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Objective:To provide a reference for the choice of electronic data capture system used in clinical research, the function and performance of some tool software were expounded and compared.Methods:We selected three freely available systems of REDCap, Commcare, and OpenEDC as research objects, describing and comparing their user license acquisition path, data capture related functions, and information security assurance measures. This article reflected how the three kinds of tool software ensure research data privacy and scientificity, and presented the consideration of system security and accessibility.Results:REDCap was the most mature system of the three, which had a fairly comprehensive design in functional integrity, data security, user friendliness, and system scalability. Commcare system featured in the mobile collection, and supported the most abundant types of collected data, while OpenEDC was characteristic of low threshold and flexible deployment.Conclusions:REDCap system is widely applicable to small and medium scale medical research, including clinical trials, retrospective studies, cohort studies, and translational research. Commcare system is the preferred option for medical investigations represented by epidemiologic surveys, while OpenEDC is particularly suitable for investigator initiated studies.
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Objective: To introduce how to build a data platform of data collection and data management for multi-center birth cohort study by using REDCap. Methods: After the REDCap electronic data capture system was installed and set up, the electronic case report forms (eCRFs) were programmed to collect data in multi-centers. The rules of data quality control were programmed, and different levels of user right for access to data platform were assigned to the data managers and data clerks based on their role in research project. Results: With REDCap system being installed, the example project was created, and a series of eCRFs were established for each stage of preconception, pregnancy and childhood through follow-up. After intensive testing to improve and achieve a stable data platform, standardized trainings were provided to data-related team. The REDCap eCRFs were then put in use online. By assigning different user right of access to data platform, data entry can be from multi- research centers and survey sites. This REDCap data platform supported the cohort project on data collection and data management. Conclusion: The data platform established by using REDCap provides strong support to birth cohorts on data collection and data management. This example project of data platform can be applied to other epidemiological studies.
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Background:Patient-reported outcomesplay an essential role in evaluating the results of clinical trials. As technological advances are made throughout the industry, pharmaceutical sponsors’ ability to collect field-based patient data has greatly increased. Recently, many clinical trials areutilizing varying modes of data capture in order to enable maximum flexibility. Given the regulatory concern over the equivalence of mixed modes of administration, the need to research the use of varying devices is essential.Methods:This study reviewedthree handheld smartphone devices for conceptual equivalence and conducted usability for standard questions used in a daily pain diary. Out of ten participants, 7 were females and 3 were males with age ranging from27-70 years, diagnosed with chronic painor fibromyalgia, completed the same pain diary on three different smartphone devices.Results:Overall, participants reported no differences between these three smartphone devices and found the presentation of the diary content to be similar, if not identical, on all three devices. Conclusions: Device type had no impact on the presentation of the diary content or participants’ understanding of the diary questions
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With the technology development in Internet of Things (IoT) area, it is good to try to use IoT and cloud computing technologies to improve the efficiency of medical equipment management. This article described using CT as sample to do the data capture and data analysis with the IoT technology. The positive result got shows the benefit of the exploring.
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Cloud Computing , Internet , Surgical EquipmentABSTRACT
Electronic data capture(EDC) plays an important role in improving the quality of clinical research.The authors introduced the main functions of EDC and the use flow, then from its core function, analyzed the role of EDC in improving the quality of clinical research and scientific research management. Then they proposed the thinking of finding and solving problems from EDC " big data".Their efforts aim at enabling research administrators in extending clinical research management scope and management quality.
