Perspectives of Information-based Methods in Medicine: An Outlook for Mental Health Care

Jan Kalina, Jana Zvárová

2016

Abstract

Information-based medicine represents a concept characterizing the future ideal of medical practice overcoming the limitations of the popular concept of evidence-based medicine. The potential of information-based medicine is catalyzed by recent development of new technologies and basic research allowing to acquire a new medical knowledge relevant for an individual patient. The paper is focused on the specialty field of psychiatry. We discuss the challenges for the development of information-based psychiatry from the point of view of medical informatics together with its specific barriers and constraints. We discuss the development of telemedicine tools for psychiatric care, so far making mainly a disappointing experience. Medical informatics will also play the role in making results of basic research available to the psychiatrist at the point of care. Research results e.g. in molecular genetics or cognitive neuroscience will require to collect and analyze massive data on an individual patient. If these data are properly combined from various sources and analyzed, they represent an enormous potential for bringing a new psychiatric knowledge closer to an individual patient. This may contribute to improving the availability of psychiatric care and bringing its desirable destigmatization and humanization.

References

  1. Bergman, L. G. and Fors, U. G. H. (2008). Decision support in psychiatry-A comparison between the diagnostic outcomes using a computerized decision support system versus manual diagnosis. BMC Medical Informatics and Decision Making, 8:1-10.
  2. Borangíu, T. and Purcarea, V. (2008). The future of healthcare-Information based medicine. Journal of Medicine and Life, 1:233-237.
  3. Chen, H., Fuller, S. S., Friedman, C., and Hersh, W. (2005). Medical informatics: Knowledge management and data mining in biomedicine. Springer, New York.
  4. Daber, R., Sukhadia, S., and Morrissette, J. J. (2013). Understanding the limitations of next generation sequencing informatics, an approach to clinical pipeline validation using artificial data sets. Cancer Genetics, 206:441-448.
  5. Dentico, D., Cheung, B. L., Chang, J.-Y., Guokas, J., Boly, M., Tononi, G., and van Veen, B. (2014). Reversal of cortical information flow during visual imagery as compared to visual perception. NeuroImage, 100:237-243.
  6. Deslich, S., Stec, B., Tomblin, S., and Coustasse, A. (2013). Telepsychiatry in the 21st century: Transforming healthcare with technology. Perspectives in Health Information Management, 10.
  7. Duffau, H., editor (2011). Brain mapping: From neural basis of cognition to surgical applications, Wien. Springer.
  8. Eddy, D. M. (1990). Practice policies: Where do they come from? Journal of the American Medical Association, 263:1265-1275.
  9. Ellegood et al., J. (2015). Clustering autism: Using neuroanatomical differences in 26 mouse models to gain insight into the heterogeneity. Molecular Psychiatry, 20:188-215.
  10. Evans, C. H. and Ildstad, S. T., editors (2001). Small clinical trials: Issues and challenges, 2001. National Academy Press.
  11. Guyatt, G., Cairns, J., and Churchill et al., D. (1992). Evidence-based medicine: A new approach to teaching the practice of medicine. Journal of the American Medical Association, 268:2420-2425.
  12. Hanson, A. and Levin, B. L. (2013). Mental health informatics. Oxford University Press, Oxford.
  13. Hasman, A., Ammenwerth, E., Dickhaus, H., Knaup, P., Lovis, C., Mantas, J., Maojo, V., Martin-Sanchez, F. J., Musen, M., Patel, V. L., Surjan, G., Talmon, J. L., and Sarkar, I. N. (2011). Biomedical informatics-a confluence of disciplines? Methods of Information in Medicine, 50:508-524.
  14. Kalina, J. (2012). Implicitly weighted methods in robust image analysis. Journal of Mathematical Imaging and Vision, 44:449-462.
  15. Kalina, J. (2014). Classification methods for highdimensional genetic data. Biocybernetics and Biomedical Engineering, 34:10-18.
  16. Kalina, J. and Zvárová, J. (2013). Decision support systems in the process of improving patient safety. In Moumtzoglou, A. and Kastania, A., editors, Bioinformatics: Concepts, Methodologies, Tools, and Applications, pages 1113-1125. IGI Global, Hershey.
