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Biomedical Data: Their Acquisition, Storage, and Use

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Biomedical Informatics

Abstract

This chapter provides fundamental background about the nature of clinical data and decision making, which will be required for understanding the field of biomedical informatics. It describes various types of clinical data, how clinical data are collected and used by medical professionals, and how they support medical practice and clinical research. It also discusses the rationale behind the transition from paper records to electronic health records (EHRs) for representing clinical data. This chapter concludes with a discussion of the relationship between concepts of data, information, and knowledge, and by introducing concepts relevant to medical decision-making such as sensitivity, specificity, and Bayes’ theorem.

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Notes

  1. 1.

    Note that it was the tendency to record such dates in computers as “14FEB12” that led to the end-of-century complexities that were called the Year 2K problem. It was shortsighted to think that it was adequate to encode the year of an event with only two digits.

  2. 2.

    Big Data Senior Steering Group. The Federal Big Data Research and Development Strategic Plan. Available at: 7 https://obamawhitehouse.archives.gov/sites/default/files/microsites/ostp/NSTC/bigdatardstrategicplan-nitrd_final-051916.pdf (Accessed 6/28/2019).

  3. 3.

    7 http://www.icd10data.com/ (Accessed 11/1/2019).

  4. 4.

    7 http://snomed.org/ (Accessed 5/6/2019).

References

  • Adler-Milstein, J., & Jha, A. K. (2013). Healthcare’s “big data” challenge. American Journal of Managed Care, 19(7), 537–538.

    Google Scholar 

  • Arocha, J. F., Wang, D., & Patel, V. L. (2005). Identifying reasoning strategies in medical decision making: A methodological guide. Journal of Biomedical Informatics, 38(2), 154–171.

    Article  Google Scholar 

  • Bernstam, E. V., Smith, J. W., & Johnson, T. R. (2010). What is biomedical informatics? Journal of Biomedical Informatics, 43(1), 104–110.

    Article  Google Scholar 

  • Blum, B. I. (1986). Clinical information systems: A review. Western Journal of Medicine, 145(6), 791–797.

    CAS  PubMed Central  Google Scholar 

  • Brennan, P. F., Chiang, M. F., & Ohno-Machado, L. (2018). Biomedical informatics and data science: Evolving fields with significant overlap. Journal of the American Medical Informatics Association, 25(1), 2–3.

    Article  Google Scholar 

  • Bycroft, C., Freeman, C., Petkova, D., Band, G., Elliott, L. T., Sharp, K., et al. (2018). The UK Biobank resource with deep phenotyping and genomic data. Nature, 562(7726), 203–209.

    Article  CAS  Google Scholar 

  • Elstein, K. A., Shulman, L. S., & Sprafka, S. A. (1978). Medical problem solving: An analysis of clinical reasoning. Cambridge, MA: Harvard University Press.

    Book  Google Scholar 

  • Erlich, Y., & Zielinski, D. (2017). DNA Foundation enables a robust and efficient storage architecture. Science, 355, 950–954.

    Article  CAS  Google Scholar 

  • Haendel, M. A., Chute, C. G., & Robinson, P. N. (2018). Classification, ontology, and precision medicine. New England Journal of Medicine, 379, 1452–1462.

    Article  CAS  Google Scholar 

  • Hirsch, J. A., Leslie-Mazwi, T. M., Nocola, G. N., Barr, R. M., Bello, J. A., Donovan, W. D., et al. (2015). Current procedural terminology; a primer. Journal of Neurointerventional Surgery, 7(4), 309–312.

    Article  Google Scholar 

  • Humphreys, B., Lindberg, D., Schoolman, H., & Barnett, G. (1998). The unified medical language system: An informatics research collaboration. Journal of the American Medical Informatics Association: JAMIA, 5, 1–11.

    Article  CAS  Google Scholar 

  • Kassirer, J. P., & Gorry, G. A. (1978). Clinical problem solving: A behavioral analysis. Annals of Internal Medicine, 89(2), 245–255.

    Article  CAS  Google Scholar 

  • Lee, D., de Keizer, N., Lau, F., & Cornet, R. (2014). Literature review of SNOMED CT use. Journal of the American Medical Informatics Association, 21(e1), e11–e19.

    Article  Google Scholar 

  • Masys, D. R., Jarvik, G. P., Abernethy, N. F., Anderson, N. R., Papanicolaou, G. J., Paltoo, D. N., et al. (2012). Technical desiderata for the integration of genomic data into electronic health records. Journal of Biomedical Informatics, 45(3), 419–422.

    Article  Google Scholar 

  • Pauker, S. G., Gorry, G. A., Kassirer, J. P., & Scwartz, W. B. (1976). Towards the simulation of clinical cognition: Taking a present illness by computer. American Journal of Medicine, 60(7), 981–996.

    Article  CAS  Google Scholar 

  • Relling, M. V., & Evans, W. E. (2015). Pharmacogenomics in the clinic. Nature, 526(7573), 342–350.

    Article  Google Scholar 

  • Sanders, D. S., Lattin, D. J., Read-Brown, S., Tu, D. C., Wilson, D. J., Hwang, T. S., et al. (2013). Electronic health record systems in ophthalmology: Impact on clinical documentation. Ophthalmology, 120, 1745–1755.

    Article  Google Scholar 

  • Senior Medical Review (1987). Urinary tract infections. Senior Medical Review Newsletter.

    Google Scholar 

  • Shortliffe, E. H. (2010). Biomedical informatics in the education of physicians. Journal of the American Medical Association, 304(11), 1227–1228.

    Article  CAS  Google Scholar 

  • Stearns, M. Q., Price, C., Spackman, K. A., & Wang, A. Y. (2001). SNOMED clinical terms: Overview of the development process and project status. Proceedings of the AMIA Symposium, 662–666.

    Google Scholar 

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Correspondence to Edward H. Shortliffe .

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Shortliffe, E.H., Chiang, M.F. (2021). Biomedical Data: Their Acquisition, Storage, and Use. In: Shortliffe, E.H., Cimino, J.J. (eds) Biomedical Informatics. Springer, Cham. https://doi.org/10.1007/978-3-030-58721-5_2

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  • DOI: https://doi.org/10.1007/978-3-030-58721-5_2

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