Database Designing in CDM
Introduction
What is Clinical Data Management?
Clinical data management (CDM) is the process of collecting and managing research data by regulatory standards to obtain complete and error-free quality information. The goal is to collect as much data as possible for analysis while adhering to federal, state, and local regulations
Why is Clinical Data Management needed?
Clinical data management (CDM) is a field that was created in response to regulatory agencies and the pharmaceutical industry's requirements. Regulatory bodies have reacted to the ongoing urge to "fast-track" the development of pharmaceutical goods by insisting that quality-assurance requirements be met when gathering the data required in the drug evaluation process. Furthermore, the CDM procedure aids in keeping important clinical trial stakeholders on the same page:
Sponsors - pharmaceutical companies, and institutions that start, monitor, and finance the trial.
CROs (Contract Research Organizations) are organizations that are hired by sponsors to execute the trials.
Sites – Centres for data collection from trial subjects.
The evaluation of the safety and efficacy of medications, diets, medical equipment, digital therapy tools, and other forms of treatment, diagnostics, or measures to prevent health issues is greatly aided by CDM.
The clinical Traditional vs Modern Approach in CDM
Clinical data management team and stages:
CDM activities begin early in the clinical trial process, when the trial protocol is developed, detailing the research objectives and methods. Data-related duties are typically distributed among departments.
Personnel involved in the CDM process:
A clinical data manager who supervises the entire CDM process
A database programmer or designer
Data entry associates
A medical coder who translates diagnosis, procedures, adverse events, and other health data into industry specific code
A quality control associate.
Let's explore the development of data management now and what each step involves,
Figure 1 Data flow in Clinical Trials and Clinical Data Management Stages
Every method, task, milestone, and deliverable throughout the CDM lifecycle is listed in a document called a data management plan or DMP.
Stage | Overall process | Additional information |
DMP design | Throughout the CDM lifecycle, every method, task, milestone, and deliverable is listed in a document called a data management plan, or DMP. | Experts in charge: data manager, database designer Data to be gathered from trial participants, existing data that can be integrated, data formats, metadata and its standards, storage and backup methods, security measures to protect confidential information, data quality procedures, responsibility assignments across team members, access and sharing mechanisms and limitations, long-time archiving and preservation procedures, the cost of data preparation and archiving, and compliance with relevant regulations and requirements
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CRF design | Case report forms are printed or electronic questionnaires used to collect data from study participants and report it to trial sponsors. | Experts in charge: data manager, database designer Case report forms that are well-designed capture only the data required for the specific research, eliminating repetition The fields that must be completed may include,
Demographics (age, gender), Demographics (age, gender) Basic measurements (height, weight), Vital signs (blood pressure, temperature, etc.) captured at various time points Lab exams Medical history Adverse events
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Database design | A clinical trial database is a collection of data structured in rows and columns that was acquired throughout the investigation. It is intended for use with the CRF framework. To put it another way, the database includes a questionnaire structure for the case report forms. | Experts in charge: data manager, database designer
Databases are clinical software systems designed to make it easier for CDM to conduct out various investigations. In general, these technologies are straightforward to use and feature built-in compliance with regulatory standards. To guarantee data security, "system validation" is performed, during which system specifications, user needs, and regulatory compliance are checked before implementation. The database defines study details such as objectives, intervals, visits, investigators, sites, and patients, and CRF layouts are built for data entry. Before going on to the real data gathering, these entry screens are checked using dummy data. |
Data capture | As previously stated, CRFs are the primary data collection tool in clinical studies. Traditionally, physicians or data entry associates collect information for report forms from participants when they visit medical institutions. However, in recent years, medical locations have ceased to be the principal source of data collection. | Experts in charge: clinicians, data managers, data entry associate, medical coder.
Details for trials are also extracted from: Electronic Health Records (EHRs) Medical devices (blood pressure monitors, ECG recording machines, and others), Laboratory information management system (LIMS), and Patient-reported outcomes (PROs) or any descriptions of health conditions that come directly from patients, without mediation and interpretation from medical experts.
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Data Validation | edit checks, source data verification, and data anonymization.
| Experts in charge: data manager, database designer, quality control associate.
A database designer creates edit checks, which are then incorporated in eCRFs to automatically verify inputs against numerical and logical criteria. This prevents values that are unlikely to occur in the document from displaying. Source data validation (SDV). SDV refers to the process of cross-referencing CRF information with actual medical records and other source files.
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Database lock | When the research is over, the database is locked so that no modifications to the information may be made. Following that, clean data is sent to stakeholders for statistical analysis, reporting, and, eventually, outcomes publishing. | Experts in charge: data manager, database designer
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Conclusion:
CDM has grown in response to the growing need from pharmaceutical firms to accelerate the drug development process and from regulatory bodies to put in place quality mechanisms to assure the creation of high-quality data for accurate drug evaluation. To match expectations, there is a progressive movement from paper-based to electronic data management systems. Technological advancements have had a favorable influence on the CDM process and systems, resulting in encouraging data generation speed and quality outcomes. Simultaneously, CDM specialists must maintain the criteria for enhancing data quality, as a specialty, and should be evaluated by the systems and procedures in place, as well as the standards that are followed. The most difficult regulatory problem would be the standardization of data management processes across businesses, as well as the establishment of legislation to define the procedures to be followed and data standards. The most difficult challenge for the industry would be the planning and execution of data management systems in a changing operating environment where the quick speed of technological progress outdates the current infrastructure. Despite these challenges, CDM is growing to become a standard-based clinical research institution by establishing a balance between the expectations of and limits in existing systems due to technology advancements and commercial needs.
References:
1. https://pubmed.ncbi.nlm.nih.gov/8130557/
2. https://www.dovepress.com/clinical-data-management-current-status-challenges-and-future-directio-peer-reviewed-fulltext-article-OAJCT
Student Name: Abdulkadar Shakil Hakim
Student ID: 008/012023
Qualification: B. Pharmacy
e-Mail ID: adil.rc119@gmail.com
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