Improving Fraud and Abuse Detection in General Physician Claims: A Data Mining Study
- سال انتشار: 1395
- محل انتشار: مجله بین المللی سیاست و مدیریت بهداشت، دوره: 5، شماره: 3
- کد COI اختصاصی: JR_HPM-5-3_003
- زبان مقاله: انگلیسی
- تعداد مشاهده: 158
نویسندگان
Health Economics Group, Social Security Organization, Tehran, Iran
Department of Health Management and Economics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
School of Computer Engineering, Iran University of Science and Technology, Tehran, Iran
Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
Department of Education Management, School of Psychology and Education, University of Tehran, Tehran, Iran
School of Computer Engineering, Iran University of Science and Technology, Tehran, Iran
Department of Health Management and Economics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
چکیده
Background We aimed to identify the indicators of healthcare fraud and abuse in general physicians’ drug prescription claims, and to identify a subset of general physicians that were more likely to have committed fraud and abuse. Methods We applied data mining approach to a major health insurance organization dataset of private sector general physicians’ prescription claims. It involved ۵ steps: clarifying the nature of the problem and objectives, data preparation, indicator identification and selection, cluster analysis to identify suspect physicians, and discriminant analysis to assess the validity of the clustering approach. Results Thirteen indicators were developed in total. Over half of the general physicians (۵۴%) were ‘suspects’ of conducting abusive behavior. The results also identified ۲% of physicians as suspects of fraud. Discriminant analysis suggested that the indicators demonstrated adequate performance in the detection of physicians who were suspect of perpetrating fraud (۹۸%) and abuse (۸۵%) in a new sample of data. Conclusion Our data mining approach will help health insurance organizations in low-and middle-income countries (LMICs) in streamlining auditing approaches towards the suspect groups rather than routine auditing of all physicians.کلیدواژه ها
Healthcare, Fraud, Abuse, Insurance, Data Mining, General Physicianاطلاعات بیشتر در مورد COI
COI مخفف عبارت CIVILICA Object Identifier به معنی شناسه سیویلیکا برای اسناد است. COI کدی است که مطابق محل انتشار، به مقالات کنفرانسها و ژورنالهای داخل کشور به هنگام نمایه سازی بر روی پایگاه استنادی سیویلیکا اختصاص می یابد.
کد COI به مفهوم کد ملی اسناد نمایه شده در سیویلیکا است و کدی یکتا و ثابت است و به همین دلیل همواره قابلیت استناد و پیگیری دارد.