Integrating Trial Data Processes Across Functional Areas using Electronic Data Capture (EDC) Technology

Transcription

1 Integrating Trial Data Processes Across Functional Areas using Electronic Data Capture (EDC) Technology Authors: Bill Gluck, PhD DATATRAK, VP of Clinical and Consulting Services Lorraine D. Ellis, MS, MBA Research Dynamics Consulting Group, Ltd., CEO 2011

2 2 of 8 Table of Contents 1 Introduction Process Workflow Changes Data Collection Recording Data Monitoring Cleaning Data Summary Overview of Process Changes and Benefits Focus on Clinical Ops and CDM Interactions Investigator Sites Benefits Clinical and Monitor Group Benefits Data Management Benefits Statistical Benefits Conclusion... 8

3 3 of 8 1 Introduction One common theme in the pharmaceutical, biotechnology and medical device industry is the constant pressure to accelerate development of drugs, biologics and products to market. Improvements usually tend to focus on one aspect of the development workflow at a time. One of the processes that is the most time and effort intensive is data collection and management. Clinical data workflows have traditionally been tweaked especially with the growing acceptance of new technology and more contemporary enterprise eclinical applications (those applications that include clinical trial management systems (CTMS), electronic data capture (EDC), randomization and drug supply, etc.). Today many companies are viewing procedures not only within but across functional areas as a necessity to streamline data flow and the development process. This white paper will describe some of the process re- engineering, role modification or definition, enhanced communication and project coordination improvements needed to implement the use of an EDC application across the functional areas of clinical monitoring, project management, Investigator sites, and clinical data management (CDM) so companies can maximize the benefits of today s technology. Electronic Data Capture technology has only been practiced widely in the industry for the past 5- to- 10 years even though it was introduced more than 25- years ago. Early EDC applications were more remote data entry stations that served only to move the data entry process to the sites; there were not many procedural or process changes. Also, early EDC software lacked the extensive functionality to evaluate the quality of the data that are found in today s systems. As the EDC application matured, it became evident that process, role and procedural changes were necessary in order to realize the full benefits of the technology. These changes were (are) not limited to changes within the management of data but also across the entire clinical trial process. 2 Process Workflow Changes Changing from a paper- based data collection system to an electronic- based data collection method requires changes in the approach to data collection, processing, and management. Processes in an EDC environment must be re- engineered to optimize all the benefits of the technology. For example, roles and responsibilities of the three key functional groups within a clinical study: the Investigator sites, Clinical Monitors and Clinical Data Managers need to be re- defined to realize the benefits of the technology. Investigator sites, for example, no longer complete paper case report forms as they enter the required data directly into the EDC application. Monitors now modify their monitoring procedures to review data before they go to the site so they can be more efficient in managing site trial performance and reviewing data against source documentation. Clinical data management too must adjust internal processes and procedures as there are many differences between paper- based approaches to collecting data versus an EDC approach. The flow of the data must be evaluated and roles and responsibilities of each task adjusted. For example, CDM in a paper- based environment would be responsible

4 4 of 8 for the assignment and resolution of data queries, whereas in an EDC application some of the assignment and resolution of queries may be distributed across CDM and the clinical monitoring group. To discuss the revised workflow of data using EDC, we have broken the data process into four key elements: collection, recording, monitoring and cleaning. 2.1 Data Collection The data collection process using EDC is considerably different than paper- based processes. In this context, data collection is defined as the design of the ecrfs and the underlying clinical database files during the start- up portion of the study. The EDC application design is critical as it needs to be completed in advance of the first patient being screened into a study; it must conform and follow the study protocol. Since the Investigator site personnel enter data into the ecrfs, the ecrfs must be designed for the workflow of the Investigator site as it conducts the protocol and records the data. The EDC application should be designed in such a manner to facilitate data exports to meet the needs of the staff performing the analysis. One benefit of a well- designed EDC application is improved protocol compliance. The flow of the EDC application from one ecrf screen to another should follow the flow of the study protocol. Thus, site coordinators are guided through the study not only by the protocol itself but through the screens of the application as they are completed. The ecrfs should contain edit checks that alert the Investigator site when they are in conflict with the protocol such as entering an ineligible patient or forgetting to complete a procedure and record the results. The design of an EDC application and ecrfs should include all functional groups involved in a clinical study. This involvement will require procedural changes that are different from paper- based studies in how the study is planned and initiated. Not only does the team need to identify what data are required for the study via reviews of the protocol but all edit checks must be defined and programmed into the application during the study design, not after the study has begun. Clinical staff should provide input on the flow of the ecrf to match clinical procedures and whether input is mandatory or voluntary. Field parameters, labels and ranges can also be provided by the clinical staff to enhance protocol compliance. Input from the biostatisticians is essential as critical data fields must be identified and included in the design specifications and programming. Because the design of the ecrfs and the database occurs before the study starts and is a team effort, the clinical staff must test drive the draft ecrfs with an Investigator site to ensure that the questions are worded appropriately, the field size and parameters are suitable for the data entry, and the order of the questions follows the protocol procedures for easier data entry. Because of the abilities of EDC to prevent inappropriate questions from being answered, the Clinical group also contributes to the decisions of when questions, such as pregnancy tests, should be answered.

