Monday, November 30, 2009

Clinical Trial Fraud - Lab Information, General Warning Signs of Misconduct

In my experience, questionable data is readily and easily detected in subject lab information and results. Clinical study staff are trained by education and are expected to know each protocol lab test and understand lab values, IUs and ranges and the proper way to fill out the lab forms. Lab protocols and tests are reviewed extensively during pre-study start Investigator Meetings with staff, monitors and PIs/SCs.

It is my practice as well as my recommendation when reviewing, monitoring and investigating subject lab information and results - do not just log the test...instead, read, read the test and the results, each data entry, read the entire form. A high frequency and incidence of data fraud at the clinical study site will, most definitely, be found in subject lab data.

Where and How?
  • Panic values on labs coded "1" and no comment is made by PI
  • Labs not evaluated prior to entrance into the clinical study
  • Technical units are expressed several different ways by staff and PI/SC.
General Warning Signs of Misconduct - What are these? Easy to identify for a monitor who is clear and present...
  • High staff turnover
  • Staff are disgruntled
  • Staff are fearful
  • Staff are anxious
  • Staff are depressed
  • Staff are defensive
  • High pressure work environment
  • Obsession with study payments
  • Absent PIs
  • Absent SCs
  • Absent staff
  • Lack of GCP training
  • Unusually fast recruitment.
Monitoring with Quality Control is a full time job and when done correctly, GCP is clear and misconduct and fraud are easily seen in trends and such. Choose and interview your clinical PIs, SCs, staff, CRO and/or consultant CRAs/CRCs and monitors carefully. Train them on GCP and QC and QA. Monitor their visits, reports, correspondence, communication and performance.

As well, there is clinical study data that falls into the "miscellaneous" subject data category - interestingly, not significant to subject outcomes or endpoints, but will point a finger at data trends leading to the identification of clinical fraud. These categories will be highlighted in my next blog pertaining to clinical fraud at the clinical study site.

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