Detection of species fraud in meat products is important for consumer protection and food industries. A molecular technique such as PCR method for detection of beef, sheep, pork, chicken, donkey, and horse meats in food products was established. The purpose of this study was to identification of fraud and adulteration in industrial meat products by PCR-RFLP assay in Iran. In present study, 224 meat products include 68 sausages, 48 frankfurters, 55 hamburgers, 33 hams and 20 cold cut meats were collected from different companies and food markets in Iran. Genomic DNA was extracted and PCR was performed for gene amplification of meat species using specific oligonucleotid primers. Raw meat samples are served as the positive control. For differentiation between donkey’s and horse’s meat, the mitochondrial DNA segment (cytochrome-b gene) was amplified and products were digested with AluI restriction enzyme. Results showed that 6 of 68 fermented sausages (8.82%), 4 of 48 frankfurters (8.33%), 4 of 55 hamburgers (7.27%), 2 of 33 hams (6.6%), and 1 of 20 cold cut meat (5%) were found to contain Haram (unlawful or prohibited) meat. These results indicate that 7.58% of the total samples were not containing Halal (lawful or permitted) meat and have another meat. These findings showed that molecular methods such as PCR and PCR-RFLP are potentially reliable techniques for detection of meat type in meat products for Halal authentication.
PCR-RFLP; Mitochondrial DNA; Meat species; Haram; Halal; Iran
Highly publicized cases of fabrication or falsification of data in clinical trials have occurred in recent years and it is likely that there are additional undetected or unreported cases. We review the available evidence on the incidence of data fraud in clinical trials, describe several prominent cases, present information on motivation and contributing factors and discuss cost-effective ways of early detection of data fraud as part of routine central statistical monitoring of data quality. Adoption of these clinical trial monitoring procedures can identify potential data fraud not detected by conventional on-site monitoring and can improve overall data quality.
central statistical monitoring; data fabrication and falsification; data fraud; data quality
OBJECTIVES: To study and describe how a group of senior researchers and a group of postgraduate students perceived the so-called "grey zone" between normal scientific practice and obvious misconduct. DESIGN: A questionnaire concerning various practices including dishonesty and obvious misconduct. The answers were obtained by means of a visual analogue scale (VAS). The central (two quarters) of the VAS were designated as a grey zone. SETTING: A Swedish medical faculty. SURVEY SAMPLE: 30 senior researchers and 30 postgraduate students. RESULTS: Twenty of the senior researchers and 25 of the postgraduate students answered the questionnaire. In five cases out of 14 the senior researchers' median was found to be clearly within the interval of the grey zone, compared with three cases for the postgraduate students. Three examples of experienced misconduct were provided. Compared with postgraduate students, established researchers do not call for more research ethical guidelines and restrictions. CONCLUSION: Although the results indicate that consensus exists regarding certain obvious types of misconduct the response pattern also indicates that there is no general consensus on several procedures.
Assignment of an individual to the population from which it most probably originated based on its multilocus genotype has been widely applied in recent years. In this study, individual assignment based on microsatellite data was used to identify a case of fishing competition fraud. Despite the fact that the true population of origin was most probably not among the reference populations, recent modifications of the assignment tests were used in confidently excluding (p < 0.0001) the possibility of a 5.5 kg salmon (Salmo salar) originating from the fishing competition location, Lake Saimaa (south-east Finland). In fact, the probability of the suspect salmon originating from one of the regions that supply most of Finland's fish markets was found to be over 600 times higher than it originating from Lake Saimaa. When presented with this evidence, the offender confessed to purchasing the salmon at a local fish shop and criminal charges were laid. This study emphasizes the potential practical application of the individual assignment procedure, in particular the usefulness of confidently excluding populations as the origin of an individual. A similar strategy could be also used, for example in suspected cases of illegal poaching, in order to assign or exclude individuals from originating from a claimed population.
In medicine, research misconduct is historically associated with laboratory or pharmaceutical research, but the vulnerability of epidemiological surveys should be recognized. As these surveys underpin health policy and allocation of limited resources, misreporting can have far-reaching implications. We report how fraud in a nationwide headache survey occurred and how it was discovered and rectified before it could cause harm.
