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Record W2264005964 · doi:10.1136/bmj.i293

Statutory regulation needed to expose and stop medical fraud

2016· editorial· en· W2264005964 on OpenAlexaboutno aff
Richard Smith

Bibliographic record

VenueBMJ · 2016
Typeeditorial
Languageen
FieldHealth Professions
TopicMedical Malpractice and Liability Issues
Canadian institutionsnot available
Fundersnot available
KeywordsMisconductGovernment (linguistics)Scientific misconductMistakeResearch integrityMalpracticeStatutory lawPolitical sciencePsychologyLawMedicinePublic relationsAlternative medicine

Abstract

fetched live from OpenAlex

Anjan Kumar Banerjee, a surgeon, spent the years 2002 to 2008 erased from the medical register for serious professional misconduct related to research fraud, financial misconduct, and substandard care, yet in 2014 he was awarded an MBE “for services to patient safety.” This embarrassing mistake was quickly rectified, and theMBE forfeited. But he remains a fellow of three medical colleges. Each either awarded him or reinstated a fellowship after his erasure, and the University of London has not withdrawn his MS degree, which has been known for 15 years to be based on fraudulent data. The long sorry story of Banerjee that cardiologist Peter Wilmshurst tells in the linked analysis article, and has told in part before, raises serious questions about the integrity of medical and scientific institutions. Wilmshurst’s story comes a few weeks after an article in the Times Higher Education about a report to government that says: “Senior figures in UK science have warned that despite decades of awareness of the cultural problems driving misconduct in science, little progress has been made...The draft... concludes that some research institutes, university administrators, funders, journals and science leaders have been covering up malpractice.” It’s splendidly ironic that this report is an unpublished “secret dossier.” But what the report says is not news. The United States had several high profile cases of research misconduct in the 1970s and ’80s, and in 1989 the government established the body that became later the Office of Research Integrity. It covers only medical research that is government funded, but it has real powers. Anxieties about research misconduct in Britain began to be raised in the ’90s, with Stephen Lock, the editor of The BMJ, taking a lead. It seems fair to say, however, that Britain has never taken the problem seriously. Despite a high level consensus statement on researchmisconduct organised by The BMJ and the Committee on Publication Ethics, the UKResearch Integrity Office (where I was a trustee) is poorly resourced and has no powers, and the Concordat to Support Research Integrity is largely a bureaucratic exercise that critics would say is designed to give the appearance of taking action but without the necessary commitment of resources to make a difference. The “secret dossier” may be a prelude to government action because, as the Chinese have recognised, an economy built on science has to have robust ways of ensuring the integrity of that science. Britain has failed to mount an adequate response for two main reasons. Firstly, many scientific leaders still do not acknowledge the seriousness of the problem, fooling themselves that research misconduct is rare, science is self correcting, and misconduct is a victimless crime. Secondly, universities jealously guard their independence: even though they depend heavily on government funding they don’t want government bodies having powers to investigate possible misconduct of their researchers. But universities clearly have a major conflict of interest when one of their researchers is accused of misconduct, particularly if he or she is eminent. It is tempting to try to bury the whole thing, perhaps encouraging the miscreant to retire early or move on rather than be investigated. Until recently, and probably even now, universities and other institutions could be confident that they would get away with burying the case. Wilmshurst has many other disturbing stories in addition to the Banerjee one; these, as he writes, can often not be told publicly because of the expense and difficulty of getting them through lawyers.The BMJ recently published an account of the case of R K Chandra, who was investigated by his Canadian university in the 1990s and found to have produced fraudulent research. 11 The university took no action, and all that it has done so far is agree that a paper retracted 10 years ago was fraudulent.The BMJ and other journals belonging to the Committee on Publication Ethics have over the years asked many other research institutions to investigate worries, and often nothing has happened. We have no way of knowing how many cases are successfully covered up, but when talking to meetings on research misconduct, including one of European medical school deans, I ask how many people know of a case of research misconduct. Usually a half to a third of people put up their hands. I then ask whether the case was fully investigated, and if appropriate the perpetrator punished and the record corrected: hardly any hands remain raised.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.058
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.085
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.058
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0090.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.044
GPT teacher head0.487
Teacher spread0.443 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEditorial

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2016
Admission routes1
Has abstractyes

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