Understanding, Navigating and Communicating Knowledge: Issues and Challenges

Abstract

This paper presents a psychological perspective on key issues related to medical vocabularies. There have been rapid advances in the development of computer technology underlying medical information systems. However, in keeping with technological progress, we must also take into account advances in our understanding of human behaviour and learn frOm failures in human performance. A central issue examined in this paper is the extent to which we can develop generic vocabularies that are also flexible and adaptable to specific situations. Empirical research indicates that variability in human performance is much greater than what current medical classifications take into account. A related challenge is that of how to best develop vocabularies that meet the needs of users. Based on theoretical perspectives and research emerging from the domain of cognitive psychology, we suggest that an understanding of the cognitive mechanisms underlying the comprehension and application of terminology is required. It is argued that rather than beginning with highly specified terminologies, i.e. the normative approach, we might instead begin by examining the natural context of how health care workers acquire, understand and negotiate knowledge in practice.

Keywords

Medical Vocabularies - Cognition - Knowledge Representation - Cognitive Evaluation

• REFERENCES

• 1 Evans DA, Cimino JJ, Hersh WR, Huff SM, Bell DS. Toward a medical-concept representation language. JAMIA 1994; 1 (3) 207-17.
• 2 Chute CG, Cohn SP, Campbell KE, Oliver DE, Campbell JR. The content coverage of clinical classifications. JAMIA 1996; 3 (3) 224-33.
• 3 Patel VL, Arocha JF. Cognitive models of clinical reasoning and conceptual representation. Meth Inform Med 1995; 34: 47-56.
• 4 Weaver CA, Mannes S, Fletcher CR. Discourse comprehension: Essays in honor of Walter Kintsch. Hillsdale, NJ: Lawrence Erlbaum Associates; 1995
• 5 Groen GJ, Patel VL. The relationship between comprehension and reasoning in medical expertise. In: Chi MT, Glaser R, Farr M. eds. The Nature of Expertise. Hillsdale, NJ: Lawrence Erlbaum Associates; 1988
• 6 Arocha JF, Patel VL. Construction-integration theory and clinical reasoning. In: Weaver CA, Mannes S, Fletcher CR. eds. Discourse comprehension: Essays in honor of Walter Kintsch. Hillsdale, NJ: Lawrence Erlbaum Associates; 1995
• 7 Kintsch W. The role of knowledge in discourse comprehension: A construction-integration model. Psychological review 1988; vol. 95 no. 2 163-82.
• 8 Patel VL, Arocha JF, Kaufman DR. Diagnostic reasoning and medical expertise. The Psychology of Learning and Motivation 1994; 31: 189-252.
• 9 Kushniruk AW, Patel VL, Fleiszer D. Analysis of medical decision making: A cognitive perspective on medical informatics. In: Gardner RM. ed. Proceedings of the Nineteenth Annual Symposium on Computer Applications in Medical Care. 1995: 193-7.
• 10 Patel VL, Groen GJ. The general and specific nature of medical expertise: A critical look. In: Ericsson KA, Smith J. eds. Toward a General Theory of Expertise. Cambridge: Cambridge University Press; 1991
• 11 Schmalhofer F, Tschaitschian B. Cooperative knowledge evolution: A construction-integration approach to knowledge discovery in medicine. Meth Inform Med 1998; 37: 491-500.
• 12 Norman DA. The psychology of everyday things. New York: Basic Books; 1988
• 13 Kushniruk AW, Patel VL. Cognitive computer-based video analysis: Its application in assessing the usability of medical systems. In: Greenes RA, Peterson HE, Protti DF. eds. Proceedings of the Eighth World Congress on Medical Informatics. New York, North Holland: 1995: 1566-9.
• 14 Kushniruk AW, Kaufman DR, Patel VL, Levseque Y, Lottin P. Assessment of a computerized patient record system: A cognitive approach to evaluating medical technology. MD Computing 1996; vol. 13 no. 5 406-15.
