Methods Inf Med 1984; 23(01): 15-22
DOI: 10.1055/s-0038-1635319
Original Article
Schattauer GmbH

Comparison of Examinees’ and Doctors’ Judgement of Health Status Using Data in an AMHTS

Vergleichende Beurteilung des Gesundheitszustandes durch Probanden und Ärzte mit Hilfe von AMHTS-Daten
Y. Sekita
1   (From the Dept. of Hospital and Medical Care Administration, Tohoku University, Sendai, the Dept. of Computer Science and Statistics, Otemon University, and the First Department of Medicine, Osaka University, Japan)
,
T. Ohta
1   (From the Dept. of Hospital and Medical Care Administration, Tohoku University, Sendai, the Dept. of Computer Science and Statistics, Otemon University, and the First Department of Medicine, Osaka University, Japan)
,
M. Inoue
1   (From the Dept. of Hospital and Medical Care Administration, Tohoku University, Sendai, the Dept. of Computer Science and Statistics, Otemon University, and the First Department of Medicine, Osaka University, Japan)
,
H. Takeda
1   (From the Dept. of Hospital and Medical Care Administration, Tohoku University, Sendai, the Dept. of Computer Science and Statistics, Otemon University, and the First Department of Medicine, Osaka University, Japan)
› Author Affiliations
Further Information

Publication History

Publication Date:
17 February 2018 (online)

Summary

Judgements of examinees’ health status by doctors and by the examinees themselves are compared applying multiple discriminant analysis. The doctors’ judgements of the examinees’ health status are studied comparatively using laboratory data and the examinees’ subjective symptom data.

This data was obtained in an Automated Multiphasic Health Testing System. We discuss the health conditions which are significant for the judgement of doctors about the examinees. The results show that the explanatory power, when using subjective symptom data, is fair in the case of the doctors’ judgement. We found common variables, such as nervousness, lack of perseverance etc., which form the first canonical axis.

Die Beurteilung des Gesundheitszustandes durch Ärzte und die Probanden selbst wurde mit Hilfe der multiplen Diskriminanz-Analyse miteinander verglichen. Die Beurteilung des Gesundheitszustandes der Versuchspersonen durch die Ärzte erfolgte aufgrund der Labordaten und der subjektiven Symptome, die mittels Automated Multiphasic Health Testing and Services (AMHTS) gewonnen wurden.

Es wird diskutiert, welche Faktoren für die ärztliche Beurteilung des Gesundheitszustandes der Probanden bedeutsam sind. Die Ergebnisse zeigen, daß die Beurteilung von seiten des Arztes auch bei Verwendung subjektiver Symptomangaben gut ist. Ferner fanden wir gemeinsame Variablen von Ärzten und Probanden, wie z. B. Nervosität, mangelnde Ausdauer usw., die die erste kanonische Achse bilden.

 
  • References

  • 1 Balinsky W., Burger R.. A Review of Research on General Health Status Indexes. Med. Care 1975; 3: 283-293.
  • 2 Cooley W. W.. Multivariate Data Analysis. New York: John Wiley; 1971
  • 3 Dales L. G., Friedman G. D., Collen M. F.. Evaluation of a Periodic Multiphasic Health Checkup. Meth. Inform. Med 1974; 13: 140-146.
  • 4 Fanshel S., Bush S. W.. A Health-Status Index and its Application to Health-Services Outcomes. Operations Res 1970; 18: 1021-1066.
  • 5 Howe H. F.. Organization and Operation of an Occupational Health Program. J. occup. Med 1975; 17: 528-540.
  • 6 Lindberg D. A. B.Watson, Fr R.. Imprecision of Laboratory Determinations and Diagnostic Accuracy; Theoretical Considerations. Meth. Inform. Med 1974; 13: 151-158.
  • 7 Pliskin J. S., Beck Jr. C. H.. A Health Index for Patient Selection-A Value Function Approach with Application to Chronic Renal Failure Patients. Mangmt Sci 1976; 22: 1009-1021.
  • 8 Press S. J.. Applied Multivariate Analysis. New York: Holt, Rinehart and Winston; 1972
  • 9 Rowe I. L., Larsen L. H.. Evaluation of Automated Multiphasic Health Testing in the Survey of the North-West Region. Med. J. Aust 1979; 22: 320-324.
  • 10 Sebag J., Hall P.. Decision-Making in Medical Research and Clinical Practice; Theory and Methodology of Laboratory Data Evaluation by Predictors, Indicators and Indices. Meth. Inform. Med 1975; 14: 113-117.
  • 11 Sekita Y., Tabata Y.. A Health Status Index Model Using a Fuzzy Approach. Europ. J. Operat. Res 1979; 3: 40-49.
  • 12 Thrall R. M., Cardus D.. Benefit-Cost and Cost-Effectiveness Analyses in Re-habilitation Research Programs. Meth. Inform. Med 1974; 13: 147-150.
  • 13 Torrance G. W.. Health Status Index Models: A Unified Mathematical View. Managmt Sci 1976; 22: 990-1001.