No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Physician Medicare fraud: Characteristics and consequences
Abstract
Purpose ‐ Criminal Medicare and/or Medicaid fraud costs taxpayers $60-250 billion annually. This paper aims to outline the characteristics of physicians who have been convicted of such fraud. Design/methodology/approach ‐ The names of convicted physicians were first gathered from public databases (primarily, the OIG exclusion list). The names were further cross-checked and verified with other public records. Details regarding demographics and the particulars of the fraud were obtained by searching court documents, media reports, the internet, and records maintained by the American Medical Association and state medical licensing boards. The paper categorizes these doctors by: age, gender, geographic location, medical school attended, and medical specialty, and compares these demographics to those of the medical profession as a whole. The paper then identifies: the specific Medicare fraud these physicians were charged with; length of prison sentence and/or probation imposed; amount of fines assessed and/or restitution ordered; and professional sanctions imposed. Findings ‐ Physicians convicted of criminal Medicare and/or Medicaid fraud tend to be male (87 percent), older (average age of 58), and international medical graduates (59 percent). Family practitioners and psychiatrists are overrepresented. The amount of fraud averaged $1.4 million per convicted physician. Surprisingly, despite the fact that 40 percent of such fraud compromised patient care and safety, 37 percent of physicians convicted of felony fraud served no jail time, 38 percent of physicians with fraud convictions continue to practice medicine, and 21 percent were not suspended from medical practice for a single day despite their fraud convictions. Practical implications ‐ The paper makes several practical recommendations including: running as many claims as possible through predictive modeling software to detect fraud before claims are paid; developing metrics on the average rate of diagnoses and procedures by specialty to be used in the predictive modeling software; incorporating the basics of ethical billing and the consequences of fraud convictions into the medical school curriculum and testing this knowledge on the USMLE; and encouraging and/or pressuring state medical boards to hold physicians more accountable for fraud. Originality/value ‐ The paper categorizes doctors convicted of Medicare and/or Medicaid fraud and makes specific recommendations regarding physician training, licensing and discipline, to reduce the amount of Medicare fraud perpetrated by doctors in the future.
... Criminal cases were examined in 2/32 studies [36,37]; both found that male doctors were significantly more likely to experience criminal charges (P <0.05). ...
... All 19 studies reported that male doctors were more likely to experience a medico-legal action than female doctors (range of odds ratios, 1.02-6.12) [5,6,14,16,19,20,22,23,25,28,31,[34][35][36][37]39]; in 3/19 studies the difference was not statistically significant [8,9,24]. No studies showed women were more likely to experience a medico-legal action than men (Fig. 2). ...
... Unfortunately, we were unable to explore further whether the sex difference in medico-legal action was impacted by specialty practised. Thirteen of the studies included in the meta-analysis examined whether the likelihood of medico-legal action differed between specialties [5,6,8,9,14,16,19,28,31,[35][36][37]39]; however, the specialities most and least likely to face medico-legal action varied greatly between the studies. In the studies which controlled for the effect of specialty when examining the association between sex and medico-legal action, all but one [31] demonstrated that male doctors remained more likely to have had medico-legal experience even with specialty taken into account [6,5,16,19,35]. ...
The relationship between male sex and poor performance in doctors remains unclear, with high profile studies showing conflicting results. Nevertheless, it is an important first step towards understanding the causes of poor performance in doctors. This article aims to establish the robustness of the association between male sex and poor performance in doctors, internationally and over time.
The electronic databases MEDLINE, EMBASE, and PsycINFO were searched from inception to January 2015. Backward and forward citation searching was performed. Journals that yielded the majority of the eligible articles and journals in the medical education field were electronically searched, along with the conference and poster abstracts from two of the largest international medical education conferences. Studies reporting original data, written in English or French, examining the association between sex and medico-legal action against doctors were included. Two reviewers independently extracted study characteristics and outcome data from the full texts of the studies meeting the eligibility criteria. Study quality was assessed using the Newcastle-Ottawa scale. A random effect meta-analysis model was used to summarize and assess the effect of doctors' sex on medico-legal action. Extracted outcomes included disciplinary action by a medical regulatory board, malpractice experience, referral to a medical regulatory body, complaints received by a healthcare complaints body, criminal cases, and medico-legal matter with a medical defence organisation.
Overall, 32 reports examining the association between doctors' sex and medico-legal action were included in the systematic review (n=4,054,551), of which 27 found that male doctors were more likely to have experienced medico-legal action. 19 reports were included in the meta-analysis (n=3,794,486, including 20,666 cases). Results showed male doctors had nearly two and a half times the odds of being subject to medico-legal action than female doctors. Heterogeneity was present in all meta-analyses.
Male doctors are more likely to have had experienced medico-legal actions compared to female doctors. This finding is robust internationally, across outcomes of varying severity, and over time.
... The authors then attempt to determine potential misuse of the Medicare system, and, potentially, mark certain physicians as being fraudulent early in their careers which can be seen as a preventative step. One study [26] uses 2012 Medicare data with exclusion labels. The authors are interested in who the perpetrators are and what happens after they get caught. ...
... Understanding the grouping, as with the Part B data, is important for data integration and/or class label generation. Even though the LEIE database contains excluded providers to be used as fraud labels, it is not all-inclusive where 38% of providers with fraud convictions continue to practice medicine and 21% were not suspended from medical practice despite their convictions [26]. We incorporate these excluded providers from the LEIE database [21] as labels to indicate fraud. ...
