Lilly in the news

“rewrites factual data provided by subject matter experts to formulate responses she feels are more beneficial.”

Lilly hit by staff accusations, FDA scrutiny at COVID drug factories

Yesterday Reuters published a piece based on a purported recent internal complaint at Lilly on a Quality leader purportedly falsifying data.

This comes on top of a March report that “Insider alleges Eli Lilly blocked her efforts to sound alarms about U.S. drug factory.”

Lilly has had several decades of “promising to address GMP issues.” Are these signs of not addressing cultural issues? Of the balkanization of fixes? Of the infamous pendulum swing? I have no insight, but as an individual who was involved in the work of consent decree remediation at another company, I certainly have lots of questions about what is up at Lilly.

Falsification and error

At the heart, data integrity is a lot about culture. There are technical requirements, but mostly we are returning to the same principles as quality culture and just keep coming back to Deming. A great example of this is the use of the fraud triangle and human error.

The fraud triangle was developed by Donald Cressey in the 1950s when investigating financial fraud and embezzlement. The principles Cressey identified are directly relevant to data integrity, and to quality culture as a whole.

Falsification Triangle
Element Exists When To Break
Incentive or Pressure Why commit falsification of data? Managerial pressure or financial gains are the two main drivers here to push people to commit fraud. Setting unrealistic objectives such as stretch goals, turnaround time or key performance indicators that are totally divorced from reality especially when these are linked to pay or advancement will only encourage staff to falsify data to receive rewards. These goals coupled with poor analytical instruments and methods will only ensure that corners will be cut to meet deadlines or targets. Management must lead by example – not through communication or establishing data governance structures but by ensuring the pressure to falsify data is removed. This means setting realistic expectations that are compatible with the organization’s capacity and process capability.
Rationalization or Incentive To commit fraud people must either have an incentive or can rationalize that this is an acceptable practice within an organization or department. Staff need to understand how their actions can impact the health of the patient. Ensure individuals know the importance of reliable and accurate data to the wellbeing of the patient as well as the business health of the company.
Opportunity The opportunity to falsify data can be due to encouragement by management as a means of keeping cost down or a combination of lax controls or poor oversight of activities that contribute to staff being able to commit fraud. Implement a process that is technically controlled so there is little, if any, opportunity to commit falsification of data.

Mistakes are human nature – we all have fat finger moments. This is why we build our processes and technologies to ensure we capture these errors and self-correct them. These errors should be tracked and trended, but only as a way to drive continuous improvement. It is important to have the capability in your quality systems to be able to evaluate mistakes up-to-and including fraud.

It helps to be able to classify issues and determine if there are changes to governance, management systems and behaviors necessary.

Events should be classified based on how intentional they are

Human error should be built into investigative systems. Yes, whenever possible we are looking for technical controls, but the human exists and needs to be fully taken into consideration.

The best way to ensure data integrity is the best way to build a quality culture.

System Model