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Lessons Learned

When validating the one million data points that compose a typical Phase 3 trial, focusing on irrelevant mistakes could easily result in wasted resources. The industry’s initial response – in the form of risk-based monitoring (RBM) – detects errors and risks more efficiently, but can still expend resources on errors not pertinent to a study’s validity and, therefore, miss opportunities to define and solve critical quality issues.

What if we were to look to other industries’ strategies for risk mitigation, in order to evolve RBM into a more useful approach for protecting clinical data? One of these methodologies – namely human factor analysis (HFA) – is employed by NASA, Ford, the US Environmental Protection Agency, major airlines and several countries’ militaries to identify and mitigate human error in large, variously trained workforces. Closer to the pharmaceutical sector, human factors are the core to the foundation training by the WHO in its education on patient safety (1). HFA uses uniquely structured datasets to show underlying behaviours that are otherwise difficult for humans to sense or reconstruct but are, ultimately, the root cause of an incident.

Consider a site that has multiple issues with informed consent. A traditional monitoring approach would log a problem, potentially announce the site as high risk and deploy general retraining on informed consent. Instead, using HFA allows one to look for trends in the data and classify what they revealed in predetermined categories; for instance, consent errors became more frequent after that site had enrolled 100 or more patients. To mitigate risk, the project team could perhaps limit the site to no more than 75 patients and provide additional investigator support focusing on resource allocation.

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Clara Heering is Senior Vice President of Clinical Risk and Data Management at ICON, and has over 20 years’ experience in clinical research, which spans both CRO and pharma industries. Clara's previous experience includes 16 years at Pfizer and two years as Research Fellow at Harvard Medical School, US. She holds a degree in Risk Management and in Medical Biology.
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