Healthcare in the United States is a critical aspect of most people’s lives, particularly for the aging demographic. This rising elderly population continues to demand more cost-effective healthcare programs. Medicare is a vital program serving the needs of the elderly in the United States. The growing number of Medicare beneficiaries, along with the enormous volume of money in the healthcare industry, increases the appeal for, and risk of, fraud. In this paper, we focus on the detection of Medicare Part B provider fraud which involves fraudulent activities, such as patient abuse or neglect and billing for services not rendered, perpetrated by providers and other entities who have been excluded from participating in Federal healthcare programs. We discuss Part B data processing and describe a unique process for mapping fraud labels with known fraudulent providers. The labeled big dataset is highly imbalanced with a very limited number of fraud instances. In order to combat this class imbalance, we generate seven class distributions and assess the behavior and fraud detection performance of six different machine learning methods. Our results show that RF100 using a 90:10 class distribution is the best learner with a 0.87302 AUC. Moreover, learner behavior with the 50:50 balanced class distribution is similar to more imbalanced distributions which keep more of the original data. Based on the performance and significance testing results, we posit that retaining more of the majority class information leads to better Medicare Part B fraud detection performance over the balanced datasets across the majority of learners.
... Nortjé and Hoffmann's [12] study found that fraudulent activities committed by SA healthcare professionals consisted mainly of billing for false claims, which are similar to the findings of this study. Syndicate fraud committed through identity theft and the submission of fictitious claims was identified in this study, which is in line with the findings of Flynn, [10] Pande and Maas [20] and Nortjé and Hoffmann. [12] Our study also found that unlicensed people pose as healthcare service providers. ...
Background. Medical schemes play a significant role in funding private healthcare in South Africa (SA). However, the sector is negatively affected by the high rate of fraudulent claims. Objectives. To identify the types of fraudulent activities committed in SA medical scheme claims. Methods. A cross-sectional qualitative study was conducted, adopting a case study strategy. A sample of 15 employees was purposively selected from a single medical scheme administration company in SA. Semi-structured interviews were conducted to collect data from study participants. A thematic analysis of the data was done using ATLAS.ti software (ATLAS.ti Scientific Software Development, Germany). Results. The study population comprised the 17 companies that administer medical schemes in SA. Data were collected from 15 study participants, who were selected from the medical scheme administrator chosen as a case study. The study found that medical schemes were defrauded in numerous ways. The perpetrators of this type of fraud include healthcare service providers, medical scheme members, employees, brokers and syndicates. Medical schemes are mostly defrauded by the submission of false claims by service providers and syndicates. Fraud committed by medical scheme members encompasses the sharing of medical scheme benefits with non-members (card farming) and non-disclosure of pre-existing conditions at the application stage. Conclusions. The study concluded that perpetrators of fraud have found several ways of defrauding SA medical schemes regarding claims. Understanding and identifying the types of fraud events facing medical schemes is the initial step towards establishing methods to mitigate this risk. Future studies should examine strategies to manage fraudulent medical scheme claims. © 2018, South African Medical Association. All rights reserved.
... Nortjé and Hoffmann's [12] study found that fraudulent activities committed by SA healthcare professionals consisted mainly of billing for false claims, which are similar to the findings of this study. Syndicate fraud committed through identity theft and the submission of fictitious claims was identified in this study, which is in line with the findings of Flynn, [10] Pande and Maas [20] and Nortjé and Hoffmann. [12] Our study also found that unlicensed people pose as healthcare service providers. ...
Background:
Medical schemes play a significant role in funding private healthcare in South Africa (SA). However, the sector is negatively affected by the high rate of fraudulent claims.
Objectives:
To identify the types of fraudulent activities committed in SA medical scheme claims.
Methods:
A cross-sectional qualitative study was conducted, adopting a case study strategy. A sample of 15 employees was purposively selected from a single medical scheme administration company in SA. Semi-structured interviews were conducted to collect data from study participants. A thematic analysis of the data was done using ATLAS.ti software (ATLAS.ti Scientific Software Development, Germany).
Results:
The study population comprised the 17 companies that administer medical schemes in SA. Data were collected from 15 study participants, who were selected from the medical scheme administrator chosen as a case study. The study found that medical schemes were defrauded in numerous ways. The perpetrators of this type of fraud include healthcare service providers, medical scheme members, employees, brokers and syndicates. Medical schemes are mostly defrauded by the submission of false claims by service providers and syndicates. Fraud committed by medical scheme members encompasses the sharing of medical scheme benefits with non-members (card farming) and non-disclosure of pre-existing conditions at the application stage.
Conclusions:
The study concluded that perpetrators of fraud have found several ways of defrauding SA medical schemes regarding claims. Understanding and identifying the types of fraud events facing medical schemes is the initial step towards establishing methods to mitigate this risk. Future studies should examine strategies to manage fraudulent medical scheme claims.
... In this paper, we focus on the mandatory exclusions which are presented in Table I. Even though providers are on the LEIE, 38% with fraud convictions continue to practice medicine and 21% were not suspended from medical practice despite their convictions [36]. Felony conviction due to healthcare fraud. ...
With the increasing number of people ages 65 and older, healthcare programs are being relied on more for quality and affordable care. Given these and other factors, healthcare spending continues to increase, particularly for the elderly. Medicare is one such program affected by the aging population. Fraud in the United States (U.S.) Medicare program is an ongoing issue resulting in higher healthcare costs for beneficiaries. In this paper, we present an empirical study of several unsupervised machine learning methods to detect out-liers, indicating fraudulent medical providers, using the Medicare Part B big dataset. We employ two methods, Isolation Forest and Unsupervised Random Forest, which have not previously been used for the detection of Medicare fraud, along with more commonly used methods to include Local Outlier Factor, autoencoders, and k-Nearest Neighbors. In order to validate the fraud detection performance of each method, we use the List of Excluded Individuals/Entities (LEIE) database which contains information on excluded providers. Moreover, we present details on processing the Part B data and incorporating the LEIE fraud labels. Our results indicate that Local Outlier Factor is the best outlier detection method and k-Nearest Neighbors, with 5 neighbors, and autoencoders are the worst at detecting Medicare Part B fraud.
... The OIG has authority to exclude individuals and entities from federally funded healthcare programs, such as Medicare. Unfortunately, the LEIE is not all-inclusive where 38% of providers with fraud convictions continue to practice medicine and 21% were not suspended from medical practice despite their convictions [51]. Moreover, the LEIE dataset only contains the NPI values for a small percentage of physicians and entities. ...