  17. Lech, M., Song, I., Yellowlees, P., and Diederich, J., editors (2014). Mental health informatics, New York. Springer.
  18. Liu, J., Pearlson, G., Windemuth, A., Ruano, G., PerroneBizzozero, N., and Calhoun, V. (2009). Combining fMRI and SNP data to investigate connections between brain function and genetics using parallel ICA. Human Brain Mapping, 30:241-255.
  19. Lohoff, F. W. (2010). Overview of the genetics of major depressive disorder. Current Psychiatry Reports, 12:539-546.
  20. Marshall, E. (2011). Human genome 10th anniversary: Waiting for the revolution. Science, 331:526-529.
  21. Mitchell, P., Meiser, B., Wilde, A., Fullerton, J., Donald, J., Wilhelm, K., and Schofield, P. (2010). Predictive and diagnostic genetic testing in psychiatry. The Psychiatric Clinics of North America, 33:225-243.
  22. Pirooznia, M., Seifuddin, F., Judy, J., Mahon, P., Bipolar Genome Study (BiGS) Consortium, Potash, J., and Zandi, P. (2012). Data mining approaches for genomewide association of mood disorders. Psychiatric Genetics, 22:55-61.
  23. Prakash, A. and Potoski, M. (2012). Voluntary environmental programs: A comparative perspective. Journal of Policy Analysis and Management, 31:123-138.
  24. Sackett, D., Rosenberg, W. M. C., Gray, M. J. A., Haynes, B. R., and Richardson, W. S. (1996). Evidence based medicine: What it is and what it isn't. BMJ, 312:71- 72.
  25. Schizophrenia Working Group of the Psychiatric Genomics Consortium (2014). Biological insights from 108 schizophrenia-associated genetic loci. Nature, 511:421-427.
  26. Subramanian, J. and Simon, R. (2010). Gene expressionbased prognostic signatures in lung cancer: Ready for clinical use? Journal of National Cancer Institute, 102:464-474.
  27. Thornton, T. (2013). Clinical judgment, tacit knowledge, and recognition in psychiatric diagnosis. Oxford Handbooks Online, Oxford.
  28. Trivedi, M. H., Daly, E. J., Kern, J. K., Grannemann, B. D., Sunderajan, P., and Claassen, C. A. (2009). Barriers to implementation of a computerized decision support system for depression: An observational report on lessons learned in real world clinical settings. BMC Medical Informatics and Decision Making, 9:1-9.
  29. van Bemmel, J. H., Helder, J. C., Sollet, P. C. G. M., and ten Bergen, S. C. (1996). Handbook of medical informatics. Bohn Stafleu van Loghum, Houten.
  30. Wager, T. D., Keller, M. C., Lacey, S. C., and Jonides, J. (2005). Increased sensitivity in neuroimaging analyses using robust regression. NeuroImage, 26:99-113.
  31. Whelan, R. and Garavan, H. (2015). When optimism hurts: Inflated predictions in psychiatric neuroimaging. Biological Psychiatry, 75:746-748.
  32. Zahourek, R. P. (2008). Integrative holism in psychiatricmental health nursing. Journal of Psychosocial Nursing and Mental Health Services, 46:31-37.
  33. Zvárová, J. (2014). Information-based holistic electronic healthcare. International Journal on Biomedicine and Healthcare, 2:2-8.
  34. Zvárová, J., VeselÉ, A., and Vajda, I. (2009). Data, information and knowledge. In Berka, P., Rauch, J., and Zighed, D., editors, Data mining and medical knowledge management: Cases and applications standards, pages 1-36. IGI Global, Hershey.
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Paper Citation


in Harvard Style

Kalina J. and Zvárová J. (2016). Perspectives of Information-based Methods in Medicine: An Outlook for Mental Health Care . In Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: HEALTHINF, (BIOSTEC 2016) ISBN 978-989-758-170-0, pages 365-370. DOI: 10.5220/0005771603650370


in Bibtex Style

@conference{healthinf16,
author={Jan Kalina and Jana Zvárová},
title={Perspectives of Information-based Methods in Medicine: An Outlook for Mental Health Care},
booktitle={Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: HEALTHINF, (BIOSTEC 2016)},
year={2016},
pages={365-370},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005771603650370},
isbn={978-989-758-170-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: HEALTHINF, (BIOSTEC 2016)
TI - Perspectives of Information-based Methods in Medicine: An Outlook for Mental Health Care
SN - 978-989-758-170-0
AU - Kalina J.
AU - Zvárová J.
PY - 2016
SP - 365
EP - 370
DO - 10.5220/0005771603650370