The role of the Clinical Data Manager has evolved. Data Managers play a more critical role in the clinical trial process than ever before. With the sheer number of trials being conducted at a global level and increasing pressure from regulatory authorities, clinical data management teams are managing higher volumes of data with a need to respond to the diversity of data coming in. (Clinical Leader, November 2017).
According to a recent study, clinical and safety data is coming from new and diverse sources:
- Real world data and evidence
- Electronic clinical outcomes assessments
- Data from smartphones and mobile devices
- Social media community data
- Electronic health/medical records
Studies indicate that a significant majority of companies have their clinical data management team in one location but managing global responsibilities. With the internationalization of clinical research, this could present challenges in terms of cultural fit and training requirements which, in turn, may affect a company’s KPIs in terms of quality and total biometrics oversight.
While EDC systems have become the norm in clinical trials, some data managers are finding them limited in that they only effectively manage traditional, structured data. How can data management teams manage any incoming unstructured data? Are data managers technically capable of managing these various applications?
The clinical data management study points out that in the past ten years, there have been no significant improvements to the long cycle times for database build and lock. Several factors contribute to this including trial design and protocol elements, varying data management practices and potential process and training issues. According to the market survey, 15 percent of respondents cite database design functionality as the main reason for these long cycle times.
Is it time to rethink the process?
As the changing landscape of clinical data management becomes more apparent, is it time to rethink how we implement a strategy? Is it time to outsource, or time to outsource better and more efficiently?
Functional Service Provision has long been an outsourcing strategy of larger pharmaceutical companies to account for peaks or gaps in the workload with temporary resourcing solutions.
However, this outsourcing model can provide benefits to Sponsors – both SMEs and large companies – who are looking to implement a quality solution to clinical data management.
Traditional FSP calls for a scalable team of resources to meet immediate or longer-term resourcing needs through on-site or FTEs. However, FSP can be adapted and scaled to meet the needs of any size company, any study size and phase.
FSP is no longer just a matter of resourcing, there are various elements that make it a successful outsourcing strategy for data management:
- Defined and specific KPIs and governance to meet expectations such as database build times
- Demonstrated expertise by geography, therapeutic area and subject matter
- Cultural fit and skills requirements assessment
- Guaranteed coverage of all absences: sick leave, holidays, etc
- Training and integration of SOPs, processes and technology
CROS NT refers to this as the Sustainable Quality FSP model.
Implementing an FSP strategy can account for some of the challenges outlined above. For example, through FSP the resources can be localized reporting to a project manager within the Sponsor’s team and an FSP Manager or global CDM manager at the global headquarters. It allows the data management resources to be familiar with the Sponsor’s processes and technologies and also benefits from using resources exposed to multiple differnet types of technologies. This can help Sponsors have better technology proficiency and improve timelines.
The traditional FSP model is also scalable for SMEs (small medium enterprises) who do not wish to set up a full data management or biometrics department but still need the resourcing solutions. Micro FSP is a more scalable and flexible FSP model that provides expert resourcing solutions while avoiding the risk of not having enough work, or too much work, for full time employees. The model is scalable to the specific needs of the company by providing resources for the number of days per week needed or technical experts in a specific area of focus. This is an ideal solution for when a Data Manager is needed for a specific project.
CROS NT has created a 5-point Sustainable Quality model for FSP for biometrics areas such as Clinical Data Management to support Sponsors with gaps in their workload. In terms of clinical data management we can support sponsors with:
- Database build, design and validation
- Data Management Plan
- CRF Design and review
- Data entry, cleaning and coding
- Risk Management Metrics to facilitate Risk-Based Monitoring
- Data Managers with expertise in various, market-leading EDC systems