Additionally, some multinational pharmaceutical giants use custom-made CDMS tools to suit their operational needs and procedures. These software tools are expensive and need sophisticated Information Technology infrastructure to function. In terms of functionality, these software tools are more or less similar and there is no significant advantage of one system over the other. Commonly used CDM tools are ORACLE CLINICAL, CLINTRIAL, MACRO, RAVE, and eClinical Suite. Most of the CDMS used in pharmaceutical companies are commercial, but a few open source tools are available as well. In multicentric trials, a CDMS has become essential to handle the huge amount of data. Many software tools are available for data management, and these are called Clinical Data Management Systems (CDMS). The data should also meet the applicable regulatory requirements specified for data quality. But most importantly, high-quality data should possess only an arbitrarily ‘acceptable level of variation’ that would not affect the conclusion of the study on statistical analysis. High-quality data should have minimal or no misses. Similarly, missing data is also a matter of concern for clinical researchers. It should be borne in mind that in some situations, regulatory authorities may be interested in looking at such data. This implies that in case of a deviation, not meeting the protocol-specifications, we may think of excluding the patient from the final database. These should meet the protocol-specified parameters and comply with the protocol requirements. How do we define ‘high-quality’ data? High-quality data should be absolutely accurate and suitable for statistical analysis. Sophisticated innovations have enabled CDM to handle large trials and ensure the data quality even in complex trials. This has been facilitated by the use of software applications that maintain an audit trail and provide easy identification and resolution of data discrepancies. To meet this objective, best practices are adopted to ensure that data are complete, reliable, and processed correctly. The primary objective of CDM processes is to provide high-quality data by keeping the number of errors and missing data as low as possible and gather maximum data for analysis. This article highlights the processes involved in CDM and gives the reader an overview of how data is managed in clinical trials.ĬDM is the process of collection, cleaning, and management of subject data in compliance with regulatory standards. Without identifying the technical phases, we undertake some of the processes involved in CDM during our research work. All researchers try their hands on CDM activities during their research work, knowingly or unknowingly. Often research students ask the question, “what is Clinical Data Management (CDM) and what is its significance?” Clinical data management is a relevant and important part of a clinical trial. The quality of data generated plays an important role in the outcome of the study. This article highlights the processes involved and provides the reader an overview of the tools and standards adopted as well as the roles and responsibilities in CDM.Ĭlinical trial is intended to find answers to the research question by means of generating data for proving or disproving a hypothesis. CDM professionals should meet appropriate expectations and set standards for data quality and also have a drive to adapt to the rapidly changing technology. Additionally, it is becoming mandatory for companies to submit the data electronically. With the implementation of regulatory compliant data management tools, CDM team can meet these demands. In the present scenario, there is an increased demand to improve the CDM standards to meet the regulatory requirements and stay ahead of the competition by means of faster commercialization of product. Various procedures in CDM including Case Report Form (CRF) designing, CRF annotation, database designing, data-entry, data validation, discrepancy management, medical coding, data extraction, and database locking are assessed for quality at regular intervals during a trial. They should have adequate process knowledge that helps maintain the quality standards of CDM processes. Team members of CDM are actively involved in all stages of clinical trial right from inception to completion. This helps to produce a drastic reduction in time from drug development to marketing. Clinical Data Management (CDM) is a critical phase in clinical research, which leads to generation of high-quality, reliable, and statistically sound data from clinical trials.
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