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Data acquisition is one of the key links that influencing the quality of clinical research.Electronic data capture system (EDC) embodies the advantages of saving time,manpower and material resources and improving efficiency and reliability by data acquisition.CDISC has established worldwide industry standards to support the electronic acquisition,exchange,submission and archiving of clinical research data.The application of CDISC standards to EDC system is favorable in ensuring the validity and standardization of clinical data.This paper takes the Oracle's OC/ RDC (Oracle Clinical / Oracle Remote Data Capture) system as an example to discuss the application of CDISC standard to EDC system from the two aspects:direct application and indirect application.We suggest that data collection should be taken into account during the design phase of a clinical trial,and the CDISC standard be applied at the CRF design stage.A design for eCRF takes time and effort by the combination of EDC system and CDISC standard,while thoughtless design may collect the wrong data.Therefore,it is suggested that a specialized personnel should be put in charge of eCRF design and maintenance during the operation of EDC system,and a set of standardized eCRFs based on CDISC standard and standard operating procedures should be built in one organization.
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We designed and applied the electronic data capture system (EDC) in order to strengthen the re-search quality and improve the efficiency of data collection of multi-center nursing research. According to the needs of research,we reasonably designed the EDC structure and functions,including data collection,verification, summary and export. Further improvement was performed after EDC was inputted into using. By using EDC,resear-chers from sub-centers completed the data collection smoothly,and the data quality met with research requirements. The design and application of EDC could effectively guarantee the data quality and improve the research efficiency.
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OBJECTIVE:To ensure the stability of electronic data capture(EDC)system in drug clinical trials and to improve the quality of drug clinical trials. METHODS:The quality control system for EDC system was established and introduced from the formulation of quality control process,establishment of data standard,trial project management,daily management,trial project design,system operation,system function,etc. RESULTS & CONCLUSIONS:Data standard have been achieved through estab-lishing EDC quality control system by our hospital based on attributable,legible,contemporaneous,original and accurate principle. The management of trial project and daily management are conducted through data registration,staff training,the formulation of da-ta management plan,fault emergency treatment,database backup;multiple verification of support data,data lock and export,trial report autogeneration and other functions have been realized by formulating related standard operation instruction,program file,op-eration manual and quality record. Those aspects improve facticity,accuracy and integrality of data in clinical trials,and lay a foun-dation for further data mining.
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Objective To establish a method for data quality control of clinical research data based on electronic data capture (EDC) system.Methods After analyzed the specific characteristics of EDC's workflow process,and also referred to international data management guideline,we established the data quality control strategy by summarizing actual data quality control experience of data management department in Peking University Clinical Research Institute.Results Application of EDC has changed traditional clinical research process,therefore EDC data quality control strategy should be built according to its own process flow,namely,selecting the appropriate EDC system,reasonable design and build electronic case report form (eCRF),standardization research center / user management processes,timely and accurate on line eCRF filling up,accurately capturing/docking ex ternal electronic data,planned data monitor and auditing,timely and efficient query management,strictly data locking and unlocking operation process,and strict electronic record life cycle monitoring.Conclusions At present time,clinical research in China is still in the earlier stage of the transition from traditional paper-based data collection (PDC) to EDC.Establishing and applying particular quality control strategy will optimize the process and results of data quality control.
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OBJECTIVE: Personal Digital Assistants (PDAs) have the potential to improve clinical trial data collection; however, most current PDA-based clinical data collection systems typically collect and store data in the offline mode, and then transfer the data to an operational database. The purpose of this study was to explore the usefulness of a wireless clinical data collection system for an irritable bowel syndrome trial compared with the traditional paper based data collection. METHODS: We have developed a PDA-based data capture system for clinical trials, and tested it in a double-blind trial. Sixty four patients with irritable bowel syndrome were randomly selected and divided into a control group that used the standard paper report forms (CRF) and an intervention group that used the electronic report forms (e-CRF), daily for five weeks. There were 630 data sets consisting of six questions each, and thus 3,570 data points total were collected. RESULTS: The response rate of the control group was significantly higher than that of the intervention group. However, the completeness of the response in the intervention group was higher and the number of input errors per person for the PDA group was lower than in the paper group. CONCLUSION: A PDA based electronic diary improved the response rate and decreased input errors in an IBS trial. We conclude that mobile devices can be very useful, especially when the proposed design and connectivity aspects have been taken into account.