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Towards a Deeper Understanding of Conceptual Models that Incorporate Patient Safety

  • Timothy ArnoldEmail author
  • Helen J. A. Fuller
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 957)

Abstract

Over the past decades, researchers, clinicians, and engineers have introduced many different conceptual models that incorporate patient safety. These models share similarities in some dimensions but may differ in others. A hermeneutic and natural language processing approach was utilized to interpret relevant literature on this subject. This descriptive account provides philosophical considerations that help to frame understanding of these models. The aim is to facilitate greater understanding of safety in health care.

Keywords

Patient safety Conceptual models Human factors Language Natural language processing Hermeneutics Philosophy of patient safety 

Notes

Acknowledgments

We would like to thank everybody at the National Center for Patient Safety for their commitment to patient safety. Also, we thank S. D. McKnight for fostering a climate that values philosophy and the manifestation of imagination. There were no relevant financial relationships or any source of support in the forms of grants, equipment, or drugs. The authors declare no conflict of interest. The opinions expressed in this article are those of the authors and do not necessarily represent those of the Veterans Administration.

References

  1. 1.
    Carayon, P., Hundt, A.S., Karsh, B.T., Gurses, A.P., Alvarado, C.J., Smith, M., Brennan, P.F.: Work system design for patient safety: the SEIPS model. BMJ Qual. Saf. 15(suppl 1), i50–i58 (2006)CrossRefGoogle Scholar
  2. 2.
    Sittig, D.F., Singh, H.: A new sociotechnical model for studying health information technology in complex adaptive healthcare systems. BMJ Qual. Saf. 19(Suppl 3), i68–i74 (2010)CrossRefGoogle Scholar
  3. 3.
    Manojlovich, M., Hofer, T.P., Krein, S.L.: Advancing patient safety through the clinical application of a framework focused on communication. J. Patient saf. 00(00), 1–6 (2018)CrossRefGoogle Scholar
  4. 4.
    Nystrom, D.T., Williams, L., Paull, D.E., Graber, M.L., Hemphill, R.R.: A theory-integrated model of medical diagnosis. J. Cogn. Eng. Decis. Making 10(1), 14–35 (2016)CrossRefGoogle Scholar
  5. 5.
    Nilsen, P.: Making sense of implementation theories, models and frameworks. Implement. Sci. 10(1), 53 (2015)CrossRefGoogle Scholar
  6. 6.
    Boell, S.K., Cecez-Kecmanovic, D.: Literature reviews and the hermeneutic circle. Aust. Acad. Res. Libr. 41(2), 129–144 (2010)CrossRefGoogle Scholar
  7. 7.
    Arnold, T., Fuller, H.J.: A linguistic approach for facilitating interpretation of human factors and ergonomics symposium proceedings: an efficient method for real-time literature review. In: Proceedings of the International Symposium on Human Factors and Ergonomics in Health Care, June 2018Google Scholar
  8. 8.
    Nersessian, N.J.: Creating Scientific Concepts. MIT Press, Cambridge (2010)Google Scholar
  9. 9.
    Rokach, L.: Pattern Classification Using Ensemble Methods, vol. 75. World Scientific, Singapore (2010)zbMATHGoogle Scholar
  10. 10.
    Sherratt, Y.: Continental Philosophy of Social Science: Hermeneutics, Genealogy, and Critical Theory from Greece to the Twenty-first Century. Cambridge University Press, Cambridge (2006)Google Scholar
  11. 11.
    Megaputer Intelligence.: PolyAnalyst™ Professional: Version 6.5.2030 [Data & Text Analysis software]. Bloomington, Indiana (2019)Google Scholar
  12. 12.
    Westergaard, D., Stærfeldt, H.H., Tønsberg, C., Jensen, L.J., Brunak, S.: A comprehensive and quantitative comparison of text-mining in 15 million full-text articles versus their corresponding abstracts. PLoS Comput. Biol. 14(2), e1005962 (2018)CrossRefGoogle Scholar
  13. 13.