Abstract In the United States, advances in technology and medical sciences continue to improve the general well-being of the population. With this continued progress, programs such as Medicare are needed to help manage the high costs associated with quality healthcare. Unfortunately, there are individuals who commit fraud for nefarious reasons and personal gain, limiting Medicare’s ability to effectively provide for the healthcare needs of the elderly and other qualifying people. To minimize fraudulent activities, the Centers for Medicare and Medicaid Services (CMS) released a number of “Big Data” datasets for different parts of the Medicare program. In this paper, we focus on the detection of Medicare fraud using the following CMS datasets: (1) Medicare Provider Utilization and Payment Data: Physician and Other Supplier (Part B), (2) Medicare Provider Utilization and Payment Data: Part D Prescriber (Part D), and (3) Medicare Provider Utilization and Payment Data: Referring Durable Medical Equipment, Prosthetics, Orthotics and Supplies (DMEPOS). Additionally, we create a fourth dataset which is a combination of the three primary datasets. We discuss data processing for all four datasets and the mapping of real-world provider fraud labels using the List of Excluded Individuals and Entities (LEIE) from the Office of the Inspector General. Our exploratory analysis on Medicare fraud detection involves building and assessing three learners on each dataset. Based on the Area under the Receiver Operating Characteristic (ROC) Curve performance metric, our results show that the Combined dataset with the Logistic Regression (LR) learner yielded the best overall score at 0.816, closely followed by the Part B dataset with LR at 0.805. Overall, the Combined and Part B datasets produced the best fraud detection performance with no statistical difference between these datasets, over all the learners. Therefore, based on our results and the assumption that there is no way to know within which part of Medicare a physician will commit fraud, we suggest using the Combined dataset for detecting fraudulent behavior when a physician has submitted payments through any or all Medicare parts evaluated in our study.
... After reviewing the violations under the aforementioned sections, we decided to only incorporate physicians with mandatory exclusions (Section 1128). Even though the LEIE database provides known provider-level exclusions, it is not a complete record of all known provider fraud, where 38% with fraud convictions continue to practice medicine and 21% were not suspended from medical practice despite their convictions [30]. This lack of knowledge regarding all possible fraudulent providers could lead to predicting a provider as fraudulent when they are not, or vice versa, which may reduce the overall accuracy of a prediction model. ...
Quality and affordable healthcare is an important aspect in people’s lives, particularly as they age. The rising elderly population in the United States (U.S.), with increasing number of chronic diseases, implies continuing healthcare later in life and the need for programs, such as U.S. Medicare, to help with associated medical expenses. Unfortunately, due to healthcare fraud, these programs are being adversely affected draining resources and reducing quality and accessibility of necessary healthcare services. The detection of fraud is critical in being able to identify and, subsequently, stop these perpetrators. The application of machine learning methods and data mining strategies can be leveraged to improve current fraud detection processes and reduce the resources needed to find and investigate possible fraudulent activities. In this paper, we employ an approach to predict a physician’s expected specialty based on the type and number of procedures performed. From this approach, we generate a baseline model, comparing Logistic Regression and Multinomial Naive Bayes, in order to test and assess several new approaches to improve the detection of U.S. Medicare Part B provider fraud. Our results indicate that our proposed improvement strategies (specialty grouping, class removal, and class isolation), applied to different medical specialties, have mixed results over the selected Logistic Regression baseline model’s fraud detection performance. Through our work, we demonstrate that improvements to current detection methods can be effective in identifying potential fraud.
... [4][5][6] Previous studies of physician fraud and other exclusions from Medicare rely on older data 7-9 and do not include sufficient comparisons of the characteristics of excluded and nonexcluded physicians. [7][8][9][10][11] Published studies of board disciplined physicians were limited to case studies from specific states. 8,10 More contemporary, comprehensive data on the number of physicians excluded from reimbursement by Medicare and state public insurance programs owing to concerns about fraud, waste, and abuse and the types of physicians who are more likely to be excluded would be helpful for understanding the scale of potentially wasteful service delivery in the United States and the success of ongoing efforts to deter, prevent, and identify health care fraud. ...
Importance
Each year, billions of dollars are wasted owing to health care fraud, waste, and abuse. Efforts to detect fraud have been increasing, yet we have little information about physicians who have been excluded from Medicare and state public insurance programs for fraud, health crimes, or the unlawful prescribing of controlled substances.
Objective
To examine the characteristics of physicians excluded from Medicare and state public insurance programs for fraud, health crimes, or unlawful prescribing of controlled substances.
Design, Setting, and Participants
This cross-sectional study considered all physicians excluded from Medicare and state public insurance programs between 2007 and 2017. The study matched exclusion data to a comprehensive, cross-sectional database of US physicians assembled by Doximity, an online networking service for US physicians. The share of physicians excluded in each state was examined and linear trends of exclusions over time were estimated. Using physician-level multivariable logistic regression models, exclusions (binary variable) were assessed as a function of physician characteristics.
Main Outcomes and Measures
Exclusions for fraud, health crimes (defined legally as criminal penalties for acts involving federal health care programs), and substance abuse; and physician characteristics, including age, sex, allopathic vs osteopathic degree, medical school attended, ranking of that medical school, medical school faculty affiliation, practice state, practice location, and specialty.
Results
Between 2007 and 2017, 2222 physicians (0.29%) were temporarily or permanently excluded from Medicare and state public insurance programs. Fraud, health crimes, and substance abuse exclusions increased, on average, 20% per year (equivalent to 48 [95% CI, 40.4-56.0] convictions/year from a base of 236 convictions in 2007 to 670 convictions in 2017 [an increase of approximately 200% from 2007 to 2017]). Exclusion rates were highest in the West and Southeast. West Virginia had the highest exclusion rate, with 5.77 exclusions per 1000 physicians (32 exclusions among 5720 physicians), while Montana had 0 exclusions during this period. Male physicians, physicians with osteopathic training, older physicians, and physicians in specific specialties (eg, family medicine, psychiatry, internal medicine, anesthesiology, surgery, and obstetrics/gynecology) were more likely to be excluded.
