Cognitive Approaches to Clinical Data Management for Decision Support: Is It Old Wine in New Bottle?

  • Vimla L. Patel
  • Thomas G. Kannampallil
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7058)

Abstract

Most current health information technology (HIT) is not designed to support the cognitive aspects of clinicians decision-making task. We propose a case for cognitive support systems (CSS), a class of support systems whose design rationale is based on aligning the decision making process closely with the empirical results on clinicians organization of knowledge structures. Using examples drawn from our current and past studies, we explain an epistemological framework of medical knowledge and how experts’ representations could be better visualized within CSS for efficient and safe decision making. We discuss the state of the current research as well as the challenges for the development of patient-centered decision support, and the cognitive support for other members of the healthcare team, all within the constraints of clinical workflow.

Keywords

cognitive support systems clinical decision making intermediate constructs knowledge elicitation knowledge representation cognitive science 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Kintsch, W.: The role of knowledge in discourse comprehension construction-integration model. Psychological Review 95, 163–182 (1988)CrossRefGoogle Scholar
  2. 2.
    Groen, G.J., Patel, V.L.: Relationship Between Comprehension and Reasoning in Medical Expertise. Lawrence Erlbaum (1988)Google Scholar
  3. 3.
    Patel, V.L., Arocha, J.F., Kaufman, D.R.: Diagnostic Reasoning and Expertise. The Psychology of Learning and Motivation: Advances in Research and Theory 31, 137–252 (1994)Google Scholar
  4. 4.
    Ericsson, K.A.: The road to excellence: the acquisition of expert performance in the arts and sciences, sports and games. Lawrence Erlbaum (1996)Google Scholar
  5. 5.
    Patel, V.L., Groen, G.J.: Knowledge-based solution strategies in medical reasoning. Cognitive Science 10, 91–116 (1986)CrossRefGoogle Scholar
  6. 6.
    Patel, V.L., Groen, G.J.: The General and Specific Nature of Medical Expertise: A Critical Look. In: Ericsson, A., Smith, J. (eds.) Towards a General Theory of Expertise: Prospects and Limits, pp. 93–125. Cambridge University Press, Cambridge (1991)Google Scholar
  7. 7.
    Patel, V.L., Kaufman, D.R.: Cognitive science and biomedical informatics. In: Shortliffe, E.H., Cimino, J.J. (eds.) Biomedical Informatics: Computer Applications in Health Care and Biomedicine, 3rd edn., pp. 133–185. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  8. 8.
    Patel, V.L., Evans, D.A., Kaufman, D.R.: Cognitive framework for doctor-patient interaction. In: Evans, D.A., Patel, V.L. (eds.) Cognitive Science in Medicine: Biomedical Modeling, pp. 253–308. MIT Press, Cambridge (1989)Google Scholar
  9. 9.
    Patel, V.L., Kaufman, D.R.: Clinical Reasoning and Biomedical Knowledge. In: Higgs, J., Jones, M. (eds.) Clinical Reasoning in the Health Professions, pp. 117–128. Butterworth Heinemann, Oxford (1995)Google Scholar
  10. 10.
    Miller, R.A., Pople, H.E., Myers, J.D.: INTERNIST-1: An Experimental Computer-Based Diagnostic Consultant for General Internal Medicine. New England Journal of Medicine 19, 307 (1982)Google Scholar
  11. 11.
    Patel, V.L., Kaufman, D.R., Arocha, J.F.: Emerging Paradigms of Cognition and Medical Decision Making. Journal of Biomedical Informatics 35, 52–75 (2002)CrossRefGoogle Scholar
  12. 12.
    Norman, G.R., Coblentz, C.L., Brooks, L.R., Babcook, C.J.: Expertise in visual diagnosis: a review of the literature. Academic Medicine 67, 78–83 (1992)CrossRefGoogle Scholar
  13. 13.
