Electronic data collection in epidemiological research. The use of REDCap in the Pelotas birth cohorts.
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ABSTRACT:
SUBMITTER: Blumenberg C
PROVIDER: S-EPMC5052541 | biostudies-other | 2016 Jul
REPOSITORIES: biostudies-other
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Project description:BackgroundMany pregnancy and birth cohort studies investigate the health effects of early-life environmental contaminant exposure. An overview of existing studies and their data is needed to improve collaboration, harmonization, and future project planning.ObjectivesOur goal was to create a comprehensive overview of European birth cohorts with environmental exposure data.MethodsBirth cohort studies were included if they a) collected data on at least one environmental exposure, b) started enrollment during pregnancy or at birth, c) included at least one follow-up point after birth, d) included at least 200 mother-child pairs, and e) were based in a European country. A questionnaire collected information on basic protocol details and exposure and health outcome assessments, including specific contaminants, methods and samples, timing, and number of subjects. A full inventory can be searched on www.birthcohortsenrieco.net.ResultsQuestionnaires were completed by 37 cohort studies of > 350,000 mother-child pairs in 19 European countries. Only three cohorts did not participate. All cohorts collected biological specimens of children or parents. Many cohorts collected information on passive smoking (n = 36), maternal occupation (n = 33), outdoor air pollution (n = 27), and allergens/biological organisms (n = 27). Fewer cohorts (n = 12-19) collected information on water contamination, ionizing or nonionizing radiation exposures, noise, metals, persistent organic pollutants, or other pollutants. All cohorts have information on birth outcomes; nearly all on asthma, allergies, childhood growth and obesity; and 26 collected information on child neurodevelopment.ConclusionCombining forces in this field will yield more efficient and conclusive studies and ultimately improve causal inference. This impressive resource of existing birth cohort data could form the basis for longer-term and worldwide coordination of research on environment and child health.
| S-EPMC3261945 | biostudies-literature
Project description:Background/aimsCoronavirus Disease 2019 (COVID-19) has presented an unprecedented challenge for delivering clinical research. The use of technology-assisted data collection for clinical research is desirable for many practitioners, but the acceptability of use in the general population has not been assessed. The aim of the study was to assess attitudes towards using technology-assisted remote methods in the delivery of clinical research in the UK and to understand the barriers to taking part in research with respect to both remote assessments and traditional research methods across different age ranges.MethodsThe study was conducted as an online anonymous survey with a 4-part questionnaire, between August 2020 and December 2020. Participants living in the UK aged 18 years and above were eligible to take part.ResultsA total 351 completed the survey and are included in the data analysis. In all age groups, participants identified that use of online assignments, video calls and telephone calls would make them more likely to take part in clinical research. Overall, the largest barrier to taking part in research was time commitments and timing of the appointment. COVID-19 has had a small, positive influence on the confidence of using technology in the general population.ConclusionsThe study found that there is a large interest in taking part in research using online, telephone and video call appointments, which could facilitate research delivery in light of ongoing COVID-19-related restrictions and also improve the accessibility and inclusivity of research.
| S-EPMC8511885 | biostudies-literature
Project description:BackgroundObservation of care at birth is challenging with multiple, rapid and potentially concurrent events occurring for mother, newborn and placenta. Design of electronic data (E-data) collection needs to account for these challenges. The Every Newborn Birth Indicators Research Tracking in Hospitals (EN-BIRTH) was an observational study to assess measurement of indicators for priority maternal and newborn interventions and took place in five hospitals in Bangladesh, Nepal and Tanzania (July 2017-July 2018). E-data tools were required to capture individually-linked, timed observation of care, data extraction from hospital register-records or case-notes, and exit-survey data from women.MethodsTo evaluate this process for EN-BIRTH, we employed a framework organised around five steps for E-data design, data collection and implementation. Using this framework, a mixed methods evaluation synthesised evidence from study documentation, standard operating procedures, stakeholder meetings and design workshops. We undertook focus group discussions with EN-BIRTH researchers to explore experiences from the three different country teams (November-December 2019). Results were organised according to the five a priori steps.ResultsIn accordance with the five-step framework, we found: 1) Selection of data collection approach and software: user-centred design principles were applied to meet the challenges for observation of rapid, concurrent events around the time of birth with time-stamping. 2) Design of data collection tools and programming: required extensive pilot testing of tools to be user-focused and to include in-built error messages and data quality alerts. 3) Recruitment and training of data collectors: standardised with an interactive training package including pre/post-course assessment. 4) Data collection, quality assurance, and management: real-time quality assessments with a tracking dashboard and double observation/data extraction for a 5% case subset, were incorporated as part of quality assurance. Internet-based synchronisation during data collection posed intermittent challenges. 5) Data management, cleaning and analysis: E-data collection was perceived to improve data quality and reduce time cleaning.ConclusionsThe E-Data system, custom-built for EN-BIRTH, was valued by the site teams, particularly for time-stamped clinical observation of complex multiple simultaneous events at birth, without which the study objectives could not have been met. However before selection of a custom-built E-data tool, the development time, higher training and IT support needs, and connectivity challenges need to be considered against the proposed study or programme's purpose, and currently available E-data tool options.