    Rasmussen, J.: Risk management in a dynamic society: a modelling problem. Saf. Sci. 27(2–3), 183–213 (1997)CrossRefGoogle Scholar
  14. 14.
    Taylor, D.H.: The hermeneutics of accidents and safety. Ergonomics 24(6), 487–495 (1981)CrossRefGoogle Scholar
  15. 15.
    Le Coze, J.C.: Reflecting on Jens Rasmussen’s legacy. A strong program for a hard problem. Saf. Sci. 71, 123–141 (2015)CrossRefGoogle Scholar
  16. 16.
    Dekker, S.: The Field Guide to Understanding ‘Human Error’. CRC Press, Boca Raton (2006)Google Scholar
  17. 17.
    Dekker, S.: The Field Guide to Understanding ‘Human Error’, 3rd edn. CRC Press, Boca Raton (2014)Google Scholar
  18. 18.
    Morel, G., Amalberti, R., Chauvin, C.: Articulating the differences between safety and resilience: the decision-making process of professional sea-fishing skippers. Hum. Factors 50(1), 1–16 (2008)CrossRefGoogle Scholar
  19. 19.
    Rogers, E.M.: Diffusion of Innovations. Simon and Schuster, New York (2010)Google Scholar
  20. 20.
    Hollnagel, E.: Is safety a subject for science? Saf. Sci. 67, 21–24 (2014)CrossRefGoogle Scholar
  21. 21.
    Collins, M.E., Block, S.D., Arnold, R.M., Christakis, N.A.: On the prospects for a blame-free medical culture. Soc. Sci. Med. 69(9), 1287–1290 (2009)CrossRefGoogle Scholar
  22. 22.
    Gibson, J.J.: The Ecological Approach to Visual Perception, Classic edn. Psychology Press, New York (2014)CrossRefGoogle Scholar
  23. 23.
    Lyons, L., Lee, J., Quintana, C., Soloway, E.: MUSHI: a multi-device framework for collaborative inquiry learning. In: Proceedings of the 7th international conference on Learning sciences, pp. 453–459. International Society of the Learning Sciences, June 2006Google Scholar
  24. 24.
    Chandrasekharan, S., Nersessian, N.J.: Building cognition: the construction of computational representations for scientific discovery. Cogn. Sci. 39(8), 1727–1763 (2015)CrossRefGoogle Scholar
  25. 25.
    Quinn, A.J., Bederson, B.B.: A taxonomy of distributed human computation. Human-Computer Interaction Lab Tech Report, University of Maryland (2009)Google Scholar
  26. 26.
    Fong, A., Ratwani, R.: An evaluation of patient safety event report categories using unsupervised topic modeling. Methods Inf. Med. 54(04), 338–345 (2015)CrossRefGoogle Scholar
  27. 27.
    De Bie, A.J.R., Nan, S., Vermeulen, L.R.E., Van Gorp, P.M.E., Bouwman, R.A., Bindels, A.J.G.H., Korsten, H.H.M.: Intelligent dynamic clinical checklists improved checklist compliance in the intensive care unit. BJA: Br. J. Anaesth. 119(2), 231–238 (2017)CrossRefGoogle Scholar
  28. 28.
    Arnold, T., Fuller, H.J.: Local lexicon extraction and language processing in facilitating language awareness and informing user-centered design in the health care environment. In: Proceedings of the International Symposium on Human Factors and Ergonomics in Health Care, vol. 6, No. 1, pp. 97–103. Sage India, New Delhi (2017, June)CrossRefGoogle Scholar
  29. 29.
    Ilgen, J.S., Eva, K.W., de Bruin, A., Cook, D.A., Regehr, G.: Comfort with uncertainty: reframing our conceptions of how clinicians navigate complex clinical situations. Adv. Health Sci. Educ. 1–13 (2018)Google Scholar
  30. 30.
    Bryan, C.S., Call, T.J., Elliott, K.C.: The ethics of infection control: philosophical frameworks. Infect. Control Hosp. Epidemiol. 28(9), 1077–1084 (2007)CrossRefGoogle Scholar
  31. 31.
    Gadamer, H.G.: The Enigma of Health: The art of Healing in a Scientific Age. Stanford University Press, Stanford (1996)Google Scholar
  32. 32.
    Gadamer, H.G.: Truth and Method, 2013th edn. Bloomsbury, London (2013)Google Scholar

Copyright information

© This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply 2020

Authors and Affiliations

  1. 1.National Center for Patient SafetyAnn ArborUSA
  2. 2.University of Michigan, College of PharmacyAnn ArborUSA

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