5 5 of Recording Data One clearly defined difference in an EDC system from the traditional paper- based workflow is the need for Investigator site staff to enter their own patient data into the application. EDC systems must be designed to facilitate entry, easy to understand and easy to navigate, as site staff do not have the time to learn or use an intricate system. An advantage of most EDC systems is the functionality to alert the site staff when entries are entered erroneously and easily allows them to revise the entry without generating a time- consuming query. This process, only available when using EDC, eliminates many of the queries generated when paper CRFS are used. The EDC system speeds the generation, resolution and tracking of queries by providing the site staff the ability to easily make data corrections online instead of searching for and manually updating paper ecrfs. The process of documenting protocol compliance also becomes easier with EDC, as well- designed ecrfs prevent the entry of data that would be a protocol violation. The system alerts the site staff to improve protocol compliance and the entry of protocol compliant data. The use of field sizes, edit parameters and data ranges embedded in the ecrfs also improves the recording of data by the Investigator site staff, as these items provide an immediate feedback mechanism on the accuracy of the data being recorded. Site personnel can update incorrect or incomplete data instantly based on this feedback and eliminate queries. Both the immediate feedback and the reduction in queries change the processes at the site and increase site efficiency. 2.3 Monitoring The monitoring process of ensuring data quality and protocol compliance should be re- engineered to obtain the benefits of an EDC system. Instead of only viewing the data and protocol results every 4- to- 6 weeks during an on- site monitoring visit, the Monitor or other staff member can review the data in real time as it is entered by the site. As data is reviewed and monitored in real time, errors in data entry by the site can be identified and retraining can be performed to prevent further and often more costly errors. Also, errors in ecrf design can also be detected and changed earlier in the process to prevent erroneous data from being recorded. After in- house data review through the EDC system, the Monitor is better prepared for the on- site monitoring visit by focusing on the unique problems of that site based on ecrf review. The Monitor can verify source documentation and use their time to evaluate the site s study conduct and provide remedial actions for any performance issues. Site performance evaluation can also be completed remotely using the metrics provided by the EDC system. Site metrics within and across sites provide information such as speed of data entry, speed of query correction, number of protocol violations, etc. that document how well the site is conducting the study. These metrics can be used to discuss performance with the site and if necessary, implement a remedial action plan even before the next scheduled on- site monitoring visit.

6 6 of 8 EDC system metrics, such as time to ecrf completion, average time from visit to data entry and number of queries, provide a window into site data issues in real time. Anomalies can then be addressed as they occur instead of waiting 4- to- 6 weeks until the next site visit to discover the issue, which by now, has usually occurred multiple times, and then correct it. 2.4 Cleaning Data The data query process also needs to be reengineered when using EDC systems. Queries can be generated and resolved in several ways, all of which are much faster than paper- based systems. One major advantage is the change in the tracking of generation and resolution of queries. The EDC system keeps track of all queries that are generated through the system, so time and resources are no longer necessary for query tracking. EDC system reports provide instant up- to- date metrics on queries generated, resolved, outstanding and the rate of correction at each site. Query generation and resolution can also be completed remotely by the Clinical group to prevent further similar errors in data entry. The Monitor would then verify the correction by source document review when on site. The Monitor no longer has to spend hours locating the queries, determining if they have been addressed and verifying the ecrf corrections. Once the queries are resolved, the Monitor just needs to source document verify the changes. Through the EDC system, the Clinical staff also has access to any queries generated by Data Management and can monitor the resolution of these queries as well. Data management also leverages the query management capabilities of EDC systems, especially in the generation, issuance, and subsequent resolution of manual queries. By adjusting internal processes, Clinical Data Management groups can optimize the core functionality of EDC systems to fire automatic queries at entry in order to reduce data entry errors. The primary focus of process changes will affect manual queries issued by the Clinical Data Manager. The manual queries include those related to cross- form checks as well as safety queries. The EDC system s flexibility provides additional benefits by creating process efficiencies as it is adapted to company s current organizational structure and business workflows. Since all queries are generated, tracked and resolved in one system, the data cleaning process becomes an integrated process between Clinical Monitors and Data Managers which improves communication between these groups and speeds the process. Current EDC applications also allow for the assignment of permissions based upon company- specific workflows, thereby allowing roles and responsibilities to better align. This ability accelerates the process for both departments as well as the study for faster database lock.

