Laboratory Data Integrity

Ashraf Mozayani, PharmD, PhDTexas Southern University

Barbara Jordan-Mickey Leland School of Public Affairs

Forensic Science Learning Lab

mozayania@tsu.edu

713-313-7332

Objectives

• Terminology associated with data integrity and data manipulation

• Why should we have a Plan to prevent and detect data manipulation/fraud?

• Situation that contribute to unethical behavior

• Steps to add to detect/avoid data manipulation

What is Data Integrity? Data that follows:

Ethical StandardsBe Acceptable in Scientific Community Be Traceable Be Defensible

Terms

Laboratory fraud: The falsification of analytical and quality assurance results, where failed method requirements are made to appear acceptable during reporting:

SamplingReceipt, Preparation,AnalysisReport writingTestifying

Terms

Intentional misrepresentation of lab data to hide existing or potential problems.

Intent to deceive – making data look better than it really is.

Dry Labbing – Reporting data for samples or procedures not actually analyzed or performed.

Data deletion – removal of bad/undesirable data. Backlogging – In this context, is the entry of data into a

laboratory document at a time later than the time indicated on the document

Time Travel- Changing times and dates

Why Should We Have A Plan?When it happens it causes :

Tainting our Lab StaffDistrust by our ClientsCost us Ruin Careers

Root Causes that Might Contribute to Unethical BehaviorAnalyst

Lack of Knowledge of testingLack of understanding the impactLack of courageDesire for perfect recordTo complete cases quickly in an

effort to meet deadlines

Root Causes that Might Contribute to Unethical BehaviorManagementIneffective Oversight Impractical ExpectationEmphasis on Production over Quality

Situations that Might Contribute to Laboratory Fraud To encourage boosting productivity

with obtaining better merit increases or bonuses

Conflict of interest with regards to a case

Lack of factual/ thorough technical and administrative review

Examples of Improper Lab Practices

PTBatch QCBlank Testimony

The Good News

The forensic scientists are good at what they do however we need to address this perceived problem:realize that NO system is error-freedesign and implement a program that ACTIVELY looks for weak spots and corrects them

And this leads to a better system – never perfect, but always better.

Suggestions to improve Data Integrity!$$$

Laboratory Data Integrity Policy

A systematic approach by laboratory to assure:Accurate data reflecting the test follows:

Analysis using accepted scientific practice and principles

Produce data that are traceable and defensible

Bias free environmentEthical Professional

Comply with all regulations associated with tasks, responsibilities, testimonies

Data Integrity Foundation

Thorough training the staff MonitoringConfidential reportingInvestigationCorrection

Staff Training

Training ProgramAll analysts should be competency testedPrior qualification and authorization should

be required to perform caseworkMock Trials should be conducted Court Testimony Evaluation should be

performed for testifying analystsMandatory Ethics Training of StaffCertification

Monitoring Data Integrity

StaffAnalytical InstrumentsTesting ProcessesOversight and Review

Monitoring Data Integrity: Staff

Experienced data reviewersThorough data review by outside expert

Including chain of custody, time stamps, signatures, and an evaluation of control data

Monitoring of computer updatesRandom, periodic observationBlind samplesDetailed review of each analyst data

Monitoring Data Integrity: Instrumentation

Analytical InstrumentationPreparation of the sample and operation of the instrument

should be performed by different individuals Instrument maintenance should be performed by individuals other

than the analyst if it is possible Calibration and tuning of instruments should be performed by an

individual other than the analyst.

All operations of the instrument should be recorded by the operator and reviewed by a qualified reviewer prior to release of the final report

All tuning, calibration and run data should be stored as PDF files immediately upon generation

Monitoring Data Integrity – The Testing Process

Testing ProcessBatching: multiple people work on a case and multiple

cases should worked together Implementing the use of unique barcode on all

samples Internal Chain of Custody: should be verified to track

the evidence. Everyone should be indicated on the chain of custody

Log Sheets, Derivative Evidence Log, and paper trail in case files

100 % Technical Reviews/Admin Reviews on all cases Taking photographs of evidence before and after

samplingPhotographing all subjective tests like microscopic

tests , color tests

Data Integrity Standard Operating Procedure- Purpose: to describe the laboratory’s data integrity

system to emphasize the importance of integrity in the

performance of all analytical work to acquire the commitment of laboratory staff

to the principle that all analyses shall be performed in a controlled and documented manner

to confirm that laboratory staff consistently meet the specific ethical requirements defined in this data integrity plan.

Dry-labbing, back filling or data manipulation/fraud is not wide spread

It can happen in any laboratory with any analyst

Learn from misfortune of other labsHave a strong Data Integrity Policy

Summary

Summary

All these programs require self-assessmentA painful process, but necessary if

we want to improveThis is NOT about not trusting our

colleagues. This IS about improving our system

Thank you for your time.

mozayaniA@tsu.edu713-313-7332