coulibaly I, Cui X, Culhane AC, et al. Repeatability of published microarray gene expression analyses. Nat Genet. 2009;41:149–55.PubMedCrossRef Ioannidis JP, Allison DB, Ball CA, Coulibaly I, Cui X, Culhane AC, et al. Repeatability of published microarray gene expression analyses. Nat Genet. 2009;41:149–55.PubMedCrossRef
go back to reference Jackson LA, Jackson ML, Nelson JC, Neuzil KM, Weiss NS. Evidence of bias in estimates of influenza vaccine effectiveness in seniors. Int J Epidemiol. 2006;35:337–44.PubMedCrossRef Jackson LA, Jackson ML, Nelson JC, Neuzil KM, Weiss NS. Evidence of bias in estimates of influenza vaccine effectiveness in seniors. Int J Epidemiol. 2006;35:337–44.PubMedCrossRef
go back to reference Jagadish HV, Gehrke J, Labrinidis A, Papakonstantinou Y, Patel JM, Ramakrishnan R, et al. Big data and its technical challenges. Commun ACM. 2014;57:86–94.CrossRef Jagadish HV, Gehrke J, Labrinidis A, Papakonstantinou Y, Patel JM, Ramakrishnan R, et al. Big data and its technical challenges. Commun ACM. 2014;57:86–94.CrossRef
go back to reference Jashinsky J, Burton SH, Hanson CL, West J, Giraud-Carrier C, Barnes MD, et al. Tracking suicide risk factors through Twitter in the US. Crisis. 2014;35:51–9.PubMedCrossRef Jashinsky J, Burton SH, Hanson CL, West J, Giraud-Carrier C, Barnes MD, et al. Tracking suicide risk factors through Twitter in the US. Crisis. 2014;35:51–9.PubMedCrossRef
go back to reference Jasser SA, Garvin JH, Wiedemer N, Roche D, Gallagher RM. Information technology in mental health research: impediments and implications in one chronic pain study population. Pain Med. 2007;8(s3):S176–81.CrossRef Jasser SA, Garvin JH, Wiedemer N, Roche D, Gallagher RM. Information technology in mental health research: impediments and implications in one chronic pain study population. Pain Med. 2007;8(s3):S176–81.CrossRef
go back to reference Joseph AJ, Tandon N, Yang LH, Duckworth K, Torous J, Seidman LJ, et al. #Schizophrenia: use and misuse on Twitter. Schizophr Res. 2015;165:111–5.PubMedCrossRef Joseph AJ, Tandon N, Yang LH, Duckworth K, Torous J, Seidman LJ, et al. #Schizophrenia: use and misuse on Twitter. Schizophr Res. 2015;165:111–5.PubMedCrossRef
go back to reference Kaplan RM, Chambers DA, Glasgow RE. Big data and large sample size: a cautionary note on the potential for bias. Clin Transl Sci. 2014;7:342–6.PubMedCrossRef Kaplan RM, Chambers DA, Glasgow RE. Big data and large sample size: a cautionary note on the potential for bias. Clin Transl Sci. 2014;7:342–6.PubMedCrossRef
go back to reference Kessler RC, Warner CH, Ivany C, Petukhova MV, Rose S, Bromet EJ, et al. Predicting suicides after psychiatric hospitalization in US Army soldiers: the army study to assess risk and resilience in service members (Army STARRS). JAMA Psychiatry. 2015;72:49–57.PubMedPubMedCentralCrossRef Kessler RC, Warner CH, Ivany C, Petukhova MV, Rose S, Bromet EJ, et al. Predicting suicides after psychiatric hospitalization in US Army soldiers: the army study to assess risk and resilience in service members (Army STARRS). JAMA Psychiatry. 2015;72:49–57.PubMedPubMedCentralCrossRef
go back to reference Kho ME, Duffett M, Willison DJ, Cook DJ, Brouwers MC. Written informed consent and selection bias in observational studies using medical records: systematic review. BMJ. 2009;338:b866.PubMedCentralPubMedCrossRef Kho ME, Duffett M, Willison DJ, Cook DJ, Brouwers MC. Written informed consent and selection bias in observational studies using medical records: systematic review. BMJ. 2009;338:b866.PubMedCentralPubMedCrossRef
go back to reference Kielman J, Thomas J, May R. Foundations and frontiers in visual analytics. Inf Vis. 2009;8:239–46.CrossRef Kielman J, Thomas J, May R. Foundations and frontiers in visual analytics. Inf Vis. 2009;8:239–46.CrossRef
