To find answers to the question in clinical trials is done by means of the data generated for proving or counter acting a hypothesis. The data generated is of persistent quality that plays a significant role in the outcome of the respective study. Many research students often question, “What is Clinical Data Management & its Significance?” It can be defined as an important part of a trial conducted as all researchers work on CDM activities during their trial work, be it knowingly or unknowingly. Unaware of the technical phases, researchers are involved in CDM activities. The article focuses on the processes involved in Clinical Data Management (CDM) and grants the new readers an outline of how the data is managed & reviewed in clinical trials.
Clinical Data Management is a cycle of collecting, cleaning & managing data that must be in compliance with regulatory standards. The primary aspect of CDM processes are to provide high quality data that is by reducing or minimizing the number of errors and missing data must be as low as possible and gather maximum data for further analysis. In order to achieve this aspect in CDM, the best practices are adopted so that the necessary data are complete, updated, processed & most of all reliable in nature. This thus facilitates the use of softwares that helps in maintaining the audit trial and provides for easy resolution & identification of data discrepancies. Innovations that are sophisticated in nature have enabled CDM to be able to manage and conduct large trials and this ensures the quality even in complex trials.
Handy Tools for Clinical Data Management:
There are several software tools that are made available for data management, and these are called Clinical Data Management Systems (CDMS). In several trials also called as multicentric trails, a CDMS has now become essential to manage large quantities of data. Most pharmaceutical companies use CDMS that are only commercial, however, a few tools are open sourced and are widely available as well. The most commonly used CDM tools are ORACLE CLINICAL, MACRO, RAVE, CLINTRIAL and eClinical Suite. These software tools are more or less similar in function and there is not much significance of one system over the other system.
Clinical Data Management Process:
Unlike a clinical trial, the CDM process begins much in the end of the trial. This definitely means that the whole process is designed keeping point in view the delivery. As a clinical trial is designed to answer the research question, the CDM process is designed in a way that it must deliver data that is error free and valid and must be statistically sound in database. However, to achieve this objective, the CDM process starts a little earlier than expected even before the entire study protocol is finalized.
Finalization & Review of Study Documents:
The study protocol is mostly reviewed from a database that is designed in a perspective for consistency & clarity. In due course of review, the CDM personnel must identify the items that must be collected and the frequency of collection with respect to the visit schedule. A Case Report Form (CRF) that is first designed by the CDM team as it is the first step in translation of protocol activities that are generated. These fields of data must be clearly defined and must stay consistent throughout.
Designing of Database:
Clinical Trial Software applications are Databases, which are built to facilitate the CDM tasks that must perform several studies. In general, these tools are in compliance with the regulatory requirements and are most easy to use. “System Validation” is to ensure system specifications, data security and most user requirements that must be in regulatory compliance that must be evaluated before implementation. Details of the study such as objectives, investigators, sites & patients are mostly defined in the database and Case Report Form layouts are designed for the basic purpose of data entry. These entry level screens are tried and tested with fake data before the transfer to the real data capture.
Most Case Report Forms are a part of Data Collection that either exists in paper or electronic version. The most conventional method is paper CRF’s to aid in data responses that are further translated to the database by the method of data entry done in-house. These papers CRF’s are written by principal investigators in accordance to the guidelines for completion.
Most CRF entries must be monitored by the Clinical Research Associate (CRA) for a complete study & review. These CRF’s are further retrieved and submitted to the CDM team. The CDM team will further track down the retrieved CRF’s & maintain their records for further use.
Entry of Data occurs only in accordance to the guidelines that must be prepared along with the DMP. However, it is applicable only in paper CRF’s that are retrieved from the sites. Otherwise, double entry of the data may occur in order to avoid this, the data is entered separately by two operators.
Validation of Data
Data Validation is a process of testing the data that must be in accordance with the specifications of protocol. Programs edit check is mostly written to identify discrepancies in the entered data, which are fed into the database to ensure validation of data. These programs are written in accordance to the logic condition that was mentioned in DVP. These programs edit check are primarily tested with dummy data that contain many discrepancies. Discrepancy maybe defined as a point of data that fails to go through any validation check.
It is also called as query resolution. This involves reviewing most discrepancies, to investigate many reasons and to resolve them with proof that is documented or declaring them as irresolvable. Discrepancy management aids to clean the data and collects sufficient evidence for deviations that were observed in the data. Nearly all CDMS have a discrepancy in database where all discrepancies must be recorded & stored with audit trials.
This Medical Coding helps to identify & classify all the medical terminologies that are in association with the clinical trials. In order to classify events, medical dictionaries are available online and are used thoroughly. However, the activity requires knowledge of medical terms and deeper understanding of diseases and the drugs used for it, a sound knowledge of several pathological processes are also involved. Medical Coding also requires knowledge of the structure of e-medical dictionaries and the classification hierarchy that are available to them.
After a thorough check on quality and assurance, the final optimal data validation is runs. If there are not many discrepancies, the SAS databases are finalized along with the statistician. Complete data management activities must be completed earlier to database lock.
Roles & Responsibilities in Clinical Data Management
In a team of CDM professionals, there are many roles & responsibilities that are attributed to the many members of the team. The basic educational qualification requirement for a team member in CDM must be a graduate in Life Science & knowledge of computer applications. In the current scenario of the industry, a number of paramedical graduates are also recruited as medical coders. A few key roles are essential in all CDM teams. The roles are mentioned below and must be considered as a basic requirement for a CDM team.
- Data Manager
- Database Programmer/Designer
- Medical Coder
- Clinical Data Coordinator
- Quality Control Associate
- Data Entry Associate
A Data Manager is mostly responsible for supervision of the entire CDM process. The responsibilities of a data manager are to prepare DMP, approving the CDM procedures and all documents that are related CDM activities. To control & allocate the database to the team members is also responsibility of the data manager. The designer or database programmer performs case report forms annotations, creates a database for the study, and performs validation of data using program edit checks. He or she is mostly responsible for the design of data entry screens in its database and validation of edit checks with fake data.