• 15 Simon HA. The structure of ill structured problems, Artificial Intelligence. 1973 4. 145-80.
• 16 Sowa JF. Conceptual analysis for knowledge-base design. Meth Inform Med 1995; 34: 165-71.
• 17 Patel VL, Evans DA, Kaufman DR. Cognitive framework for doctor-patient interaction. In: Evans DA, Patel VL. eds. Cognitive Science in Medicine: Biomedical Modeling. Cambridge, MA: MIT Press; 1989: 253-308.
• 18 Patel VL. Expert-novice differences in clinical text understanding. Technical Report #CME84-CS3, Centre for Medical Education. McGill University; Montreal, Quebec, Canada.:
• 19 Furnas GW, Landauer TK, Gomez LM, Dumais ST. The vocabulary problem in human-system communication. Communications of the ACM 1987; 30 (11) 964-71.
• 20 Furnas GW, Landauer TK, Gomez LM, Dumais ST. Statistical semantics: Analysis of the potential performance of keyword information systems. In: Thomas J, Schneider M. Human Factors in Computer Systems. Ablex: 1984
• 21 Clancey WJ. The learning process in the epistemology of medical information. Meth Inform Med 1995; 34: 122-30.
• 22 Nielsen J. Usability engineering. New York: Academic Press; 1993
• 23 Kushniruk AW, Patel VL, Cimino JJ, Barrows RA. Cognitive evaluation of the user interface and vocabulary of an outpatient information system. In: Cimino JJ. ed. Proceedings of the 1996 AMIA Fall Symposium. 1996. Philadelphia: Hanley & Belfus Inc.; 22-6.
• 24 Rogers E. A cognitive theory of visual interpretation. In: Chandrasekaran B, Glasgow J, Narayanan NH. eds. Diagrammatic Reasoning: Cognitive and Computational Perspec tives. Menlo Park, CA: AAAI Press; 1995
• 25 Lesgold A, Rubinson H, Feltovich P, Glaser R, Klopger D, Wang Y. Expertise in a complex skill: Diagnosing x-ray pictures. In: Chi M, Glaser R, Farr MJ. eds. The nature of expertise. Hillsdale NJ: Erlbaum,; 1988: 311-42.
• 26 Nygren E. Human information processing and interfaces to patient data. Proceedings of the IMIA WG6 Conference. 1997
• 27 Nygren E, Henriksson P. Reading the medical record I.: Analysis of physicians' way of reading the medical record. Computer Methods and Programs in Biomedicine 1997; 39: 1-12.
• 28 Preece J, Rogers Y, Sharp H, Benyon D, Holland S, Carey T. Human-computer interaction. New York: Addison-Wesley Publishing Co.; 1994
• 29 Tuttle MS, Cole WG, Sheretz DD, Nelson SJ. Navigating to knowledge. Meth Inform Med 1995; 34: 214-31.
• 30 Cole WG, Tuttle MS, Sheretz DD. Cognitive design and evaluation of user interfaces. Proceedings of the IMIA WG6 Conference. 1997
• 31 Nielsen J. Multimedia and beyond. New York: AP Professional; 1995
• 32 Folz PW, Dumais ST. Personalized information delivery: An analysis of information filtering methods. Communications of the ACM 1992; 35 (12) 51-60.
• 33 Chute CG, Yang Y. An overview of statistical methods for the classification and retrieval of patient events. Meth Inform Med 1995; 34: 104-10.
• 34 Garrod S, Doherty G. Conversation, coordination and convention: An empirical investigation of how groups establish linguistic convention. Cognition 1994; 53: 181-25.
• 35 Garrod S. How groups co-ordinate their concepts and terminology: Implications for medical informatics. Meth Inform Med 1998; 37: 471-6.
• 36 Patel VL, Evans DA, Groen GJ. Reconciling knowledge and reasoning. In: Evans DA, Patel VL. eds. Cognitive Science in Medicine: Biomedical Modeling. Cambridge, MA: The MIT Press,; 1989: 53-112.
• 37 Shortliffe EH, Barnett GO, Cimino JJ, Greenes RA, Huff SM, Patel VL. Collaborative medical informatics research using the Internet and the World Wide Web. In: Cimino JJ. ed. Proceedings of the 1996 AMIA Fall Symposium. Philadelphia: Hanley & Belfus Inc.,; 1996: 125-9.
• 38 Shortliffe EH, Patel VL, Cimino JJ, Barnett O, Greenes RA. A study of collaboration among medical informatics research laboratories. AI Med 1998; 12: 97-123.