go back to reference Knopman DS, Petersen RC, Rocca WA, Larson EB, Ganguli M. Passive case-finding for Alzheimer’s disease and dementia in two U.S. communities. Alzheimers Dement. 2011;7:53–60.PubMedCentralPubMedCrossRef Knopman DS, Petersen RC, Rocca WA, Larson EB, Ganguli M. Passive case-finding for Alzheimer’s disease and dementia in two U.S. communities. Alzheimers Dement. 2011;7:53–60.PubMedCentralPubMedCrossRef
go back to reference Kosinski M, Stillwell D, Graepel T. Private traits and attributes are predictable from digital records of human behavior. Proc Natl Acad Sci USA. 2013;110:5802–5.PubMedCentralPubMedCrossRef Kosinski M, Stillwell D, Graepel T. Private traits and attributes are predictable from digital records of human behavior. Proc Natl Acad Sci USA. 2013;110:5802–5.PubMedCentralPubMedCrossRef
go back to reference Kouzes RT, Anderson GA, Elbert ST, Gorton I, Gracio DK. The changing paradigm of data-intensive computing. Computer. 2009;1:26–34.CrossRef Kouzes RT, Anderson GA, Elbert ST, Gorton I, Gracio DK. The changing paradigm of data-intensive computing. Computer. 2009;1:26–34.CrossRef
go back to reference Kraska T. Finding the needle in the big data systems haystack. IEEE Internet Comput. 2013;17:84–6.CrossRef Kraska T. Finding the needle in the big data systems haystack. IEEE Internet Comput. 2013;17:84–6.CrossRef
go back to reference Lagomasino IT, Stockdale SE, Miranda J. Racial-ethnic composition of provider practices and disparities in treatment of depression and anxiety, 2003–2007. Psychiatr Serv. 2011;62:1019–25.PubMedCrossRef Lagomasino IT, Stockdale SE, Miranda J. Racial-ethnic composition of provider practices and disparities in treatment of depression and anxiety, 2003–2007. Psychiatr Serv. 2011;62:1019–25.PubMedCrossRef
go back to reference Lauer MS, D’Agostino RB Sr. The randomized registry trial—the next disruptive technology in clinical research? N Engl J Med. 2013;369:1579–81.PubMedCrossRef Lauer MS, D’Agostino RB Sr. The randomized registry trial—the next disruptive technology in clinical research? N Engl J Med. 2013;369:1579–81.PubMedCrossRef
go back to reference Lazer D, Kennedy R, King G, Vespignani A. Big data. The parable of Google Flu: traps in big data analysis. Science. 2014;343:1203–5.PubMedCrossRef Lazer D, Kennedy R, King G, Vespignani A. Big data. The parable of Google Flu: traps in big data analysis. Science. 2014;343:1203–5.PubMedCrossRef
go back to reference March JS, Silva SG, Compton S, Shapiro M, Califf R, Krishnan R. The case for practical clinical trials in psychiatry. Am J Psychiatry. 2005;162:836–46.PubMedCrossRef March JS, Silva SG, Compton S, Shapiro M, Califf R, Krishnan R. The case for practical clinical trials in psychiatry. Am J Psychiatry. 2005;162:836–46.PubMedCrossRef
go back to reference Mark TL, Levit KR, Buck JA. Datapoints: psychotropic drug prescriptions by medical specialty. Psychiatr Serv. 2009;60:1167.PubMedCrossRef Mark TL, Levit KR, Buck JA. Datapoints: psychotropic drug prescriptions by medical specialty. Psychiatr Serv. 2009;60:1167.PubMedCrossRef
go back to reference McIntyre RS, Cha DS, Jerrell JM, Swardfager W, Kim RD, Costa LG, et al. Advancing biomarker research: utilizing ‘Big Data’ approaches for the characterization and prevention of bipolar disorder. Bipolar Disord. 2014;16:531–47.PubMedCrossRef McIntyre RS, Cha DS, Jerrell JM, Swardfager W, Kim RD, Costa LG, et al. Advancing biomarker research: utilizing ‘Big Data’ approaches for the characterization and prevention of bipolar disorder. Bipolar Disord. 2014;16:531–47.PubMedCrossRef
go back to reference Mislove A, Lehmann S, Ahn YY, Onnela JP, Rosenquist JN. Understanding the demographics of Twitter users, 5th ICWSM; 2011. p. 11. Mislove A, Lehmann S, Ahn YY, Onnela JP, Rosenquist JN. Understanding the demographics of Twitter users, 5th ICWSM; 2011. p. 11.