Conclusions and Relevance
The number of physicians excluded from participation in Medicare and state public insurance reimbursement owing to fraud, waste, and abuse increased between 2007 and 2017. Several physician characteristics, including being a male, older age, and osteopathic training, were significantly and positively associated with exclusion. Our results highlight the potential value of using physician characteristics in conjunction with information on medical claims filed by physicians to help identify adverse physician behavior.
... The LEIE, unfortunately, contains the NPI values for only a small percentage of physicians and entities within its database, contributing to the large class imbalance found after fraud labels are added to the Medicare datasets. We note that 38% of providers convicted of fraud continue practicing medicine and 21% of providers with fraud convictions were not suspended from practicing medicine, despite being convicted [55]. There are different categories of exclusions, based on severity of offense. ...
Abstract The United States healthcare system produces an enormous volume of data with a vast number of financial transactions generated by physicians administering healthcare services. This makes healthcare fraud difficult to detect, especially when there are considerably less fraudulent transactions (documented and readily available) than non-fraudulent. The ability to successfully detect fraudulent activities in healthcare, given such discrepancies, can garner up to $350 billion in recovered monetary losses. In machine learning, when one class has a substantially larger number of instances (majority) compared to the other (minority), this is known as class imbalance. In this paper, we focus specifically on Medicare, utilizing three ‘Big Data’ Medicare claims datasets with real-world fraudulent physicians. We create a training and test dataset for all three Medicare parts, both separately and combined, to assess fraud detection performance. To emulate class rarity, which indicates particularly severe levels of class imbalance, we generate additional datasets, by removing fraud instances, to determine the effects of rarity on fraud detection performance. Before a machine learning model can be distributed for real-world use, a performance evaluation is necessary to determine the best configuration (e.g. learner, class sampling ratio) and whether the associated error rates are low, indicating good detection rates. With our research, we demonstrate the effects of severe class imbalance and rarity using a training and testing (Train_Test) evaluation method via a hold-out set, and provide our recommendations based on the supervised machine learning results. Additionally, we repeat the same experiments using Cross-Validation, and determine it is a viable substitute for Medicare fraud detection. For machine learning with the severe class imbalance datasets, we found that, as expected, fraud detection performance decreased as the fraudulent instances became more rare. We apply Random Undersampling to both Train_Test and Cross-Validation, for all original and generated datasets, in order to assess potential improvements in fraud detection by reducing the adverse effects of class imbalance and rarity. Overall, our results indicate that the Train_Test method significantly outperforms Cross-Validation.
... Compared with our knowledge of street crime, the causes of elite medical crime are less well understood. Numerous commentators contend that the unmatched trust, respect, and authority doctors engender have contributed to a dearth of scholarship on physician malfeasance ( Pande & Maas, 2013 ). Whatever it is, the limited scientific evidence makes it difficult to determine the full extent of this problem, and in turn, restricts our ability to identify actionable policy solutions. ...
The concept of deviance is complex, given that norms vary considerably across groups, times, and places. Society tends to primarily recognize traditional portraits of deviants such as street-offenders and drug addicts. The label "deviant" is commonly cast upon society’s undesirables, but this socially constructed image often overlooks subtler—and arguably more dangerous—deviance. Physician malfeasance is an especially problematic form, given that medical professionals garner trust, autonomy, and prestige from society, which allows them to operate outside of the public eye.
This book responds to a growing number of concerns regarding deviant physician actions such as physically and sexually abusive behaviors, fabricating medical findings and records, and taking advantage of patients (e.g., filing fraudulent Medicaid claims). It explores theoretical explanations for physician deviance, and goes on to consider potential responses such as Medicaid Fraud Control Units, the Questionable Doctors database, and the ability of doctors to police themselves.
The unique perspective offered in this book informs discussions of white-collar crime and deviance and has important implications for researchers, policymakers, and students involved in criminal justice and public policy.
... Compared with our knowledge of street crime, the causes of elite medical crime are less well understood. Numerous commentators contend that the unmatched trust, respect, and authority doctors engender have contributed to a dearth of scholarship on physician malfeasance ( Pande & Maas, 2013 ). Whatever it is, the limited scientific evidence makes it difficult to determine the full extent of this problem, and in turn, restricts our ability to identify actionable policy solutions. ...
... This study contributes to the following domains of research. The first one tries to depict fraudsters' profiles in different countries or industries (Pande and Maas 2013;Dehghanpour and Rezvani 2015;Button et al. 2016). Scholars from the second domain of studies investigate the factors affecting the size of loss due to different fraud categories including insurance (Akomea-Frimpong et al. 2016;Timofeyev 2015;Tseng and Su 2014). ...
This study aims to explore the current trends in fraud prevention in the insurance industry in Russia. Survey responses from 20 experts and professionals of the leading insurance companies in Moscow were collected. More than a half of them are former police officers who work at security or investigation departments. Survey data analysis was employed. According to the experts’ opinion, existing gaps in the legislation and difficulties in cooperation with the police are the main sources of inefficiency of fraud prevention strategies utilised by the Russian insurance companies. The respondents agreed that both insurers and fraudsters actively use new technologies. Fraudulent claims in compulsory third party liability motor insurance remain the most common activity among Russian criminals, although they quickly expand to health and property insurance. Typically, an insurance fraudster is a 34-year-old male with a college/university degree who cooperates with an insurance broker in 42% of cases. Based on this, a set of recommendations aimed at increasing the efficiency of insurance fraud prevention was produced.
... We note, however, that the LEIE dataset contains NPI values for only a fraction of fraudulent physicians and entities in the US. Nationally, approximately 21% of convicted fraudulent providers have not been suspended from medical practice, and about 38% of those convicted continue to practice medicine [41]. ...
