Reengineering claims processing using probabilistic inductive learning

IEEE Transactions on Engineering Management

Volumn 46, Issue 3, 1999, Pages 335-345

  Arunasalam, Ruthra G ^a   Richie, Jill T ^b   Egan, William ^c   Gür Ali, Özden ^c   Wallace, William A ^a  

^a Bureau of Medical Management   (United States)

^b RENSSELAER POLYTECHNIC INSTITUTE   (United States)

^c ZS Associates   (United States)

Author keywords

Administrative costs; Claims processing; Conciliation process; Data mining; Decision making; Decision trees; Health care administration; Logistic regression; New york state workers' compensation board; Probabilistic inductive learning (pril)

Indexed keywords

EID: 4844225690     PISSN: 00189391     EISSN: None     Source Type: Journal    
DOI: 10.1109/17.775285     Document Type: Article

References (25)

1. I. Hellander, D.U. Himmelstein, S. Woolhandler, and S. Wolfe, "Health care paper chase 1993: The cost to the nation, the states, and the District of Columbia," Int.J. Health Services, vol 24, no. 1, pp. 1-9, 1994.
2. E.B. Click, "A patient's paper chase," Western J. Med., vol. 162, no. 2, p. 177, 1995.
3. L.E. England, "Swimming in a pool of paper," Mississippi State Med. Assoc., vol. 36, no. 5, pp. 143-144, 1995.
4. I. Shulman, "Electronic claims," J. Amer. Dental Assoc., vol. 127, no. 4, p. 424, 1996.
5. D. Kaslow, "More practices are filing electronic claims," Dental Econ., vol. 84, no. 11, pp. 32-43, 1994.
6. Workers ' Compensation Digest of Laws. New York: Workers' Compensation Board, 1994.
7. T. Thomason, "Correlates of workers' compensation claims adjustment," J. Risk Insurance, vol. 61, no. 1, pp. 59-78, 1994.
8. P.T. Shultz and K. L. Looram, "Managing workers' compensation medical costs: A state-by-state guide," Employee Relations, vol 19, no. 3, pp. 251-267, 1993-1994.
9. A. Cheadle, G. Franklin, C. Wolfhagen, J. Savarino, P. Liu, C. Salley, and M. Weaver, "Factors influencing the duration of work-related disability: A population-based study of Washington State Workers' Compensation," Amer.J. Public Health, vol. 84, no. 2, pp. 190-196, 1994.
10. D.D. Ballantyne and C. A. Telles, Workers' Compensation in New York State. Cambridge, MA: Workers' Compensation Res. Inst., 1992.
11. F.O. Gur, "The use of exploratory data analysis to develop decision rules for claims classification at a workers' compensation board," Master's thesis, Dep. Decision Sci. Eng. Syst., Rensselaer Polytechnic Inst., Troy, NY, 1990.
12. O.C. Dais, "Summary of the Benefits Bill (S454-D)," General Council Office to Chairwoman Patton, Board Members, Bureau Heads, and Legislative Committee, 1990.
13. U. Fayyad, G. Piatetsky-Shapiro, and G. Smyth, "The KDD process for extracting useful knowledge from volumes of data," Commun. ACM, vol. 13, no. 11, pp. 27-34, 1996.
14. R.J. Brachman, T. Khabaza, W. Kloesgen, G. Piatetsky-Shapiro, and E. Simoudis, "Mining business databases," Commun. ACM, vol. 39, no. 11, pp. 428, 1996.
15. J.R. Quinlan, "Decision trees and decision making," IEEE Trans. Syst., Man, Cybern., vol. 20, pp. 339-346, Feb. 1990.
16. P.O. Gur Ali and W.A. Wallace, "Induction of rules subject to a quality constraint: Probabilistic inductive learning," IEEE Trans. Knowledge Data Eng., vol. 5, pp. 979-983, June 1993.
17. C. Glymour, D. Madigan, D. Pregibon, and P. Smyth, "Statistical inference in data mining," Commun. ACM, vol 39, no. 11, pp. 35-41, 1996.
18. F.O. Gur Ali, "Probabilistic inductive learning: Induction of decision rules with reliability measures for decision support," Ph.D. thesis, Dep. Decision Sci. Eng. Syst., Rensselaer Polytechnic Inst., Troy, NY, 1994.
19. F.O. Gur Ali and W. A. Wallace, "Classifying delinquent customers for credit collections: An application of probabilistic inductive learning," Int. J. Human-Comput. Studies, vol .42, no. 6, pp. 633-646, 1995.
20. _, "Bridging the gap between business objectives and parameters of data mining algorithms, decision support system," Decision Support Syst. (Special Issue on Data Mining), vol. 21, no. 1, pp. 3-15, 1998.
21. J. Neter, M.H. Kutner, C. J. Nachtsheim, and W. Wasserman, Applied Linear Regression Models. Chicago, IL: Irwin, 1990.
22. W.W. Cohen, "Fast effective rule induction," in Machine Learning: P roc. 12th Int. Conf. Lake Tahoe, CA: Morgan Kaufmann, 1995, pp. 115-123.
23. M.J. Norusis, SPSS Advanced Statistics Student Guide. Chicago, IL: SPSS, Inc., 1990, pp. 119-146.
24. D.W. Hosmer and S. Lemeshow, Applied Logistic Regression. New York: Wiley, 1989.
25. Bureau of Labor Statistics, U.S. Dep. Labor. (1996). Industry injury and illness data, safety and health statistics. [Online]. Available WWW: http://stats.bls.gov/special.requests/ocwc/osh/os/osnr0005.txt.