go back to reference Monniaux D. The pitfalls of verifying floating-point computations. ACM Trans Progr Lang Syst (TOPLAS). 2008;30:12. Monniaux D. The pitfalls of verifying floating-point computations. ACM Trans Progr Lang Syst (TOPLAS). 2008;30:12.
go back to reference Monroe BL, Pan J, Roberts ME, Sen M, Sinclair B. No! Formal theory, causal inference, and big data are not contradictory trends in political science. PS Polit Sci Polit. 2015;48:71–4.CrossRef Monroe BL, Pan J, Roberts ME, Sen M, Sinclair B. No! Formal theory, causal inference, and big data are not contradictory trends in political science. PS Polit Sci Polit. 2015;48:71–4.CrossRef
go back to reference Moses C, Celi LA, Marshall J. Pharmacovigilance: an active surveillance system to proactively identify risks for adverse events. Popul Health Manag. 2013;16:147–9.PubMedCrossRef Moses C, Celi LA, Marshall J. Pharmacovigilance: an active surveillance system to proactively identify risks for adverse events. Popul Health Manag. 2013;16:147–9.PubMedCrossRef
go back to reference Murdoch TB, Detsky AS. The inevitable application of big data to health care. JAMA. 2013;309:1351–2.PubMedCrossRef Murdoch TB, Detsky AS. The inevitable application of big data to health care. JAMA. 2013;309:1351–2.PubMedCrossRef
go back to reference Nakaya HI, Wrammert J, Lee EK, Racioppi L, Marie-Kunze S, Haining WN, et al. Systems biology of vaccination for seasonal influenza in humans. Nat Immunol. 2011;12:786–95.PubMedCentralPubMedCrossRef Nakaya HI, Wrammert J, Lee EK, Racioppi L, Marie-Kunze S, Haining WN, et al. Systems biology of vaccination for seasonal influenza in humans. Nat Immunol. 2011;12:786–95.PubMedCentralPubMedCrossRef
go back to reference O’Donoghue SI, Gavin AC, Gehlenborg N, Goodsell DS, Hériché JK, Nielsen CB, et al. Visualizing biological data—now and in the future. Nat Methods. 2010;7(3 Suppl):S2–4.PubMedCrossRef O’Donoghue SI, Gavin AC, Gehlenborg N, Goodsell DS, Hériché JK, Nielsen CB, et al. Visualizing biological data—now and in the future. Nat Methods. 2010;7(3 Suppl):S2–4.PubMedCrossRef
go back to reference Orlovska S, Pedersen MS, Benros ME, Mortensen PB, Agerbo E, Nordentoft M. Head injury as risk factor for psychiatric disorders: a nationwide register-based follow-up study of 113,906 persons with head injury. Am J Psychiatry. 2014;171:463–9.PubMedCrossRef Orlovska S, Pedersen MS, Benros ME, Mortensen PB, Agerbo E, Nordentoft M. Head injury as risk factor for psychiatric disorders: a nationwide register-based follow-up study of 113,906 persons with head injury. Am J Psychiatry. 2014;171:463–9.PubMedCrossRef