Abstract A majority of predictive models should be updated regularly, since the most recent data associated with the model may have a different distribution from that of the original training data. This difference may be critical enough to impact the effectiveness of the machine learning model. In our paper, we investigate the relationship between time and predictive model maintenance. Our work incorporates severely imbalanced big data from three Medicare datasets, namely Part D, DMEPOS, and Combined, that have been used in several fraud detection studies. We build training datasets from year-groupings of 2013, 2014, 2015, 2013–2014, 2014–2015, and 2013–2015. Our test datasets are built from the 2016 data. To mitigate some of the adverse effects from the severe class imbalance in these datasets, the performance of five class ratios obtained by Random Undersampling and five learners is evaluated by the Area Under the Receiver Operating Characteristic Curve metric. The models producing the best values are as follows: Logistic Regression with the 2015 year-grouping at a 99:1 class ratio (Part D); Random Forest with the 2014-2015 year-grouping at a 75:25 class ratio (DMEPOS); and Logistic Regression with the full 2015 year-grouping (Combined). Our experimental results show that the largest training dataset (year-grouping 2013–2015) was not among the selected choices, which indicates that the 2013 data may be outdated. Moreover, we note that because the best model is different for Part D, DMEPOS, and Combined, this suggests that these three datasets may actually be sub-domains requiring unique models within the Medicare fraud detection domain.
... Given the size and scope of the PHI sector, developing and implementing tools to manage big data seems inevitable. Here we see machine learning and AI-technologies as somehow necessary to achieve, or at least significantly facilitate, the holistic approach, as advocated earlier, in the fight against fraud (see also Pande and Maas 2013). ...
The private healthcare insurance sector is rarely the subject of criminological analysis unless seen as corrupt. It is even more unusual that it is the subject of analysis as a victim of fraud. This paper is thus different in that it establishes a picture of international private healthcare insurance sectors approach in preventing fraud and providing healthcare services. We start by explaining why the private health insurance markets exist. This is followed by the methods employed to secure innovative data from the private health insurance sector. The results of the research conducted in collaboration with the International Federation of Health Plans are then presented. A discussion on key aspects of this research is then examined before we lastly, consider a way forward and the development of fraud resilience in the private insurance healthcare market.
... The second set of audit studies seeks to identify the observable hospitals' or physicians' characteristics associated with fraudulent or abusive behavior [15][16][17][18] . Some important results are considered below. ...
Background:
Fraud- or theft-related crimes account for the highest number of crimes in the mental health industry in the US.
Aim:
This exploratory study aims to demonstrate a fraudster's and respective victims' profiles as well as to identify the loss predictors' hierarchy in the mental health industry in the US.
Materials and methods:
The Psychiatric Crime database and mixed-effects models are utilized for this purpose.
Results:
A typical fraudster's profile is defined as a 53-year old male psychiatrist who victimizes one or two of the largest federal insurance programs in states with high property crime ratios. The results revealed the year and state where the fraud is prosecuted explain the largest portion of the variance in loss size. Predictably, case-specific factors also have a significant impact on the loss. Specifically, Medicaid, the existence of collusion, and fraudster's age are associated with the fraud loss.
Conclusions:
This study empirically justifies considering loss, due to healthcare fraud, from a multi-level perspective. Identified typical fraudster's and respective victim's profiles helped to elaborate on specific practical recommendations aimed at fraud prevention in the mental healthcare system in the US.
This study examines how the accounting profession disciplines its members for professional misconduct in periods of increased public scrutiny. We conjecture and find that increased public scrutiny of the Canadian accounting profession, marked by the establishment of the Canadian Public Accountability Board in 2003, is positively associated with the severity of punitive sanctions administered by the profession’s disciplinary committees. We find that disciplinary committees are more likely to also demand rehabilitation outcomes and greater future monitoring for offenders. Finally, reporting of discipline outcomes has increased in outlets internal to the accounting profession, but not in publications targeted outside to the public. This latter finding is consistent with the private interest theoretical model of professional ethics developed by Parker (Acc Organ Soc 19:507–525, 1994) as evidence of a latent motivation of the profession to protect its professional private interests. Exploratory analyses indicate that punishment, rehabilitation, and reporting in external publications significantly influence whether offenders return to good standing.
The study intends to study consumers' perception towards over-the-counter (OTC) products and factors that influences OTC products in India. It also aims to study the impact of demographic variables on consumers' purchase behaviour towards OTC products. The research is exploratory in nature. It is based on primary data. Primary data are collected via a questionnaire. Thirty respondents participated as a test case to understand and validate the questionnaire. The data obtained are analysed to identify the consumers' perception towards over-the-counter products. It was done in period of 1–30 October 2015. The respondents are from Mumbai – a metropolis and Nasik – a class city by population. Totally 180 respondents participated on a random basis. There were 90 respondents each from Mumbai and Nasik. Respondents were contacted on a random basis. Consumers' perception towards OTC is studied. Demographic variables are considered too for studying the perceptions between two cities. It is observed in our study that there is a significant difference in the perception for OTC based on gender and age. Doctors’ advice, brand name, pharmacist's advice, past experience, safe to use, prior awareness, friends' advise, testimonial from users are influencing factors that affect purchase behaviour of OTC products. This is the first time a study is done in emerging markets like India, compared to western countries whose market is well developed.
Understanding of the factors consumer consider, while purchasing and repurchasing over-the-counter (OTC) pharmaceutical products, will be of great help to the marketers. Identified factors can be used to position the products in the direct-to-consumer advertising. The research is an exploratory in the nature. It is based on the primary data. Primary data are collected via questionnaire. Three hundred respondents participated in the study. The respondents are from Metro and A class city and B class city. There were 100 respondents each from Mumbai, Nashik, and Pimpalgaon. Respondents are selected on a random basis. Factors influencing the consumer purchase behaviour are analysed on quantitative and qualitative features. It was observed that five factors – influencers, reliability, awareness, corporate image, and promotion – are responsible for the purchase of OTC pharmaceutical products. Medicinal factors, aesthetics, and producer’ image also have a major influence on purchase of the OTC pharmaceutical products. However, there is variance in the role of factors among the three cities. In this study, we tried to incorporate the theory of planned behaviour (Ajzen I. Attitudes, personality, and behavior. Homewood (IL): Dorsey Press; 1988) and extension of the theory of reasoned action (Ajzen I, Fishbein M. The prediction of behavior from attitudinal and normative variables. J Exp Soc Psychol. 1970;6:466–487. DOI:10.1016/0022-1031(70)90057-0) to develop and predict consumer behaviour using factor analysis.
