A Hybrid System Improves Claims Auditing at Blue Cross

Jerrold H. May, William E. Spangler, Sean Chen and Sharon L. Donohue
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Jerrold H. May: Artificial Intelligence in Management Laboratory, Joseph M. Katz Graduate School of Business, University of Pittsburgh, Pittsburgh, Pennsylvania 15260
William E. Spangler: Artificial Intelligence in Management Laboratory, University of Pittsburgh
Sean Chen: Artificial Intelligence in Management Laboratory, University of Pittsburgh
Sharon L. Donohue: Knowledge Engineering Group, Blue Cross of Western Pennsylvania, Fifth Avenue Place, Suite 778, Pittsburgh, Pennsylvania 15222

Interfaces, 1993, vol. 23, issue 6, 67-80

Abstract: The PlanTracker system helps Blue Cross of Western Pennsylvania (BCWP) to analyze errors in claims records transmitted from other Blue Cross organizations with the goal of improving their accuracy. The development of PlanTracker was complicated by a complex and constantly changing data transmission environment that impeded the formation of both descriptive models of human domain expertise and normative models based on analysis of the claims data. We developed a hybrid system that compensated for these problems by utilizing statistical and heuristic knowledge to assess claims data submissions over time. PlanTracker has reduced the time required to audit claims information from seven days to about one hour, helping BCWP to increase the frequency and volume of its records transmission and reduce errors in transmitted claims data. As a result, BCWP has achieved a more timely and consistent billing cycle for its corporate accounts. Since 1987, the dollar volume of claims rejected annually has decreased from 10 percent to 4.5 percent.

Keywords: financial institutions: insurance; computers: system design and operation (search for similar items in EconPapers)
Date: 1993
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