With the passage of time, the number of cancer patients has been increasing worldwide. More patients lead to greater data volume and organizations are now in need of powerful management like master data management.
Master data management compiles the golden record of customers and help organizations in chronic diseases like cancer research.
Master data management and clinical research
The success of any research depends on the data generated, gathered, stored and analyzed. It is a team process consisting of customers, manufacturers of drug and medical devices, biologists and organizations. To maintain the quality of data from all domains, master data management is important. Master data management ensures the security and privacy of information and data from patients and other participants.
Researchers who have access to patient data through an master data management can learn more about the effectiveness of anticancer agents, analyze genetic data to find therapeutic targets, and monitor patients more effectively while enhancing quality of life and survival.
Objective of clinical data management
Clinical data management procedure has two main objectives. One is to collect maximum data to analyze and the other objective is to assure the quality of data and integrity of statistical analysis by reducing the errors and chances of missing data. The regulatory requirements compliance by the research organization is also necessary during data management. Clinical data management is three step procedure including collection, cleaning and management of data.
Clinical trial management system
Clinical trial management system is system software helpful in managing the clinical research data. It helps in centralized planning, reporting and keeping the record of all aspects of clinical trial. The master data management in clinical research follows a cycle. Cycle starts with planning stages and after passing through different steps the database is locked. Cycle of clinical master data management involves
- Planning
- Collection of data
- Assurance of data plan with tools
- Identification of risks
- Preservation of already present data
- Integration of different datasets and information
- Statistical analysis of data
- Locking down the database for integrity
Role of master data management in clinical research
Clinical data management is not possible without collaboration of clinical staff. Staff gathers data from patients either on paper or on devices. Next it includes top-line data that makes executive summary of clinical trials. Some other roles clinical data management plays in clinical research are dealing with case report form (CRF), its designing, annotation and tracking. Data processing tasks include data abstraction, archiving, collection, entry and validation, extraction, analysis, storage, privacy, and transmission. Then, master data management deals with database tasks such as it design, building, testing and locking. Further, it works on discrepancy management, medical data coding and processing, patient recorded data, and severe adverse event (SAE) reconciliation. Study metrics and tracking, quality control and assurance of the management system, user acceptance testing and validation checklist are next key roles of a clinical master data management.
Hybrid data management is another expert kind of management of data coming from several sources. It makes the disparate data related to each other and also manageable.
There is an Integrated Cancer Information and Surveillance System (ICISS) that helps population-based cancer research. It helps by establishing a large information technology system linking and managing large data sets.
All in all, the master data management plays an important role in cancer research compliance as it provides an interdisciplinary approach and manages data, systems, and methods that enables researchers to more effectively use data to enhance public health.
About Sasi Kumar
Sasi Kumar Raju Addepalli is a Technical Lead for Master Data Management(MDM) at a leading Cancer Research and Diagnostics Company, He introduced and worked on Industry cutting edge technologies to leverage latest master data techniques to speed up and resolve future problems in Health Care. He Built MDM Implementations from Boot Strap. He is well known for his expertise in the MDM Industry especially in Health Care and his skills are being very helpful for Fortune 500 companies.