Objective
To identify the method used in detecting fraud cases.
Methods
Articles searching by using topic-appropriate keywords and incorporated into search engines (data-based) journals Pubmed/Medline, Cochrane, Wiley, ScienceDirect, and secondary data-based Google scholar. Then data extraction is done based on inclusion criteria. The selected articles have the aim of investigating/detecting cases of fraud that have occurred in the health sector or other related sectors that support the study.
Results
The findings of the nine reviewed articles have suggested that most of the fraud perpetrators are performed by medical personnel (doctors) and providers. Many types of fraud occur such as insurance claims or medical actions that are completely unadministered nor following the procedure and duplicating claims. The methods that appropriate to be used in detecting fraud are secondary data tracking, information, and technology specialist provision.
Conclusion
Secondary data tracking is the most widely used method in fraud detection. Fraud perpetrators are ones who dominated by medical circles with fictitious claim cases. Perpetrators tend not to act themselves but in organizations with network.
Purpose
To make readers aware of the extensiveness of healthcare fraud in the U.S. and how it involves and affects the government, healthcare providers, insurance companies, patients, and the public. In addition, recommendations are made that may help control this pervasive type of fraud.
Design/methodology/approach
A range of different journal publications, information from government health institutions and law enforcement websites, healthcare fraud cases and healthcare laws are used as a basis to provide information about how fraudsters are committing healthcare fraud and how to prevent this fraud from occurring.
Findings
Despite increased funding and prosecution efforts by the government, healthcare fraud continues to be a major threat to the U.S. economy and public. While healthcare fraud will never be eradicated, specific efforts can be deployed to help rein in these complex fraud schemes.
Practical implications
The paper provides a useful resource of information on healthcare fraud for healthcare providers, insurance companies, patients, and the public that may help combat healthcare fraud and prevent financial losses.
Originality/value
This paper provides recommendations regarding healthcare fraud that could help prevent this large drain on the U.S. economy.
Health care fraud is a costly, challenging problem in health insurance. This study provides a systematic evaluation and synthesis of the methodologies and data samples used in current peer-reviewed studies from different academic fields on characterizing health care fraud. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement was used to guide reviewing the literature. In addition, a qualitative case study approach was employed to assess the studies included in the review in order to independently confirm the conclusions of the systematic review. Out of the 450 articles that were identified by the search criteria, 27 studies were deemed as relevant and included in the analysis. Using 24 variables designed from the literature to synthesize the fraud detection methodologies, the systematic review showed an inability to compare studies quantitatively because few studies reported the accuracy of their detection methods or the overall rate of fraud. The qualitative assessment independently confirmed that prior studies are highly diverse, with the only common characteristic being widespread use of data mining methods. Applying a previously validated approach that has not been taken by prior health care fraud reviews, our qualitative method showed high validity in terms of reviewers’ agreement on the classification of fraud detection methods (r = 93%). Two limitations of this study are that the strength of the evidence is reliant on the quality and number of studies previously performed on the topic, and our systematic review and qualitative results were limited to the text of the final studies as published in peer-reviewed journals. The main gaps we identified are the need to validate existing methods, lack of proof of intent to commit fraud, absence of a fraud rate estimate in the studies analyzed, and inability to use prior evidence to select the best fraud detection method(s). Additional research designed to address these gaps would be of value to researchers, policymakers, and health care practitioners who aim to select the best fraud detection methods for their specific area of practice.
Purpose
– The purpose of this paper is to examine the international mobility of physicians by comparing the regulations governing the practice of foreign physicians in the USA and eight other countries.
Design/methodology/approach
– This is a comparative study of the regulations governing the practice of foreign physicians in eight countries: China, India, the Philippines, the UK, Germany, Denmark, Israel and Australia. Their requirements are then contrasted with the USA’s requirements for foreign physician licensure to evaluate the extent of reciprocity among these countries. We conclude the paper by outlining some recommendations to increase the international mobility of physicians in the future.
Findings
– The results indicate that licensure for US physicians to practice in the nations above ranges from impossible (India), to difficult (China), to moderately difficult (the UK, Germany and Denmark), to easy and completely reciprocal (Australia, Israel and the Philippines).
Originality/value
– The results and recommendations in this study are a valuable starting point for further research and policy changes that will ensure a more reciprocal relationship between the USA and other countries, in terms of opportunities for international medical practice.
The identification of health care professionals who are incompetent, impaired, uncaring or have criminal intent has received increasing attention in recent years. These individuals are often subject to disciplinary action by professional licensing authorities. To date, no national data exist for Canadian physicians disciplined for professional misconduct. We sought to describe the characteristics of physicians disciplined by Canadian professional licensing authorities.
We constructed a database of physicians disciplined by provincial licensing authorities during the years 2000 to 2009. Comparisons were made with the general population of physicians licensed in Canada. Data on demographic characteristics, type of misconduct and penalty imposed were collected for each disciplined physician.
A total of 606 identifiable physicians were disciplined by their professional college during the years 2000 to 2009. The proportion of licensed physicians who were disciplined in a given year ranged from 0.06% to 0.11%. Fifty-one of the disciplined physicians committed 64 repeat offences, accounting for a total of 113 (19%) offences. Most of the disciplined physicians were independent practitioners (99%), male (92%) and trained in Canada (67%). The most common specialties of physicians subject to disciplinary action were family medicine (62%), psychiatry (14%) and surgery (9%). For disciplined physicians, the average number of years from medical school graduation to disciplinary action was 28.9 (standard deviation [SD] = 11.3). The 3 most frequent violations were sexual misconduct (20%), failure to meet a standard of care (19%) and unprofessional conduct (16%). The 3 most frequently imposed penalties were fines (27%), suspensions (19%) and formal reprimands (18%).