The context was a door-to-door survey to estimate the prevalence and burden of headache disorders in Pakistan. Data were collected from all four provinces of Pakistan by non-medical interviewers and collated centrally. Measures to ensure data integrity were preventative, detective and corrective. We carefully selected and trained the interviewers, set rules of conduct and gave specific warnings regarding the consequences of falsification. We employed two-fold fraud detection methods: comparative data analysis, and face-to-face re-contact with randomly selected participants. When fabrication was detected, data shown to be unreliable were replaced by repeating the survey in new samples according to the original protocol.
Comparative analysis of datasets from the regions revealed unfeasible prevalences and gender ratios in one (Multan). Data fabrication was suspected. During a surprise-visit to Multan, of a random sample of addresses selected for verification, all but one had been falsely reported. The data (from 840 cases) were discarded, and the survey repeated with new interviewers. The new sample of 800 cases was demographically and diagnostically consistent with other regions.
Fraud in community-based surveys is seldom reported, but no less likely to occur than in other fields of medical research. Measures should be put in place to prevent, detect and, where necessary, correct it. In this instance, had the data from Multan been pooled with those from other regions before analysis, a damaging fraud might have escaped notice.
Fraud; Research misconduct; Epidemiology; Headache; Pakistan; Global Campaign against Headache
Using cross sectional data Psychological vulnerability was identified as a correlate of older adult’s being defrauded. We extend that research by examining fraud prevalence using longitudinal data from the Health and Retirement Study, and to identify the best predictors of fraud longitudinally across a 4-year time frame. Whereas reported fraud prevalence was 5.0% in a 5-year look-back period in 2008, it increased to 6.1% in 2012. The rate of new-incident fraud across only a 4-year look-back was 4.3%. Being younger-old, having a higher level of education, and having more depression significantly predicted the new cases of fraud reported in 2012. Psychological vulnerability was a potent longitudinal predictor of fraud, with the most vulnerable individuals being more than twice as likely to be defrauded. Results indicate that fraud victimization among older adults is rising, and that vulnerability variables, along with some demographic variables, predict new cases of fraud.
The amount of insurance fraud is increasing in Canada. This should worry physicians, because all personal-injury claims must be substantiated by a medical certificate. The vast majority of physicians are honest and ethical, fraud investigators say, but some are being duped as patients scheme to cheat the insurance industry. In one sensational auto-insurance-fraud case, some Ontario physicians are being investigated about possible involvement in a self-referral scheme. Nicole Baer looks at insurance fraud and the challenges it poses for doctors.
Widely reported cases of research fraud have eroded public confidence in scientific research. When funding agencies met last fall they underscored the importance of integrity in the research process and discussed steps that could be taken to promote it.
Peer review is an essential component of the process that is universally applied prior to the acceptance of a manuscript, grant or other scholarly work. Most of us willingly accept the responsibilities that come with being a reviewer but how comfortable are we with the process? Peer review is open to abuse but how should it be policed and can it be improved? A bad peer review process can inadvertently ruin an individual’s career, but are there penalties for policing a reviewer who deliberately sabotages a manuscript or grant? Science has received an increasingly tainted name because of recent high profile cases of alleged scientific misconduct. Once considered the results of work stress or a temporary mental health problem, scientific misconduct is increasingly being reported and proved to be a repeat offence. How should scientific misconduct be handled—is it a criminal offence and subject to national or international law? Similarly plagiarism is an ever-increasing concern whether at the level of the student or a university president. Are the existing laws tough enough? These issues, with appropriate examples, are dealt with in this review.
peer review; journal impact factors; conflicts of interest; scientific misconduct; plagiarism
Scientific misconduct and fraud occur in science. The (anonymous) peer review process serves as goalkeeper of scientific quality rather than scientific integrity. In this brief paper we describe some limitations of the peer-review process. We describe the catastrophic facts of the ‘Woo-Suk Hwang fraud case’ and raise some ethical concerns about the issue. Finally, we pay attention to plagiarism, autoplagiarism and double publications. (Neth Heart J 2009;17:25-9.)
