A wide variety of data is generated by clinical studies require careful collation and review. Conventionally, the collection of this data is customized and done in the (CRF) Case Report Form to specifically perform a clinical study. With digitalization, electronic CRFs have replaced paper CRFs. Therefore, instead of entering the data on the paper, it is entered using computers to the dedicated and customized Electronic Data Capture system. This interface is an integral part of DCTs. The data referred to here is the information gathered from the participants during the trial course. In contrast to conventional trials, where the collection of data takes place at physical sites of study, DCTs employ technologies digitally to collect data remotely. DCTs promote flexibility, ease, and monitoring in real-time. DCTs ensure that the data collected is of good quality and maintains the integrity for the triumph and consistency of the outcomes of the study.
The vital data components in DCTs includes data generated from patients containing of (PROs) Patient-Reported Outcomes and data from wearable devices, (EHRs) Electronic Health Records comprising of the history of the health and medical accounts, results from remote lab tests, data gathered during a participant and a healthcare professional’s virtual meet, digital data of imaging, adherence to medication and data on compliance, demographic data, baseline data, primary and secondary objectives of the study’s data, safety and adverse events data, and data on informed consent.
Evaluating the DCTs data quality implies the evaluation of different perspectives for ensuring dependability, precision, and integrity. Here are some key considerations:
- Data Accuracy:
- Source Data Verification (SDV): Ensure that data collected remotely aligns with source documents, such as electronic health records or patient diaries.
- Real-time Data Monitoring: Implement real-time monitoring tools to identify and address data discrepancies promptly.
- Engagement of Patients:
- Training of Patients and Support: It should be assured that adequate training is provided to patients for using any devices or technology used for the collection of data.
- Compliance of Patients: Issues should be monitored and addressed with respect to compliance of patients with protocols pertaining to collection of data.
- Security of Data and Privacy:
- Reliable Transmission of Data: Employment of safe channels for data transmission for maintaining privacy.
- Accordance with Regulations: Regulations pertaining to the protection of data must be taken into account, such as USA’s (HIPAA) (Health Insurance Portability and Accountability Act) or EU’s (GDPR) (General Data Protection Regulation).
- Technology Reliability:
- Validation of System: Validation of the devices and digital platforms need to be carried out whether they are reliable and functioning properly for the collection of data.
- Encryption of Data: Implementation of protocols of encryption for data protection during storage and transmission.
- Compliance with Regulations:
- Regulatory Configuration: It should be ensured that the processes of DCT observe standards and guidelines of regulatory norms.
- Trails of Audit: Maintaining detailed trails of audit for tracking any data changes or alterations.
- Monitoring of Data and Controlling:
- Monitoring in a Centralized way: To supervise the quality of data across numerous sites, a central system of monitoring should be established.
- Protocols for Cleaning of Data: Development and implementation of protocols for the identification and addressing of errors in data or contradictions.
- Site and Investigator Training:
- Training Programs: Provide training for investigators and site staff on the use of technology and adherence to data collection protocols.
- Site Audits: Conduct periodic site audits to assess data collection practices and address any issues.
- Adherence to Protocols:
- Protocol Compliance Checks: Regularly assess whether the decentralized trial is adhering to the study protocol.
- Protocol Amendments: Implement procedures for managing and documenting protocol amendments.
- Data Validation and Quality Control:
- Data Validation Checks: Implement automated checks for data validation to identify outliers or errors.
- Quality Control Processes: Establish robust quality control processes to ensure data accuracy and completeness.
- (PROs) Patient-reported Outcomes:
- Studies on Validation: The outcomes reported by patients must be validated to ensure trustworthiness and legitimacy.
- Training of Patients: Providing transparent training and backing to patients remotely reporting results.
Assessment of the data quality in DCTs needs an approach holistic in nature which counts on technology, engagement of patients, compliance with regulations, and practices of managing data. Monitoring regularly, training, and process of validation promotes maintenance of quality of data throughout the entire process of the trial. It requires technical compatibility between various digital interfaces as well as gadgets, wearables and various software programs are integrated in the clinical study program. It requires reasonable computer literacy and familiarity to use gadgets/ wearables for the end users and those involved in the data entry at various levels.
