Optimizing Diagnostic Test Sequences: The Probability Modifying Plot

J. L. Severens; P. F. de Vries Robbé; A. L. M. Verbeek

doi:10.1055/s-0038-1634143

Methods of Information in Medicine, Inhaltsverzeichnis

Methods Inf Med 1999; 38(01): 50-55
DOI: 10.1055/s-0038-1634143

Original article

Schattauer GmbH

Optimizing Diagnostic Test Sequences: The Probability Modifying Plot

Autor*innen

J. L. Severens

¹Department of Medical Informatics, Epidemiology and Statistics, University of Nijmegen, The Netherlands
P. F. de Vries Robbé

¹Department of Medical Informatics, Epidemiology and Statistics, University of Nijmegen, The Netherlands
A. L. M. Verbeek

¹Department of Medical Informatics, Epidemiology and Statistics, University of Nijmegen, The Netherlands

Abstract

Abstract:

The problem of deciding the optimal sequence of diagnostic tests can be structured in decision trees, but unmanageable bushy decision trees result when the sequence of two or more tests is investigated. Most modelling techniques include tests on the basis of gain in certainty. The aim of this study was to explore a model for optimizing the sequence of diagnostic tests based on efficiency criteria. The probability modifying plot shows, when in a specific test sequence further testing is redundant and which costs are involved. In this way different sequences can be compared. The model is illustrated with data on urinary tract infection. The sequence of diagnostic tests was optimized on the basis of efficiency, which was either defined as the test sequence with the least number of tests or the least total cost for testing. Further research on the model is needed to handle current limitations.

Keywords:

Diagnostic Tests - Test Sequence - Decision Analysis

Volltext

Referenzen

REFERENCES
1 Elstein AS, Kleinmuntz B, Rabinowitz M. et al. Diagnostic reasoning of high- and low-domain-knowledge clinicians. Med Dec Making 1993; 13: 21-9.
2 Kassirer JP. Our stubborn quest for diagnostic certainty; a cause of excessive testing. N Engl J Med 1989; 320: 1489-91.
3 Putterman C, Ben-Chetrit E. Testing, testing, testing. N Engl J Med 1995; 333: 1208-11.
4 Boyko EJ. Ruling out or ruling in disease with the most sensitive or specific test: short cut or wrong turn?. Med Dec Making 1994; 14: 175-9.
5 Doubilet PM, Cain KC. The superiority of sequential over simultaneous testing. Med Dec Making 1985; 5: 447-51.
6 Glasziou PP, Hilden JH. Decision tables and logic in decision analysis. Med Dec Making 1986; 6: 154-60.
7 Glasziou PP. Decision tables – an under-utilized tool? (editorial). Med Dec Making 1994; 14: 207.
8 Lachs MS, Nachamkin I, Edelstein PH, Goldman J, Feinstein AR, Schwartz JS. Spectrum bias in the evaluation of diagnostic tests: lessons from the rapid dipstick test for urinary tract infection. Ann Intern Med 1992; 117: 135-40.
9 Sox HC, Blatt MA, Higgins MC, Marton KI. Selecting and interpretation of diagnostic tests. In: Sox HC, Blatt MA, Higgings MC, Marton KI. eds. Medical Decision Making . Boston: Butterworths; 1988: 239-90.
10 Pauker SG, Kassirer JP. The threshold approach to clinical decision making. N Engl J Med 1980; 302: 1109-17.
11 Fendrick AM, Chernew ME, Hirth RA, Bloom BS. Alternative management strategies for patients with suspected peptic ulcer disease. Ann Intern Med 1995; 123: 260-8.
12 Breiman L, Friedman L, Olshen R, Stone CJ. Classification and Regression Trees . Belmont CA: Wadworth; 1984
13 Diamond GA. Clinical epistemology of sensitivity and specificity. J Clin Epidemiol 1992; 45: 9-13.
14 Knottnerus JA, Leffers P. The influence of referral patterns on the characteristics of diagnostic tests. J Clin Epidemiol 1992; 45: 1143-54.
15 Van Schouw YT, Van Dijk R, Verbeek ALM. Problems in selecting the adequate patient population from existing data files for assessment studies of new diagnostic tests. J Clin Epidemiol 1995; 48: 417-22.
16 Knottnerus JA. Application of logistic regression to the analysis of diagnostic data: exact modelling of a probability tree of multiple binary variables. Med Dec Making 1992; 12: 93-108.