    Sharda, P., Das, A., Cohen, T., Patel, V.L.: Customizing clinical narratives for the electronic medical record interface using cognitive methods. International Journal of Medical Informatics 75, 346–368 (2006)CrossRefGoogle Scholar
  14. 14.
    Chase, H., Simon, H.A.: Perception in Chess. Cognitive Psychology 4, 55–81 (1973)CrossRefGoogle Scholar
  15. 15.
    Shortliffe, E.H., Patel, V.L.: Generation and Formulation of Knowledge: Human-Intensive Techniques. In: Greenes, R.A. (ed.) Clinical Decision Support - The Road Ahead, pp. 207–226. Elsevier (2007)Google Scholar
  16. 16.
    Ericsson, K.A., Simon, H.A.: Protocol Analysis: Verbal Reports as Data. MIT Press (1993)Google Scholar
  17. 17.
    Cañas, A.J., Novak, J.D.: A concept map-centered learning environment. In: Proceedings of the 11th Biennial Conference of the European Association for Research in Learning and Instruction, EARLI (2005)Google Scholar
  18. 18.
    Patel, V.L., Arocha, J.F.: Cognitive models of clinical reasoning and conceptual representation. Methods of Information in Medicine 34(1), 1–10 (1995)Google Scholar
  19. 19.
    Cañas, A.J., Hill, G., Carff, R., Suri, N., Lott, J., Eskridge, T.: CmapTools: A knowledge modeling and sharing environment (2004) Google Scholar
  20. 20.
    Simon, H.A.: Structure of ill-structured problems. Artificial Intelligence 4(3-4), 181–201 (1973)CrossRefGoogle Scholar
  21. 21.
    Simon, H.A.: The Sciences of the Artificial. MIT Press (1996)Google Scholar
  22. 22.
    Hassebrock, F., Prietula, M.J.: A Protocol-Based Coding Scheme for the Analysis of Medical Reasoning. International Journal of Man-Machine Studies 37(5), 613–652 (1992)CrossRefGoogle Scholar
  23. 23.
    Cohen, T., Kannampallil, T.G., Patel, V.L.: Perils of Thoughtless Design: A Case for Cognitive Support Systems Under Review (2011)Google Scholar
  24. 24.
    Lamping, J., Rao, R., Pirolli, P.: A Focus+Context Technique Based on Hyperbolic Geometry for Visualizing Large Hierarchies. In: Proceedings of the Proc. ACM Conf. Human Factors in Computing Systems, CHI (1995)Google Scholar
  25. 25.
    Gottipati, D., Nguyen, V., Myneni, S., Almoosa, K.L., Kannampallil, T.G., Patel, V.L.: Information Integration Model in Critical Care Setting: Role of Electronic Health Records. In: Proceedings of the AMIA Annual Symposium (2011)Google Scholar
  26. 26.
    Stead, W., Lin, H.: Computational Technology for Effective Health Care: Immediate Steps and Strategic Directions. National Research Council (2009)Google Scholar
  27. 27.
    Agency for Healthcare Research and Quality U.S. Department of Health and Human Services, C. N. Challenges and Barriers to Clinical Decision Support (CDS) Design and Implementation Experienced in the Agency for Healthcare Research and Quality CDS Demonstrations (2010)Google Scholar
  28. 28.
    Ash, J.S., Sittig, D.F., Poon, E.G., Guappone, K., Campbell, E., Dykstra, R.H.: The extent and importance of unintended consequences related to computerized provider order entry. Journal of American Medical Informatics Association 14, 415–423 (2007)CrossRefGoogle Scholar
  29. 29.
    Bloomrosen, M., Starren, J., Lorenzi, N.M., Ash, J.S., Patel, V.L., Shortliffe, E.H.: Anticipating and addressing the unintended consequences of health IT and policy: a report from the AMIA 2009 Health Policy Meeting. Journal of American Medical Informatics Association 18(1), 82–90 (2011)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Vimla L. Patel
    • 1
  • Thomas G. Kannampallil
    • 2
  1. 1.Center for Cognitive Studies in Medicine and Public HealthNew York Academy of MedicineNew YorkUSA
  2. 2.Center for Cognitive Informatics and Decision Making, School of Biomedical InformaticsUniversity of Texas Health Science CenterHoustonUSA

Personalised recommendations