double publications; fraud; scientific misconduct; peer review; plagiarism; stem cell research
Claims for reimbursement of child support, the reversal of property settlements and compensation can arise when misattributed paternity is discovered. The ethical justifications for such claims seem to be related to the financial cost of bringing up children, the absence of choice about taking on these expenses, the hard work involved in child rearing, the emotional attachments that are formed with children, the obligation of women to make truthful claims about paternity, and the deception involved in infidelity. In this paper it is argued that there should not be compensation for infidelity and that reimbursement is appropriate where the claimant has made child support payments but has not taken on the social role of father. Where the claimant's behaviour suggests a social view of fatherhood, on the other hand, claims for compensation are less coherent. Where the genetic model of fatherhood dominates, the “other” man (the woman's lover and progenitor of the children) might also have a claim for the loss of the benefits of fatherhood. It is concluded that claims for reimbursement and compensation in cases of misattributed paternity produce the same distorted and thin view of what it means to be a father that paternity testing assumes, and underscores a trend that is not in the interests of children.
paternity fraud; misattributed paternity; definition of “father”; genetics; genetic relatedness
Publication of medical research is the cornerstone for the propagation and dissemination of medical knowledge, culminating in significant effects on the health of the world's population. However, instances of individuals and institutions subverting the ethos of honesty and integrity on which medical research is built in order to advance personal ambitions have been well documented. Many definitions to describe this unethical behavior have been postulated, although the most descriptive is the “FFP” (fabrication, falsification, and plagiarism) model put forward by the United States’ Office of Research Integrity. Research misconduct has many ramifications of which the world's media are all too keen to demonstrate. Many high-profile cases the world over have demonstrated this lack of ethics when performing medical research. Many esteemed professionals and highly regarded world institutions have succumbed to the ambitions of a few, who for personal gains, have behaved unethically in pursuit of their own ideals. Although institutions have been set up to directly confront these issues, it would appear that a lot more is still required on the part of journals and their editors to combat this behavioral pattern. Individuals starting out at very junior positions in medical research ought to be taught the basics of medical research ethics so that populations are not failed by the very people they are turning to for assistance at times of need. This article provides a review of many of the issues of research misconduct and allows the reader to reflect and think through their own experiences of research. This hopefully will allow individuals to start asking questions on, what is an often, a poorly discussed topic in medical research.
Ethics; fraud; plagiarism; research; scientific misconduct; United States’ office of Research Integrity
This paper proposes an intelligent credit card fraud detection model for detecting fraud from highly imbalanced and anonymous credit card transaction datasets. The class imbalance problem is handled by finding legal as well as fraud transaction patterns for each customer by using frequent itemset mining. A matching algorithm is also proposed to find to which pattern (legal or fraud) the incoming transaction of a particular customer is closer and a decision is made accordingly. In order to handle the anonymous nature of the data, no preference is given to any of the attributes and each attribute is considered equally for finding the patterns. The performance evaluation of the proposed model is done on UCSD Data Mining Contest 2009 Dataset (anonymous and imbalanced) and it is found that the proposed model has very high fraud detection rate, balanced classification rate, Matthews correlation coefficient, and very less false alarm rate than other state-of-the-art classifiers.
In its one-and-a-half year history Genome Biology has witnessed the publication of the first plant genome, the first draft of the human genome (twice) and a more than doubling of the number of completed microbial sequences. There has also been a shift in 'functional genomics' away from simple microarray data and towards studies of the expression, structure and function of proteins, pathway and network analysis, and harnessing the power of comparative genomics. Debate has also raged over the past year on the importance and merits of providing immediate world-wide, barrier-free open access to the full text of research articles.
An electroencephalogram (EEG) signal is extremely nonstationary, highly composite and very complex, all of which reflects the underlying integral neurodynamics. Understanding the EEG “grammar”, its internal structural organization would place a “Rozetta stone” in researchers’ hands, allowing them to more adequately describe the information processes of the brain in terms of EEG phenomenology. This Special Issue presents a framework where short-term EEG spectral pattern (SP) of a particular type is viewed as an information-rich event in EEG phenomenology. It is suggested that transition from one type of SP to another is accompanied by a “switch” between brain microstates in specific neuronal networks, or in cortex areas; and these microstates are reflected in EEG as piecewise stationary segments. In this context multiple faces of a short-term EEG SP reflect the poly-operational structure of brain activity.
