Three Methods for Aiding Clinical Decision Making

  • George Wright
  • Kee-On Ng


The mathematical techniques to-be presented are intended as aids to the clinician’s decision making.1 The methods to be introduced do not imply that a mathematical model or theory implemented by computer can replace the clinician. The work we are about to discuss shows that decision aids, utilising the clinician’s knowledge and expertise, can improve on unaided judgement and choice. Diagnosis, prognosis and treatment decisions made under conditions of uncertainty and including the clinician’s differential valuation of the consequences of the decisions, can be improved. This extra precision is due to the optimal combination of the information the clinician already possesses rather than the clinician’s access to extra information.


Decision Analysis Subjective Probability Brain Damage Prior Opinion Subjective Expected Utility 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. Beach, B.H., 1975, Expert judgement about uncertainty: Bayesian decision making in realistic settings, Org. Beh. & Hum. Perf., 14:10.CrossRefGoogle Scholar
  2. Brown, R.V., Kahr., A.S., and Peterson, C., 1974, “Decision Analysis for the Manager,” Holt, Rinehart & Winston, New York.Google Scholar
  3. Christensen-Szalanski, J.J.J., and Bushyhead, J.B., 1979, Decision analysis as a descriptive model of physician decision making, Technical Rep., 79-45, Department of Health Services Research, University of Washington.Google Scholar
  4. Christensen-Szalanski, J.J.J., and Bushyhead, J.B., in press, Physicians’ use of probabilistic information in a real clinical setting, J. Exp. Psychol.Google Scholar
  5. Dawes, R.M., 1975, Graduate admission variables and future success, Science, 187:721.PubMedCrossRefGoogle Scholar
  6. Dawes, R.M., and Corrigan, B., 1974, Linear models in decision making, Psychol. Bull., 81:95.CrossRefGoogle Scholar
  7. Diamond, G.A., and Forrester, J.S., 1979, Diagnosis of coronary heart disease, New Eng. J. Med., 300:1350.PubMedCrossRefGoogle Scholar
  8. Edwards, W., Lindman, H., and Phillips, L.D., 1966, Emerging technologies for making decision, in: “New Directions in Psychology 11,” T.M. Newcomb, ed., Holt, Rinehart & Winston, New York.Google Scholar
  9. Emerson, P.A., Teather, D., and Handley, A.J., 1974, The application of decision theory to prevention of deep vein thrombosis following myocardial infarction, Quart. J. Med., New Series, XLIII, 171:389.Google Scholar
  10. Fischhoff, B., and Beyth, R., 1975, I knew it would happen: Remembered probabilities of once-future things, Org. Beh. & Hum. Perf., 13:1.CrossRefGoogle Scholar
  11. Goldberg, L.R., 1965, Diagnosticians versus diagnostic signs: the diagnosis of psychosis versus neurosis from the MMPI, Psycho1. Monogs., 79:602.Google Scholar
  12. Graham, R.K., and Kendall, B.S., 1960, Memory-for-designs test: revised general manual, Perc. & Mot. Skills, 11:147.Google Scholar
  13. Hogarth, R.M., 1975, Cognitive processes and the assessment of subjective probability distributions, J. Amer. Stat. Assoc, 70:721.CrossRefGoogle Scholar
  14. Lichenstein, S., Fischhoff, B., and Phillips, L.D., 1977, Calibration of probabilities: the state of the art, in: “Decision Making and Change in Human Affairs,” H. Jungerman & G. de Zeeuw, eds., D. Reidel, Amsterdam.Google Scholar
  15. Meehl, P.E., 1959, A comparison of clinicians with five statistical methods of identifying psychotic MMPI profiles, J. Coun. Psychol., 6:102.CrossRefGoogle Scholar
  16. Peterson, C.R., and Beach, L.R., 1967, Man as an intuitive statistician, Psychol. Bull., 68:29.PubMedCrossRefGoogle Scholar
  17. Phillips, L.D., 1973, “Bayesian Statistics for Social Scientists,” Nelson, London.Google Scholar
  18. Pliskin, J.S., and Beck, C.H., 1976, Decision analysis in individual clinical decision making: a real world application in treatment of renal disease, Methods Info. Med., 15:43.Google Scholar
  19. Raiffa, H., 1968, “Decision Analysis: Introductory Lectures on Choices Under Uncertainty,” Addison-Wesley, Reading, Mass.Google Scholar
  20. Schwartz., W.B., 1979, Decision analysis: a look at the chief complaints, New Eng. J. Med., 300:556.PubMedCrossRefGoogle Scholar
  21. Schwartz, W.B., Gorry, G.A., Kassirer, J.P., and Essig, A., 1973, Decision analysis and clinical judgement, The Amer. J. Med., 55:459.CrossRefGoogle Scholar
  22. Slovic, P., 1972, From Shakespeare to Simon: speculations — and some evidence — about man’s ability to process information, Oregon Research Institute, Res. Bull., 12.Google Scholar
  23. Slovic, P., Fischhoff, B., and Lichtenstein, S., 1977, Behavioural decision theory, Ann. Rev. Psychoi., 28:1CrossRefGoogle Scholar
  24. Tversky, A., and Kahneman, D., 1974, Judgement under uncertainty: Heuristics and biases, Science, 185:1124.PubMedCrossRefGoogle Scholar
  25. Wright, G.N., and Phillips, L.D., 1979, Personality and probabilistic thinking: an exploratory study, Brit. J. Psychol., 70:295.CrossRefGoogle Scholar

Copyright information

© Plenum Press, New York 1982

Authors and Affiliations

  • George Wright
    • 1
  • Kee-On Ng
    • 2
  1. 1.Department of Behavioural SciencesHuddersfield PolytechnicEngland
  2. 2.Sub-department of Clinical PsychologyLiverpool UniversityEngland

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