go back to reference Overhage JM, Overhage LM. Sensible use of observational clinical data. Stat Methods Med Res. 2013;22:7–13.PubMedCrossRef Overhage JM, Overhage LM. Sensible use of observational clinical data. Stat Methods Med Res. 2013;22:7–13.PubMedCrossRef
go back to reference Patty JW, Penn EM. Analyzing big data: social choice and measurement. PS Polit Sci Polit. 2015;48:95–101.CrossRef Patty JW, Penn EM. Analyzing big data: social choice and measurement. PS Polit Sci Polit. 2015;48:95–101.CrossRef
go back to reference Perlis RH, Iosifescu DV, Castro VM, Murphy SN, Gainer VS, Minnier J. Using electronic medical records to enable large-scale studies in psychiatry: treatment resistant depression as a model. Psychol Med. 2012;42:41–50.PubMedCrossRef Perlis RH, Iosifescu DV, Castro VM, Murphy SN, Gainer VS, Minnier J. Using electronic medical records to enable large-scale studies in psychiatry: treatment resistant depression as a model. Psychol Med. 2012;42:41–50.PubMedCrossRef
go back to reference Pivovarov R, Albers DJ, Sepulveda JL, Elhadad N. Identifying and mitigating biases in EHR laboratory tests. J Biomed Inform. 2014;51:24–34.PubMedCrossRef Pivovarov R, Albers DJ, Sepulveda JL, Elhadad N. Identifying and mitigating biases in EHR laboratory tests. J Biomed Inform. 2014;51:24–34.PubMedCrossRef
go back to reference Polsky D, Eremina D, Hess G, Hill J, Hulnick S, Roumm A, et al. The importance of clinical variables in comparative analyses using propensity-score matching: the case of ESA costs for the treatment of chemotherapy-induced anaemia. Pharmacoeconomics. 2009;27:755–65.PubMedCrossRef Polsky D, Eremina D, Hess G, Hill J, Hulnick S, Roumm A, et al. The importance of clinical variables in comparative analyses using propensity-score matching: the case of ESA costs for the treatment of chemotherapy-induced anaemia. Pharmacoeconomics. 2009;27:755–65.PubMedCrossRef
go back to reference Potash JB. Electronic medical records: fast track to big data in bipolar disorder. Am J Psychiatry. 2015;172:310–1.PubMedCrossRef Potash JB. Electronic medical records: fast track to big data in bipolar disorder. Am J Psychiatry. 2015;172:310–1.PubMedCrossRef
go back to reference Rohrer R, Paul CL, Nebesh B. Visual analytics for big data. Next Wave. 2014;20:1–17. Rohrer R, Paul CL, Nebesh B. Visual analytics for big data. Next Wave. 2014;20:1–17.
