Data Quality Assurance. In order to ensure the data quality standards, Pro Public will reasonably meet the five standards of data quality as mentioned in USAID (ADS 203) framework.
Data Quality Assurance. Explain what standards will apply for data quality and how errors will be handled.
Data Quality Assurance. 9.1 The Parties collate data on waste collection and record that information through DEFRA's data recording system known as “Waste Data Flow”. The Parties agree to adopt the Audit Commission’s code of practice on data quality standards as set out in Schedule 6, Part C (The Standards for Better Quality Data, A Voluntary Code of Practice) in order to ensure the accuracy, validity, reliability, timeliness, relevance, completeness and security of information.
Data Quality Assurance. In order to properly analyze the data, it was necessary to examine data quality by comparing the data to projected values. As more data were collected, these data were also compared to previous data sets. If a significant discrepancy was identified, the source of the variation was investigated. Each data element was assessed to ensure the quality of the data collection and transmission. If the monthly data set follows previous trends and does not appear to be a drastic outlier, further confirmation of the data set integrity was performed by reviewing operation and identifying any variances that may have affected the data set. These operational conditions were reviewed with on-site personnel to determine if any variances in operations occurred, such as an accident or significant under-utilization. If a trailer did experience one of the preceding, it was assessed further to determine if the collected data were outliers. If the data were identified as outliers, they were removed from the monthly analysis.
Data Quality Assurance. The project will not only utilize a variety of data collection tools, but in doing so, the project will employ data quality assurance procedures/mechanism to help us decide if the data is valid, attributable, truthful, precise, reliable, and timely.
Data Quality Assurance. ● All participant data relating to the study will be recorded on printed or electronic CRF unless transmitted to the sponsor or designee electronically (e.g. laboratory data). The Investigator (or designee) is responsible for verifying that data entries are accurate and correct by physically or electronically signing the CRF. ● The investigator must maintain accurate documentation (source data). ● The investigator must permit study-related monitoring, audits, IRB review, and regulatory agency inspections and provide direct access to source data. ● Monitoring details describing strategy (e.g. risk-based initiatives in operations and quality such as Risk Management and Mitigation Strategies and Analytical Risk-Based Monitoring), methods, responsibilities and requirements, including handling of noncompliance issues and monitoring techniques (central, remote, or on-site monitoring) are provided in the Monitoring Plan. ● The sponsor or designee is responsible for the data management of this study including quality checking of the data.
Data Quality Assurance. Information shared under this agreement will be adequate to help with the effective discharge of Derbyshire IOM arrangements. It will be relevant and not contain excessive detail which is beyond that required for the agreed purpose. Information discovered to be inaccurate, out-of-date or inadequate for the purpose should be notified to the originating owner of the data who will be responsible for correcting the data and notifying all other recipients of the information who must make sure the correction is made. Partner agencies will ensure that there is an effective management regime to monitor data quality, and that the arrangements for information sharing are fit for purpose.
Data Quality Assurance. Several quality assurance measures were implemented to ensure that data were of high quality. In addition to the training described above, supervisors and E2A/Pathfinder staff monitored the fieldwork to ensure completeness of data and to ensure adherence to assessment guidelines. A data quality consultant also collected data independently in randomly selected facilities. This data was not significantly different from those collected by the research assistants. Field teams also met daily to review their work, discuss problems and challenges, explore ways to improve data-collection activities, and plan for the following day.
Data Quality Assurance. The handling of data, including data quality assurance, will comply with regulatory guidelines (eg, ICH and GCP) and the sponsor’s SOPs and working instructions. Data management and control processes specific to this study will be described in a data management plan. All steps and actions taken regarding data management and quality assurance will be documented in a data handling report. When data management is outsourced, the contract organization will be responsible for the development and implementation of the data management plan and preparation of the data handling report according to the sponsor’s standards. Incoming completed CRFs will be logged into the CRF tracking system and will be reviewed for completeness, the presence of mandatory values, dated signatures, and consistency. All medication and adverse event terms recorded on the CRF will be automatically encoded in the sponsor’s database. All entries rejected by the system will be re-evaluated and corrected as appropriate according to the data on the CRF. All data on the CRF will be entered into a validated database using double data entry. Edit checks will be implemented in the data entry panel to ensure data quality and accuracy. Responses to requests for further clarification of data recorded on the CRF will be answered, dated, and signed by the investigator. Changes will be implemented in the sponsor’s database and the data review and validation procedures will be repeated as needed. All medication and adverse event information and textual comments will be proofread for consistency between the database and the CRF; the database will be corrected appropriately. In the case when data management is outsourced, the contract organization will be responsible for database quality assurance including, but not limited to, all medication and adverse event terms as described above. If eCRFs are used, data management at ImmuPharma or its designee will implement edit checks on the eCRF to enforce data entry guidelines, data consistency, and compliance to the protocol and regulatory requirements. Each study center coordinator will be responsible for entering study data on the eCRFs. Data management will track eCRFs and review them for completeness, the presence of mandatory values, consistency, and dated electronic signatures. In addition to checking for SDV flags, data management will electronically attach data clarification queries directly onto the eCRFs during the review process to ensure data quality...
Data Quality Assurance. All subject data relating to the study will be recorded on printed or electronic CRFs unless transmitted to the Sponsor or designee electronically (eg, laboratory data). The investigator is responsible for verifying that data entries are accurate and correct by physically or electronically signing the CRF. The investigator must maintain attributable, legible, contemporaneous, original, and accurate documentation (source data) that supports the information entered in the CRF. The investigator must permit study-related monitoring, audits, IRB/IEC review, and regulatory agency inspections and provide direct access to source data documents. Details describing monitoring strategy (eg, risk-based initiatives in operations and quality such as risk management and mitigation strategies and analytical risk-based monitoring), methods, responsibilities and requirements, including handling of noncompliance issues and monitoring techniques (central, remote, or on-site monitoring) are provided in the Monitoring Plan. The Sponsor or designee is responsible for the data management of this study including quality review of the data. The Sponsor maintains ultimate responsibility for the quality and integrity of study data, even if study-related duties and functions are transferred to other individuals or organizations (eg, contractors or contract research organizations). Study monitors will perform ongoing source data verification to confirm that data entered into the CRF by authorized site personnel are attributable, legible, contemporaneous, original, and accurate from source documents; that the safety and rights of subjects are being protected; and that the study is being conducted in accordance with the currently approved protocol and any other study agreements, ICH GCP, and applicable regulatory requirements. Records and documents, including signed ICFs, pertaining to the conduct of this study must be retained by the investigator per ICH GCP and local regulations or institutional policies. No records may be destroyed during the retention period without the written approval of the Sponsor. No records may be transferred to another location or party without written notification to the Sponsor.
