Change comes in oh so many forms in a clinical trial:
- Changes to form design,
- Changes to workflow,
- Changes in site membership,
- Technology updates,
- Regulatory compliances changes,
- Data loss due to unexpected failures in hardware, IT networks, hacker, software bugs, etc.,
- Recruitment issues, and more.
One type of change that’s becoming more common is mid-study data migrations.
Mid-Study Data Migrations
We know many OpenClinica customers use more than one electronic data capture (EDC) system. While it often makes sense in the beginning, the continued use of various EDCs presents a multitude of challenges including user frustration, training and data management issues, and additional costs.
Traditionally, sites and sponsors have opted to wait until a study completes to roll off a particular EDC system. As anyone who works in the clinical trial space knows all too well, the wait can be quite long.
Clinical trials can take upwards of five years. According to the U.S. Food and Drug Administration (FDA), for example, the length of study for a phase 1 drug trial is several months. For phase 2, the range is several months to two years, and for phase 3, it is one to four years.
Now, there is a better way – and that’s why academic research organizations and contract research organizations are increasingly choosing to consolidate the number of EDCs while studies are ongoing. Once thought all-but-impossible, data migrations are seamlessly happening mid-study with no disruptions to ongoing clinical trials.
As experts in processing clinical trial data, OpenClinica leveraged its experience successfully migrating five studies in six months for a multinational company with $50+ billion in annual revenue to manage the process of migrating data for 14 active studies for a leading research university. To sign up for an early look at our upcoming case study, Migrating Data Mid-Study – 14 Studies in 16 Months, click here.
It’s worth noting the OpenClinica data management playbook, Managing Change in Clinical Trials, offers a proven pathway for change management whether the change your clinical trial is experiencing is a mid-study data migration, a planned update to your EDC systems or protocols or the addition of new trial sites.
Managing Change in Clinical Trials
Managing clinical trial changes starts with “identifying each stakeholder, their role in the study, and what they need.”
Key stakeholders include:
- Clinical Research Coordinators (CRCs) who are largely tasked with implementing protocols,
- Investigators who sign-off on the data,
- Patients,
- Data Scientists,
- Data Managers who are responsible for ensuring the smooth flow of quality data,
- Study Programmers, often technical personnel who update forms, logic, workflows, sites, and more,
- Monitors who perform the labor-intensive work of data quality assessment, protocol compliance review, and anomaly identification and
- IT Personnel.
As we wrote in the playbook, Managing Change in Clinical Trials, the hallmarks of successful change management are three focus areas:
- Engage: Involve stakeholders during the planning stages of the study.
- Communicate: Practice frequent communication, solicit feedback, and adjust expectations as necessary throughout the study.
- Manage Risk: Make a list of risks that could impact each stakeholder and assess/reassess it periodically. Involving staff provides invaluable input and buy-in for change. For a more formal and quantitative evaluation, use a risk assessment matrix.
In addition to identifying stakeholders, their roles and their needs, an effective change management framework also includes:
- The development of standard operating procedures and
- The creation of data-specific standard operating procedures such as:
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- Data entry, receipt, and handling,
- Database security,
- Data extraction and validation,
- Data retention and archival,
- Data validation
To learn more about our proven approach to manage change in clinical trials, download our playbook at: https://www.openclinica.com/managing-change-in-clinical-trials. To add your name to the list to preview our upcoming case study, Migrating Data Mid-Study – 14 Studies in 16 Months, click here.