Advertisement

A Conceptual Framework for Applying the Anticipatory Theory of Complex Systems to Improve Safety and Quality in Healthcare

  • Thomas O. StaigerEmail author
  • Patricia A. Kritek
  • Erin L. Blakeney
  • Brenda K. Zierler
  • Kurt O’Brien
  • Ross H. Ehrmantraut
Chapter

Abstract

Effective anticipation is a fundamental characteristic of highly reliable organizations. In Rosen’s anticipatory theory of complex systems, all living systems and virtually all other complex systems require anticipatory models to maintain an organized state. This paper provides an overview of Rosen’s anticipatory theory of complex systems and presents a conceptual framework for applying this framework to improve safety and quality in healthcare. Organizational interventions based on this theory could include education of clinicians, patients, and families on how anticipatory complex systems function and improve safety in clinical environments, and systems interventions to promote optimal concordance between a team’s model of a clinical situation and the actual clinical situation. Enhanced general understandings of anticipatory complex systems and of their failure modes could help reduce communications failures that are a common cause of serious adverse events.

Keywords

Anticipation Complexity Safety Quality Medicine Situational awareness Communication 

References

  1. 1.
    Chassin, M.R., Loeb, J.M.: High reliability healthcare: getting there from here. The Milbank Q. 91, 459–490 (2013)CrossRefGoogle Scholar
  2. 2.
    Leonard, M., Graham, S., Bonacum, D.: The human factor: the critical importance of effective teamwork and communication in providing safe care. Qual. Saf. Health Care 13(Suppl 1), i85–i90 (2004)CrossRefGoogle Scholar
  3. 3.
    Sturmberg, J.P., Martin, C.M., Katerndahl, D.A.: Systems and complexity thinking in the general practice literature. Ann. Fam. Med. 12, 66–74 (2014)CrossRefGoogle Scholar
  4. 4.
    Kannampallil, T.G., Schauer, G.F., Cohen, T., Patel, V.L.: Considering complexity in healthcare systems. J. Biomed. Inform. 44, 943–947 (2011)CrossRefGoogle Scholar
  5. 5.
    Weick, K.E., Sutcliffe, K.M.: Managing the Unexpected. Wiley, San Francisco (2007)Google Scholar
  6. 6.
    Rosen, R.: Anticipatory Systems. Philosophic, Mathematic, and Methodological Foundations, 2nd edn. Springer, New York (2012)Google Scholar
  7. 7.
    Nadin, M.: Anticipation (special issue). Int. J. Gen Syst 39(1), 35–133 (2010)CrossRefzbMATHGoogle Scholar
  8. 8.
    Nadin, M.: Mind—Anticipation and Chaos (Milestones in Research and Discovery). Belser Presse, Stuttgart/Zurich (1991)Google Scholar
  9. 9.
    Nadin, M.: Anticipation—The End Is Where We Start From. Müller Verlag, Basel (2003)Google Scholar
  10. 10.
    Zadeh, L.A.: Fuzzy sets as a basis for theory of possibility. Fuzzy Sets Syst. 1, 3–28 (1978)MathSciNetCrossRefzbMATHGoogle Scholar
  11. 11.
    Staiger, T.O.: Anticipation in complex systems: potential implications for improving safety and quality in healthcare. In: Proceedings of the First International Conference on Systems and Complexity in Healthcare (In press)Google Scholar
  12. 12.
    Louie, A.H.: Robert Rosen’s anticipatory systems. Foresight 12, 18–29 (2010)CrossRefGoogle Scholar
  13. 13.
    Miller-Keane, O’Toole, M.T.: Miller-Keane Encyclopedia and Dictionary of Medicine, Nursing, and Allied Health, 7th edn. Elsevier, Amsterdam (2003)Google Scholar
  14. 14.
    Gen Script Glossary of Biochemistry and Molecular Biology “feed-forward regulation”. http://www.google.com/webhp?nord=1#nord=1&q=gen+script+glossary+of+biochemistry
  15. 15.
    Rosen, R.: Life Itself. Columbia University Press, New York (1991)Google Scholar
  16. 16.
    Rouse, W.B.: Health care as a complex adaptive system. The Bridge 38, 17–25 (2008)Google Scholar
  17. 17.
    Rosen, R.: Fundamentals of Measurement and Representations of Natural Systems. North-Holland, New York (1978)Google Scholar
  18. 18.
    Rosen, R.: Feedforwards and global system failure: a general mechanism for senescence. J. Theor. Biol. 74, 579–590 (1978)CrossRefGoogle Scholar
  19. 19.
    Rock, R.: SCARF: a brain-based model for collaborating with and influencing others. Neuroleadership J., 1–9 (2008)Google Scholar
  20. 20.
    Romero-Brufau, S., Gaines, K., Huddleston, J.: Nurses’ ability to identify physiological deterioration of hospitalized patients. In: 11th International Conference on Rapid Response Systems and Medical Emergency Teams. Amsterdam (2015)Google Scholar
  21. 21.
  22. 22.
    Starmer, A.J., Spector, N.D., Srivastava, R., et al.: I-PASS, a mnemonic to standardize verbal handoffs. Pediatrics 129, 201–204 (2012)CrossRefGoogle Scholar
  23. 23.
    Staiger, T.O., Jarvik, J.G., Deyo, R.A., Martin, B., Braddock, C.B.: Patient-physician agreement as a predictor of outcomes in patients with back pain. JGIM 20, 935–937 (2005)CrossRefGoogle Scholar
  24. 24.
    Zehnder, R., Staiger, T.O.: Association between patient-physician agreement and outcomes in primary care. In: Society of General Internal Medicine. Northwest Regional Meeting. Seattle (2006)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2017

Authors and Affiliations

  • Thomas O. Staiger
    • 1
    Email author
  • Patricia A. Kritek
    • 1
  • Erin L. Blakeney
    • 2
  • Brenda K. Zierler
    • 2
  • Kurt O’Brien
    • 3
  • Ross H. Ehrmantraut
    • 3
  1. 1.Department of MedicineUniversity of WashingtonSeattleUSA
  2. 2.School of Nursing University of WashingtonSeattleUSA
  3. 3.UW Medicine Organizational Development and TrainingUniversity of WashingtonSeattleUSA

Personalised recommendations