Title
Diagnostic Accuracy Under Congestion
Abstract
In diagnostic services, agents typically need to weigh the benefit of running an additional test and improving the accuracy of diagnosis against the cost of delaying the provision of services to others. Our paper analyzes how to dynamically manage this accuracy/congestion trade-off. To that end, we study an elementary congested system facing an arriving stream of customers. The diagnostic process consists of a search problem in which the service provider conducts a sequence of imperfect tests to determine the customer's type. We find that the agent should continue to perform the diagnosis as long as her current belief that the customer is of a given type falls into an interval that depends on the congestion level as well as the number of performed tests thus far. This search interval should shrink as congestion intensifies and as the number of performed tests increases if additional conditions hold. Our study reveals that, contrary to diagnostic services without congestion, the base rate i.e., the prior probability of the customer type has an effect on the agent's search strategy. In particular, the optimal search interval shrinks when customer types are more ambiguous a priori, i.e., as the base rate approaches the value at which the agent is indifferent between types. Finally, because of congestion effects, the agent should sometimes diagnose the customer as being of a given type, even if test results indicate otherwise. All these insights disappear in the absence of congestion. This paper was accepted by Martin Lariviere, operations management.
Year
DOI
Venue
2013
10.1287/mnsc.1120.1576
Management Science
Keywords
Field
DocType
base rate,search problem,diagnostic accuracy,search interval,congestion effect,optimal search interval,congestion intensifies,congestion level,congestion trade-off,customer type,diagnostic service,bayes rule,queueing theory,service operations,dynamic programming
Dynamic programming,Mathematical optimization,Economics,Service system,A priori and a posteriori,Operations research,Service provider,Queueing theory,Search problem,Prior probability,Bayes' theorem
Journal
Volume
Issue
ISSN
59
1
0025-1909
Citations 
PageRank 
References 
12
0.68
7
Authors
3
Name
Order
Citations
PageRank
Saed Alizamir1162.13
Francis de Véricourt229521.41
Peng Sun342026.68