7 7 of 8 3 Summary Overview of Process Changes and Benefits Focus on Clinical Ops and CDM Interactions The use of ecrfs not only speeds the data collection process but also provides many benefits to all team members. 3.1 Investigator Sites Benefits As the concept of remote data entry and subsequent adoption of EDC applications became evident there was push- back from Investigator sites that they would be doing more work; however, there are benefits that the sites gain through the use of EDC applications that they do not have when using paper- based CRF s. The large reductions in the number of queries and better access to the clinical study patient data are two main benefits for the Investigator site. Users of EDC applications have documented reductions up to 90% of queries, which translates into huge time savings for Investigator site personnel. In addition, sites also have access to patient data throughout the course of the clinical study, which provides visibility to the completion of clinical milestones and can lead to faster payments from the sponsoring studies. 3.2 Clinical and Monitor Group Benefits Being able to design the ecrfs to enhance protocol compliance decreases the number and types of protocol violations which results in cleaner data. The ability for the clinical staff to participate in ecrf design and provide only applicable questions, set response range limits, and prevent inaccurate data saves time in correcting inaccurate data. The ability to review the site s data before the on- site monitoring visit provides the Monitor insight into site activities so they can correct any issues in real time instead of being surprised by issues that are brought to their attention when they arrive for the next on- site visit. 3.3 Data Management Benefits Another added benefit to having the Investigator site enter data as compared to having Clinical Data Management groups transcribe and enter data into Clinical Data Management Systems (CDMS) is that the sites are much closer to the data. The time from entry to query generation and resolution is compressed which results in the availability of cleaner data faster so clinical decisions can be made sooner. Additionally, safety data are more readily available, thus increasing awareness of patient safety throughout the course of clinical studies.

8 8 of Statistical Benefits In addition to the data management benefits mentioned above, there are benefits downstream for Biostatistics departments. These benefits include an overall streamlining of the process as Biostatistics are involved at the front- end of the data collection design so they are well aware of the data items to be collected and assist in the definition of the back- end export data structure. This allows the Biostatistical programmers to begin pre- programming and validation for the study tables, listings and figures much earlier in the process, which accelerates the study timeline. Through the active participation of all the functional members of the study team earlier in the study process, especially Biostatisticians, data structures and edit checks are better understood, thus promoting the reliability of data quality amongst the team. 4 Conclusion The use of an EDC system to collect and manage the data during a clinical study is a great advance in the clinical trial industry. However, the processes of paper- based CRFs must be evaluated and reengineered to obtain maximum benefit from the EDC technology. Just applying an EDC technology on top of a paper- based collection process is simply electrifying the paper process. In order to optimize the process, a company must review and understand the current workflow, identify advances in technology and define opportunities where process changes can benefit the overall organization. The introduction of EDC systems require a shift in the roles and responsibilities of the Site Coordinators, Clinical Monitors, Clinical Data Managers, and Safety personnel when compared to the roles and responsibilities defined for personnel when using traditional paper- based data collection systems. The overall goal of integrating trial data processes across functional areas using EDC technology is to streamline the company s processes; however, it is imperative that companies also realize a time savings, a heightened awareness of safety issues as they appear during the course of a clinical study, an increase in the reliability of the clinical data collected and managed and an overall decrease in the cost to achieve the previous items.