go back to reference Rusanov A, Weiskopf NG, Wang S, Weng C. Hidden in plain sight: bias towards sick patients when sampling patients with sufficient electronic health record data for research. BMC Med Inform Decis Mak. 2014;14:51.PubMedCentralPubMedCrossRef Rusanov A, Weiskopf NG, Wang S, Weng C. Hidden in plain sight: bias towards sick patients when sampling patients with sufficient electronic health record data for research. BMC Med Inform Decis Mak. 2014;14:51.PubMedCentralPubMedCrossRef
go back to reference Schneeweiss S, Avorn J. A review of uses of health care utilization databases for epidemiologic research on therapeutics. J Clin Epidemiol. 2005;58:323–37.PubMedCrossRef Schneeweiss S, Avorn J. A review of uses of health care utilization databases for epidemiologic research on therapeutics. J Clin Epidemiol. 2005;58:323–37.PubMedCrossRef
go back to reference Shneiderman B, Plaisant C, Hesse BW. Improving healthcare with interactive visualization. Computer. 2013;5:58–66.CrossRef Shneiderman B, Plaisant C, Hesse BW. Improving healthcare with interactive visualization. Computer. 2013;5:58–66.CrossRef
go back to reference Spiegelhalter DJ. Statistics. The future lies in uncertainty. Science. 2014;18(345):264–5.CrossRef Spiegelhalter DJ. Statistics. The future lies in uncertainty. Science. 2014;18(345):264–5.CrossRef
go back to reference Srinivasan S, Moser RP, Willis G, Riley W, Alexander M, Berrigan D, et al. Small is essential: importance of subpopulation research in cancer control. Am J Public Health. 2015;105(Suppl 3):S371–3.PubMedCrossRef Srinivasan S, Moser RP, Willis G, Riley W, Alexander M, Berrigan D, et al. Small is essential: importance of subpopulation research in cancer control. Am J Public Health. 2015;105(Suppl 3):S371–3.PubMedCrossRef
go back to reference Starren J, Williams MS, Bottinger EP. Crossing the omic chasm: a time for omic ancillary systems. JAMA. 2013;309:1237–8.PubMedCrossRef Starren J, Williams MS, Bottinger EP. Crossing the omic chasm: a time for omic ancillary systems. JAMA. 2013;309:1237–8.PubMedCrossRef
go back to reference Szlezák N, Evers M, Wang J, Pérez L. The role of big data and advanced analytics in drug discovery, development, and commercialization. Clin Pharmacol Ther. 2014;95:492–5.PubMedCrossRef Szlezák N, Evers M, Wang J, Pérez L. The role of big data and advanced analytics in drug discovery, development, and commercialization. Clin Pharmacol Ther. 2014;95:492–5.PubMedCrossRef
go back to reference Titiunik R. Can big data solve the fundamental problem of causal inference? PS Polit Sci Polit. 2015;48(1):75–9.CrossRef Titiunik R. Can big data solve the fundamental problem of causal inference? PS Polit Sci Polit. 2015;48(1):75–9.CrossRef
go back to reference Toh S, García Rodríguez LA, Hernán MA. Confounding adjustment via a semi-automated high-dimensional propensity score algorithm: an application to electronic medical records. Pharmacoepidemiol Drug Saf. 2011;20:849–57.PubMedCentralPubMedCrossRef Toh S, García Rodríguez LA, Hernán MA. Confounding adjustment via a semi-automated high-dimensional propensity score algorithm: an application to electronic medical records. Pharmacoepidemiol Drug Saf. 2011;20:849–57.PubMedCentralPubMedCrossRef
go back to reference Tukey JW. The collected works of John W. Tukey: graphics 1965–1985, vol V. In: Cleveland WS, editor. Statistics/probability series. Belmont: Chapman and Hall; 1988. p. 421. Tukey JW. The collected works of John W. Tukey: graphics 1965–1985, vol V. In: Cleveland WS, editor. Statistics/probability series. Belmont: Chapman and Hall; 1988. p. 421.
go back to reference Valuck RJ, Anderson HO, Libby AM, Brandt E, Bryan C, Allen RR, et al. Enhancing electronic health record measurement of depression severity and suicide ideation: a distributed ambulatory research in therapeutics network (DARTNet) study. J Am Board Fam Med. 2012;25:582–93.PubMedCrossRef Valuck RJ, Anderson HO, Libby AM, Brandt E, Bryan C, Allen RR, et al. Enhancing electronic health record measurement of depression severity and suicide ideation: a distributed ambulatory research in therapeutics network (DARTNet) study. J Am Board Fam Med. 2012;25:582–93.PubMedCrossRef
go back to reference Ware C. Information visualization: perception for design. 3rd ed. Waltham: Elsevier; 2012. Ware C. Information visualization: perception for design. 3rd ed. Waltham: Elsevier; 2012.
