A survey on statistical methods for health care fraud detection

被引:98
作者
Li, Jing [1 ]
Huang, Kuei-Ying [2 ]
Jin, Jionghua [2 ]
Shi, Jianjun [2 ]
机构
[1] Arizona State Univ, Dept Ind Engn, Tempe, AZ 85287 USA
[2] Univ Michigan, Dept Ind & Operat Engn, Ann Arbor, MI 48109 USA
关键词
Fraud detection; Health care; Statistical methods;
D O I
10.1007/s10729-007-9045-4
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Fraud and abuse have led to significant additional expense in the health care system of the United States. This paper aims to provide a comprehensive survey of the statistical methods applied to health care fraud detection, with focuses on classifying fraudulent behaviors, identifying the major sources and characteristics of the data based on which fraud detection has been conducted, discussing the key steps in data preprocessing, as well as summarizing, categorizing, and comparing statistical fraud detection methods. Based on this survey, some discussion is provided about what has been lacking or under-addressed in the existing research, with the purpose of pinpointing some future research directions.
引用
收藏
页码:275 / 287
页数:13
相关论文
共 45 条
[1]  
ABBOTT DW, 1998, P IEEE INT C SYST MA
[2]  
[Anonymous], 1995, INTELLIGENT SYSTEMS
[3]  
[Anonymous], 2000, J ADV COMPUT INTELL, DOI DOI 10.20965/JACIII.2000.P0130
[4]  
[Anonymous], 1999, P KDD, DOI [10.1145/312129.312195, DOI 10.1016/J.EC0LENG.2010.11.031]
[5]  
[Anonymous], ACM SIGKDD EXPLORATI, DOI [DOI 10.1145/1007730.1007738, 10.1145/1007730.1007738]
[6]  
[Anonymous], 1998, P 11 ANN C COMP LEAR
[7]  
Bennett KP, 1999, ADV NEUR IN, V11, P368
[8]  
BONCHI F, 1999, P 5 ACM SIGKDD INT C, P175
[9]   A Bayesian network of eutrophication models for synthesis, prediction, and uncertainty analysis [J].
Borsuk, ME ;
Stow, CA ;
Reckhow, KH .
ECOLOGICAL MODELLING, 2004, 173 (2-3) :219-239
[10]  
Chan CL, 2001, IC-AI'2001: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE, VOLS I-III, P402