Electroencephalogram (EEG) phenomenology; short-term spectral patterns; neuronal assemblies; EEG oscillatory states; brain oscillations; EEG frequencies.
Electronic Health Records; Fraud; ONC
The cost of prescription drugs and medical devices has increased dramatically over the past several years. This increase has exceeded the annual average inflation index, making medical products desired sources of ill-gotten financial gains through diversion, theft, fraud, and deceit. With databases often being compromised, personal health information, personal identification, and therapy history are all available to be used by thieves through deception and misrepresentation, and are being traded on clandestine websites. With increasing values of medical services, wanted efforts continue to emerge in profiteering schemes, using illicit deals for financial gains by exploiting what was once perceived as sacred areas of medical care. Estimates of healthcare resource costs in dollars, lives, and products exceed $200 billion. Select examples of fraud in our medical services are presented that expose plan members to the risks of loss and theft that can compromise the privacy of their health records. The author outlines prevention steps for payors to guard against such practices.
Telemarketing fraud is pervasive and older consumers are disproportionally targeted. Given laboratory research showing that forewarning can effectively counter influence appeals, we conducted a field experiment to test whether forewarning could protect people who had been victimized in the past. A research assistant with prior experience as a telemarketer pitched a mock scam two or four weeks after participants were warned about the same scam or an entirely different scam. Both warnings reduced unequivocal acceptance of the mock scam although outright refusals (as opposed to expressions of skepticism) were more frequent with the same scam warning than the different scam warning. The same scam warning, but not the different scam warning, lost effectiveness over time. Findings demonstrate that social psychological research can inform effective protection strategies against telemarketing fraud.
Telemarketing fraud; prevention; forewarning; decision making; aging
The 1990s state litigation that resulted in the tobacco industry's initial document disclosure obligations fully expired in 2010. These obligations have been extended and enhanced until 2021 through a federal lawsuit against the tobacco industry over violations of the Racketeer Influenced Corrupt Organizations Act (RICO). In this special communication, we summarise and explain the new legal framework and enhanced document disclosure obligations of the major US tobacco companies. We describe the events leading up to these new requirements, including the tobacco companies’ failed attempt to close the Minnesota Tobacco Document Depository, the release of 100 000 documents onto the companies’ document websites discovered to have been publicly available at the Minnesota Tobacco Document Depository but not online, and the addition of over 2300 documents to those websites, which are also now publicly available at Minnesota after being secured for years in a separate, non-public storage room at the Minnesota Tobacco Document Depository. We also detail the document indexing enhancements and redesign of the University of California, San Francisco's Legacy Tobacco Documents Library website, made possible by the RICO litigation, and which is anticipated to be released in September 2014. Last, we highlight the public health community's continued opportunity to expose the US tobacco industry's efforts to undermine public health through these new search enhancements and improved document accessibility and due to the continuously growing document collection until at least 2021.
Litigation; Tobacco Industry; Tobacco Industry Documents
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 5 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 (54%) were ‘suspects’ of conducting abusive behavior. The results also identified 2% 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 (98%) and abuse (85%) 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.
Healthcare; Fraud; Abuse; Insurance; Data Mining; General Physician
Inappropriate payments by insurance organizations or third party payers occur because of errors, abuse and fraud. The scale of this problem is large enough to make it a priority issue for health systems. Traditional methods of detecting health care fraud and abuse are time-consuming and inefficient. Combining automated methods and statistical knowledge lead to the emergence of a new interdisciplinary branch of science that is named Knowledge Discovery from Databases (KDD). Data mining is a core of the KDD process. Data mining can help third-party payers such as health insurance organizations to extract useful information from thousands of claims and identify a smaller subset of the claims or claimants for further assessment. We reviewed studies that performed data mining techniques for detecting health care fraud and abuse, using supervised and unsupervised data mining approaches. Most available studies have focused on algorithmic data mining without an emphasis on or application to fraud detection efforts in the context of health service provision or health insurance policy. More studies are needed to connect sound and evidence-based diagnosis and treatment approaches toward fraudulent or abusive behaviors. Ultimately, based on available studies, we recommend seven general steps to data mining of health care claims.
health care; data mining; KDD; Business Intelligence; insurance claim; fraud