Reliability block diagrams to model disease management.
OBJECTIVE
Studies of diagnostic or therapeutic procedures in the management of any given disease tend to focus on one particular aspect of the disease and ignore the interaction between the multitude of factors that determine its final outcome. The present article introduces a mathematical model that accounts for the joint contribution of various medical and non-medical components to the overall disease outcome.


METHODS
A reliability block diagram is used to model patient compliance, endoscopic screening, and surgical therapy for dysplasia in Barrett's esophagus.


RESULTS
The overall probability of a patient with a Barrett's esophagus to comply with a screening program, be correctly diagnosed with dysplasia, and undergo successful therapy is 37%. The reduction in the overall success rate, despite the fact that the majority of components are assumed to function with reliability rates of 80% or more, is a reflection of the multitude of serial subsystems involved in disease management. Each serial component influences the overall success rate in a linear fashion. Building multiple parallel pathways into the screening program raises its overall success rate to 91%. Parallel arrangements render systems less sensitive to diagnostic or therapeutic failures.


CONCLUSIONS
A reliability block diagram provides the means to model the contributions of many heterogeneous factors to disease outcome. Since no medical system functions perfectly, redundancy provided by parallel subsystems assures a greater overall reliability.
Sonnenberg
A
A
Department of Veterans Affairs Medical Center and University of New Mexico, Albuquerque 87108, USA. sonnbrg@unm.edu
Inadomi
J M
JM
Bauerfeind
P
P
D001471:Barrett Esophagus / Q000175:diagnosis / Q000523:psychology / Q000601:surgery / Q000628:therapy*; D001706:Biopsy; D019468:Disease Management; D004945:Esophagoscopy; D006801:Humans; D008403:Mass Screening; D015233:Models, Statistical; D010349:Patient Compliance; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013597:Systems Analysis; D017211:Treatment Failure