A small proportion of registered physicians in Canada were disciplined by their medical licensing authorities. Sexual misconduct was the most common disciplined offence. The standardization of provincial reporting along with the creation of a national database of physician offenders would facilitate more comparable public reporting as well as further research and educational initiatives.
This study determined the risk of discipline by a medical board for psychiatrists relative to other physicians and assessed the contributions to such risk.
Physicians disciplined by the California Medical Board in a 30-month period were compared with matched groups of nondisciplined physicians.
Among 584 disciplined physicians, there were 75 (12.8%) psychiatrists, nearly twice the number of psychiatrists among nondisciplined physicians. Female psychiatrists were underrepresented in the disciplined group. Psychiatrists were significantly more likely than nonpsychiatrist physicians to be disciplined for sexual relationships with patients and about as likely to be charged with negligence or incompetence. The disciplined and nondisciplined psychiatrists did not differ significantly from a group of 75 nondisciplined psychiatrists on years since medical school graduation, international medical graduate status, or board certification. The disciplined group included significantly more psychiatrists who claimed child psychiatry as their first or second specialty and significantly fewer psychoanalysts.
Organized psychiatry has an obligation to address sexual contact with patients and other causes for medical board discipline. This obligation may be addressable through enhanced residency training, recertification exams, and other means of education.
This paper examines the impact of corruption on foreign direct investment (FDI). It argues that corruption results not only in a reduction in FDI, but also in a change in the composition of country of origin of FDI. It presents two key findings. First, corruption results in relatively lower FDI from countries that have signed the Organization for Economic Cooperation and Development Convention on Combating Bribery of Foreign Public Officials in International Business Transactions. This suggests that laws against bribery abroad may act as a deterrent against engaging in corruption in foreign countries. Second, corruption results in relatively higher FDI from countries with high levels of corruption. This suggests that investors who have been exposed to bribery at home may not be deterred by corruption abroad, but instead seek countries where corruption is prevalent. Journal of International Business Studies (2006) 37, 807–822. doi:10.1057/palgrave.jibs.8400223
The inauguration of the Medicaid program in the mid 1960s ultimately led to the appearance of a wide range of new forms of illegal behavior by physicians. The fact that government authorities, instead of individual patients, were responsible for payments undoubtedly encouraged the large number of violations. A review of the background of sanctioned physicians shows an overrepresentation of psychiatrists and foreign medical graduates as well as minority-group physicians. Interviews with physicians sanctioned for Medicaid fraud and abuse indicated that they routinely placed the blame for their violations on the program, their employees, patients, or others. In particular, they find program guidelines confusing and irrational and insist that they intrude on what ought to be independent medical judgments. The enforcers, for their part, maintain that the convicted physicians are merely rationalizing self-serving and greedy behavior.
(JAMA. 1991;266:3318-3322)
We study cultural norms and legal enforcement in controlling corruption by analyzing the parking behavior of United Nations officials in Manhattan. Until 2002, diplomatic immunity protected UN diplomats from parking enforcement actions, so diplomats' actions were constrained by cultural norms alone. We find a strong effect of corruption norms: diplomats from high-corruption countries (on the basis of existing survey-based indices) accumulated significantly more unpaid parking violations. In 2002, enforcement authorities acquired the right to confiscate diplomatic license plates of violators. Unpaid violations dropped sharply in response. Cultural norms and (particularly in this context) legal enforcement are both important determinants of corruption. (c) 2007 by The University of Chicago. All rights reserved..
The inauguration of the Medicaid program in the mid 1960s ultimately led to the appearance of a wide range of new forms of illegal behavior by physicians. The fact that government authorities, instead of individual patients, were responsible for payments undoubtedly encouraged the large number of violations. A review of the background of sanctioned physicians shows an overrepresentation of psychiatrists and foreign medical graduates as well as minority-group physicians. Interviews with physicians sanctioned for Medicaid fraud and abuse indicated that they routinely placed the blame for their violations on the program, their employees, patients, or others. In particular, they find program guidelines confusing and irrational and insist that they intrude on what ought to be independent medical judgments. The enforcers, for their part, maintain that the convicted physicians are merely rationalizing self-serving and greedy behavior.
State medical boards discipline several thousand physicians each year. Although certain subgroups, such as those disciplined for malpractice, substance use, or sexual abuse, have been studied, little is known about disciplined physicians as a group.
To assess the offenses, contributing factors, and type of discipline of a consecutive series of disciplined physicians.
Case-control study on publicly available data matching 375 disciplined physicians with 2 groups of control physicians, one matched solely by locale, and a second matched for sex, type of practice, and locale.
All disciplined physicians publicly reported by the Medical Board of California from October 1995 through April 1997.
Characteristics of disciplined physicians, offenses leading to discipline, and type of discipline.
A total of 375 physicians licensed by the Medical Board of California (approximately 0.24% per year) were disciplined for 465 offenses. The most frequent causes for discipline were negligence or incompetence (34%), abuse of alcohol or other drugs (14%), inappropriate prescribing practices (11%), inappropriate contact with patients (10%), and fraud (9%). Discipline imposed was revocation of medical license (21%), actual suspension of license (13%), stayed suspension of license (45%), and reprimand (21%). Type of offense was significantly associated with severity of discipline (P=.03). In logistic regression models comparing disciplined physicians with controls matched by locale, board discipline was significantly associated with physicians' sex (odds ratio [OR] for women, 0.44; 95% confidence interval [CI], 0.28-0.70) and involvement in direct patient care (OR, 2.56; 95% CI, 1.75-3.75). In the regression model with additional matching criteria, disciplinary action was negatively associated with specialty board certification (OR, 0.42; 95% CI, 0.29-0.60) and positively associated with being in practice more than 20 years (OR, 2.02; 95% CI, 1.39-2.92).
A small but substantial proportion of physicians is disciplined each year for a variety of offenses. Further study of disciplined physicians is necessary to identify physicians at high risk for offenses leading to disciplinary action and to develop effective interventions to prevent these offenses.
