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Real-World Evidence Generation
Published in Kelly H. Zou, Lobna A. Salem, Amrit Ray, Real-World Evidence in a Patient-Centric Digital Era, 2023
Joseph S. Imperato, Joseph P. Cook, Diana Morgenstern, Kim Gilchrist, Tarek A. Hassan, Jorge Saenz, Danute Ducinskiene
For an evaluation of patient populations, it would be difficult to develop a research cohort designed prospectively utilizing the target population, condition, and intervention to understand the resultant health outcomes. Observational research has bridged this dilemma with new research datasets which link transactional information, disease classification, co-morbidities, interventions, and therapeutics to understand health outcomes. Electronic data capture of the patient journey has expedited and further clarified the patient journey in a longitudinal framework by linking data sets with individual patient records across healthcare entities (laboratory, pharmacy, specialist, diagnostic, etc.).
Real-World Data and Real-World Evidence
Published in Wei Zhang, Fangrong Yan, Feng Chen, Shein-Chung Chow, Advanced Statistics in Regulatory Critical Clinical Initiatives, 2022
Are two main steps of registry construction. Patient management process involves (i) identification of the target population, distribution of patients, and inclusion and exclusion criteria; (ii) recruitment of patients (e.g., telephone follow-up, online follow-up visits) and control of bias; (iii) follow-up plans and compliance maintenance. Data collection process should comprehensively consider: (i) design of the registry Case Report Form (CRF) and Data Management Plan (DMP); (ii) design of the Electronic Data Capture (EDC) system; (iii) selection of data sources; (iv) methods for data extraction and entry; (v) quality assessment and data standardization55 (e.g., Clinical Data Interchange Standards Consortium); (vi) data storage and submission.
In Vitro Alternative Methods for the Assessment of Dermal Irritation and Inflammation
Published in David W. Hobson, Dermal and Ocular Toxicology, 2020
David W. Hobson, James A. Blank
The neutral red method is relatively sensitive as it can detect as few as 1000 cells and provides a linear relationship between cell number and neutral red content up to 40,000 3T3 fibroblast cells.35 This method does not require the use of radioactive material and is also fast, inexpensive, and can be easily automated. Data can be electronically captured by interfacing the microtiter plate spectrophotometer to a computer. In addition to making the assay quicker, electronic data capture simplifies data analyses and enhances quality control. This assay would be difficult to use with nonadherent cell types as it requires a wash step.
Satisfaction with opioid prescription and use after minor gynaecologic surgery: a pilot prospective study
Published in Journal of Obstetrics and Gynaecology, 2023
Chailee Moss, Carolyn Brookhart, Prerna Pandya, Mostafa A. Borahay, Melindia Mann, Victoria Handa, Anna Maya Powell
Chart abstraction was performed to confirm the performed procedure, anaesthesia time and type, operative difficulties and opioid prescription. Patients were surveyed preoperatively (within 1 week prior to surgery), on postoperative day (POD) 1 or 2 and finally at POD 14. Survey instruments were emailed to patients through Research Electronic Data Capture (REDCap) at Johns Hopkins University School of Medicine (Harris et al.2009) and follow up phone calls were made by study personnel up to three times to assist with survey completion. Research Electronic Data Capture is a secure, web-based application designed to support data capture for research studies, providing: (1) an intuitive interface for validated data entry; (2) audit trails for tracking data manipulation and export procedures; (3) automated export procedures for seamless data downloads to common statistical packages; and (4) procedures for importing data from external sources.
The Texas Immuno-Oncology Biorepository, a statewide biospecimen collection and clinical informatics system to enable longitudinal tumor and immune profiling
Published in Baylor University Medical Center Proceedings, 2023
Ronan J. Kelly, Timothy G. Whitsett, G. Jackson Snipes, Sheila M. Dobin, Jennifer Finholt, Natalie Settele, Elisa L. Priest, Kenneth Youens, Lucy B. Wallace, Gary Schwartz, Lucas Wong, Sherronda M. Henderson, Alan C. Gowan, Ekokobe Fonkem, Maria I. Juarez, Christal E. Murray, Jeffrey Wu, Kendall Van Keuren-Jensen, Patrick Pirrotte, Sarah Highlander, Tania Contente, Angela Baker, Jose Victorino, Michael E. Berens
A data management plan documents data handling processes and data quality assurance for clinical data needed to annotate the samples. Clinical data quality is maintained by multiple levels of data quality assurance. First, electronic data capture forms are designed with data quality and end users in mind. Where possible, data validation checks are built in to minimize data entry errors. Next, data is abstracted from the electronic health record by individuals who have undergone training and passed a data abstraction test. Thorough documentation on methods of abstraction has been created for every data field. After data entry, designated data leads review critical data fields for accuracy. Additional data review occurs regularly on a percentage of entered forms to check for errors. Data is extracted from the REDCap system and additional data quality checks are performed. These data quality checks will continue to evolve to ensure that the data meets quality standards.
Safety and effectiveness of ramucirumab and docetaxel: a single-arm, prospective, multicenter, non-interventional, observational, post-marketing safety study of NSCLC in Japan
Published in Expert Opinion on Drug Safety, 2022
Yucherng Chen, Soshi Nagaoka, Taeko Katayose, Nobuyuki Sekine
Patient data was reported by investigators via an electronic data capture (EDC) system. Data collected through the EDC included baseline and clinical characteristics, prior treatment, use of ramucirumab, concomitant therapies, safety, and effectiveness. Safety was evaluated by the frequency, grade, and seriousness of adverse events (AEs). An AE was defined as any unfavorable or unintended disease or sign (including an abnormal laboratory test value) in a patient administered ramucirumab, with or without a causal relationship to ramucirumab. Adverse events of special interest (AESI) included arterial thromboembolism, venous thromboembolism, infusion reaction, gastrointestinal perforation, hemorrhage (especially pulmonary hemorrhage), cardiac failure congestive, impaired wound healing, fistula, posterior reversible encephalopathy syndrome, hypertension, proteinuria/nephrotic syndrome, liver disorder/hepatic failure, febrile neutropenia, and interstitial lung disease. AEs, serious adverse events (SAEs), and AESIs were classified using the Medical Dictionary for Regulatory Activities version 22.1 preferred terms and graded were based on the National Cancer Institute Common Terminology Criteria for Adverse Events (CTCAE) Version 4.02.