go back to reference Weiner MW, Veitch DP, Aisen PS, Beckett LA, Cairns NJ, Green RC, et al. The Alzheimer’s disease neuroimaging initiative: a review of papers published since its inception. Alzheimers Dement. 2012;8(1 Suppl):S1–68.PubMedCentralPubMedCrossRef Weiner MW, Veitch DP, Aisen PS, Beckett LA, Cairns NJ, Green RC, et al. The Alzheimer’s disease neuroimaging initiative: a review of papers published since its inception. Alzheimers Dement. 2012;8(1 Suppl):S1–68.PubMedCentralPubMedCrossRef
go back to reference Wells BJ, Chagin KM, Nowacki AS, Kattan MW. Strategies for handling missing data in electronic health record derived data. EGEMS (Wash DC). 2013;1:1035. Wells BJ, Chagin KM, Nowacki AS, Kattan MW. Strategies for handling missing data in electronic health record derived data. EGEMS (Wash DC). 2013;1:1035.
go back to reference Wiechers IR, Leslie DL, Rosenheck RA. Prescribing of psychotropic medications to patients without a psychiatric diagnosis. Psychiatr Serv. 2013;64:1243–8.PubMedCrossRef Wiechers IR, Leslie DL, Rosenheck RA. Prescribing of psychotropic medications to patients without a psychiatric diagnosis. Psychiatr Serv. 2013;64:1243–8.PubMedCrossRef
go back to reference Wilbur DC. Digital pathology: get on board—the train is leaving the station. Cancer Cytopathol. 2014;122:791–5.PubMedCrossRef Wilbur DC. Digital pathology: get on board—the train is leaving the station. Cancer Cytopathol. 2014;122:791–5.PubMedCrossRef
go back to reference Wu LT, Gersing KR, Swartz MS, Burchett B, Li TK, Blazer DG. Using electronic health records data to assess comorbidities of substance use and psychiatric diagnoses and treatment settings among adults. J Psychiatr Res. 2013;47:555–63.PubMedCentralPubMedCrossRef Wu LT, Gersing KR, Swartz MS, Burchett B, Li TK, Blazer DG. Using electronic health records data to assess comorbidities of substance use and psychiatric diagnoses and treatment settings among adults. J Psychiatr Res. 2013;47:555–63.PubMedCentralPubMedCrossRef
go back to reference Yancey AK, Ortega AN, Kumanyika SK. Effective recruitment and retention of minority research participants. Annu Rev Public Health. 2006;27:1–28.PubMedCrossRef Yancey AK, Ortega AN, Kumanyika SK. Effective recruitment and retention of minority research participants. Annu Rev Public Health. 2006;27:1–28.PubMedCrossRef
go back to reference Youyou W, Kosinski M, Stillwell D. Computer-based personality judgments are more accurate than those made by humans. Proc Natl Acad Sci USA. 2015;112:1036–40.PubMedCentralPubMedCrossRef Youyou W, Kosinski M, Stillwell D. Computer-based personality judgments are more accurate than those made by humans. Proc Natl Acad Sci USA. 2015;112:1036–40.PubMedCentralPubMedCrossRef
go back to reference Zarin DA, Young JL, West JC. Challenges to evidence-based medicine: a comparison of patients and treatments in randomized controlled trials with patients and treatments in a practice research network. Soc Psychiatry Psychiatr Epidemiol. 2005;40:27–35.PubMedCrossRef Zarin DA, Young JL, West JC. Challenges to evidence-based medicine: a comparison of patients and treatments in randomized controlled trials with patients and treatments in a practice research network. Soc Psychiatry Psychiatr Epidemiol. 2005;40:27–35.PubMedCrossRef
Metadata
Title
Big data are coming to psychiatry: a general introduction
Authors
Scott Monteith
Tasha Glenn
John Geddes
Michael Bauer
Publication date
01-12-2015
Publisher
Springer Berlin Heidelberg
Published in
International Journal of Bipolar Disorders / Issue 1/2015
Electronic ISSN: 2194-7511
DOI
https://doi.org/10.1186/s40345-015-0038-9

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