Physicians who abuse their patients sexually cause immense harm, and, therefore, the discipline of physicians who commit any sex-related offenses is an important public health issue that should be examined.
To determine the frequency and severity of discipline against physicians who commit sex-related offenses and to describe the characteristics of these physicians.
Analysis of sex-related orders from a national database of disciplinary orders taken by state medical boards and federal agencies.
A total of 761 physicians disciplined for sex-related offenses from 1981 through 1996.
Rate and severity of discipline over time for sex-related offenses and specialty, age, and board certification status of disciplined physicians.
The number of physicians disciplined per year for sex-related offenses increased from 42 in 1989 to 147 in 1996, and the proportion of all disciplinary orders that were sex related increased from 2.1% in 1989 to 4.4% in 1996 (P<.001 for trend). Discipline for sex-related offenses was significantly more severe (P<.001) than for non-sex-related offenses, with 71.9% of sex-related orders involving revocation, surrender, or suspension of medical license. Of 761 physicians disciplined, the offenses committed by 567 (75%) involved patients, including sexual intercourse, rape, sexual molestation, and sexual favors for drugs. As of March 1997, 216 physicians (39.9%) disciplined for sex-related offenses between 1981 and 1994 were licensed to practice. Compared with all physicians, physicians disciplined for sex-related offenses were more likely to practice in the specialties of psychiatry, child psychiatry, obstetrics and gynecology, and family and general practice (all P<.001) than in other specialties and were older than the national physician population, but were no different in terms of board certification status.
Discipline against physicians for sex-related offenses is increasing over time and is relatively severe, although few physicians are disciplined for sexual offenses each year. In addition, a substantial proportion of physicians disciplined for these offenses are allowed to either continue to practice or return to practice.
The professional standards of international medical graduates have been the subject of controversy, but empirical research on this topic has been limited.
This report considers whether international medical graduates are at greater risk than US medical graduates for exclusion by the federal government from federally funded programs, such as Medicare and Medicaid.
The list of excluded physicians was merged with data regarding 87,729 family and general practice physicians from the American Medical Association Physician Masterfile, 555 of whom were currently excluded. Logistic regression was used to estimate the effect of international medical graduate status on the probability of exclusion, controlling for board-certification status and other physician characteristics. International medical graduates from high-income Organization for Economic Cooperation and Development (OECD) countries are distinguished from other international medical graduates.
The adjusted exclusion rates of international medical graduates from OECD countries were similar to that of US medical graduates. Among board-certified physicians, the relative risk of exclusion of non-OECD international medical graduates was 2.19 (P <0.001) compared with US medical graduates. Board certification had an even stronger association: US medical graduates who had never been board certified had a relative risk of 4.12 (P <0.001) compared with board-certified US medical graduates. The never board-certified relative risk was 1.72 (P <0.001) among non-OECD international medical graduates compared with board-certified graduates. Among physicians who had never been board certified, rates of US and international medical graduates did not differ substantially.
Further investigation is needed regarding the causal determinants of exclusion disparities. It is unclear to what extent these disparities may reflect differences in ethical conduct, quality of care, or prejudicial enforcement practices, and the extent to which board certification can causally reduce actions leading to exclusion.
Although physicians have been disciplined for a variety of offenses by state medical boards across the United States, limited information is available about the characteristics of these physicians. To assess the characteristics of, offenses committed by, and resulting disciplinary actions taken against a consecutive series of disciplined physicians in the state of Ohio, the authors conducted a case-control study of all 308 physicians publicly disciplined by the State Medical Board of Ohio (SMBO) from January 1997 to June 1999. Subjects were matched with two groups of control physicians--one matched by location only, and the second matched for location, gender, practice type, and self-designated specialty. The main outcomes measured were disciplinary actions, offenses leading to state medical board actions, and the characteristics of disciplined physicians. Of 340 physicians disciplined during these 30 months (approximately 0.37% per year), 308 committed 477 offenses requiring 409 actions by the SMBO. The most common offenses were impairment due to alcohol and/or drug use (21%), inappropriate prescribing or drug possession (14%), previous state actions (15%), negligence or incompetence (7%), and drug-related charges (7%). Although offenders were significantly less likely to be women (P < .05; odds ratio [OR], 0.46; 95% confidence interval [CI], 0.28-0.75), the authors found no difference in the severity of disciplinary action taken against offenders by gender (OR, 1.23; 95% CI, 0.54-2.82) or by type of medical training, ie, between osteopathic physicians and allopathic physicians (OR, 0.70; 95% CI, 0.39-1.26). Compared with controls matched for location, gender, practice type, and self-designated specialty, offenders were significantly less likely to be board certified (OR, 0.65; CI, 0.46-0.92) and significantly more likely to have been in practice 20 or fewer years (OR, 1.51; 95% CI, 1.08-2.13). Disciplinary actions in Ohio were more frequent, more severe, and more often in response to impairment due to alcohol and/or drug use and previous state actions than previously reported. No difference in the severity of disciplinary action was noted between men and women or between osteopathic and allopathic physicians.
Physician impairment is a serious public health issue affecting physicians as well as their families, colleagues, and patients. Though physicians generally display healthier habits than members of the general population, overall rates of impairment are similar among both groups, and prescription drug abuse (including prescription opioids) is particularly problematic among physicians. The current review focuses mainly on prescription opioid abuse and dependence among physicians. It includes a brief history of early physician experiences with anesthetic and analgesic agents, and explores several hypotheses regarding the etiology of prescription opioid abuse and dependence among physicians. Barriers to identification and to treatment entry among physicians are discussed. In addition, methods of assessment and successful treatment in specialized impaired physician programs are described. Medical and psychosocial interventions, 12-step involvement, and extensive use of evaluations are highlighted. Attention is paid to typical follow-up contracting and monitoring strategies, as well as strategies for prevention. Given the extremely positive outcomes demonstrated by specialized programs for treating impaired professionals, it is recommended that their methods be disseminated and utilized in treatment centers for the general public.