| S-EPMC7995708 | biostudies-literature
Project description:ObjectivesEffective data collection and surveillance of epidemiological trends are essential in confronting the growing challenges associated with substance use (SU), especially in light of emerging trends and underreporting of cases. However, research and data are scarce regarding SU and substance use disorder (SUD) in Korea.MethodsWe conducted a scoping review to identify data sources and surveillance methods used in SU research in Korea up to December 2023. This review was complemented by semi-structured consultations with experts in this area in Korea, whose feedback led to revisions of previously identified data sources and assessments.ResultsOur review identified 32 publications conducting secondary analyses on existing data to examine the epidemiology of SU and SUD in Korea. Of these, 14 studies utilized clinical databases to explore the prescription patterns of addictive substances, particularly opioids. Eleven data sources showed promise for advancing SU research; however, they face substantial limitations, including a lack of available data, missing data, the absence of key variables, the exclusion of marginalized populations not captured within the clinical system, and complexities in matching individual-level data across time points and datasets.ConclusionsCurrent surveillance methods for SU in Korea face considerable challenges in accessibility, usability, and standardization. Moreover, existing data repositories may fail to capture information on populations not served by clinical or judicial systems. To systematically improve surveillance approaches, it is necessary to develop a robust and nationally representative survey, refine the use of existing clinical data, and ensure the availability of data on treatment facilities.
| S-EPMC11309831 | biostudies-literature
Project description:The objective was to compare case ascertainment, agreement, validity, and missing values for clinical research data obtained, processed, and linked electronically from electronic health records (EHR) compared to "manual" data processing and record abstraction in a cohort of out-of-hospital trauma patients.? This was a secondary analysis of two sets of data collected for a prospective, population-based, out-of-hospital trauma cohort evaluated by 10 emergency medical services (EMS) agencies transporting to 16 hospitals, from January 1, 2006, through October 2, 2007. Eighteen clinical, operational, procedural, and outcome variables were collected and processed separately and independently using two parallel data processing strategies by personnel blinded to patients in the other group. The electronic approach included EHR data exports from EMS agencies, reformatting, and probabilistic linkage to outcomes from local trauma registries and state discharge databases. The manual data processing approach included chart matching, data abstraction, and data entry by a trained abstractor. Descriptive statistics, measures of agreement, and validity were used to compare the two approaches to data processing.? During the 21-month period, 418 patients underwent both data processing methods and formed the primary cohort. Agreement was good to excellent (kappa = 0.76 to 0.97; intraclass correlation coefficient [ICC] = 0.49 to 0.97), with exact agreement in 67% to 99% of cases and a median difference of zero for all continuous and ordinal variables. The proportions of missing out-of-hospital values were similar between the two approaches, although electronic processing generated more missing outcomes (87 of 418, 21%, 95% confidence interval [CI] = 17% to 25%) than the manual approach (11 of 418, 3%, 95% CI = 1% to 5%). Case ascertainment of eligible injured patients was greater using electronic methods (n = 3,008) compared to manual methods (n = 629).? In this sample of out-of-hospital trauma patients, an all-electronic data processing strategy identified more patients and generated values with good agreement and validity compared to traditional data collection and processing methods.
| S-EPMC3278860 | biostudies-literature
Project description:ObjectiveElectronic data collection (EDC) has become a suitable alternative to paper based data collection (PBDC) in biomedical research even in resource poor settings. During a survey in Nepal, data were collected using both systems and data entry errors compared between both methods. Collected data were checked for completeness, values outside of realistic ranges, internal logic and date variables for reasonable time frames. Variables were grouped into 5 categories and the number of discordant entries were compared between both systems, overall and per variable category.ResultsData from 52 variables collected from 358 participants were available. Discrepancies between both data sets were found in 12.6% of all entries (2352/18,616). Differences between data points were identified in 18.0% (643/3580) of continuous variables, 15.8% of time variables (113/716), 13.0% of date variables (140/1074), 12.0% of text variables (86/716), and 10.9% of categorical variables (1370/12,530). Overall 64% (1499/2352) of all discrepancies were due to data omissions, 76.6% (1148/1499) of missing entries were among categorical data. Omissions in PBDC (n = 1002) were twice as frequent as in EDC (n = 497, p < 0.001). Data omissions, specifically among categorical variables were identified as the greatest source of error. If designed accordingly, EDC can address this short fall effectively.
| S-EPMC6704619 | biostudies-literature
Project description:BackgroundEpidemiologic cohort studies have begun to leverage electronic research participant portals to facilitate data collection, integrate wearable technologies, lower costs, and engage participants. However, little is known about the acceptability of portal use by research participants.ObjectiveThe aim of this study is to conduct focus groups among a sample of Cancer Prevention Study-3 (CPS-3) participants to better understand their preferences and concerns about research portals.MethodsCPS-3 participants were stratified based on sex, race and ethnicity, age, and cancer status, and randomly invited to participate. Focus groups used an exploratory case design with semistructured guides to prompt discussion. Using a constant comparison technique, transcripts were assigned codes to identify themes.ResultsParticipants (31/59, 52% women; 52/59, 88% White/non-Latinx) were favorably disposed toward using a research participant portal to take surveys, communicate with the study staff, and upload data. Most participants indicated that a portal would be beneficial and convenient but expressed concerns over data safety. Participants stressed the importance of an easy-to-use and trustworthy portal that is compatible with mobile devices.ConclusionsIn addition to being beneficial to researchers, portals may also benefit participants as long as the portals are secure and simple. Participants believe that portals can provide convenient ways to report data and remain connected to the study.
| S-EPMC7563628 | biostudies-literature
Project description:Online data collection methods are expanding the ease and access of developmental research for researchers and participants alike. While its popularity among developmental scientists has soared during the COVID-19 pandemic, its potential goes beyond just a means for safe, socially distanced data collection. In particular, advances in video conferencing software has enabled researchers to engage in face-to-face interactions with participants from nearly any location at any time. Due to the novelty of these methods, however, many researchers still remain uncertain about the differences in available approaches as well as the validity of online methods more broadly. In this article, we aim to address both issues with a focus on moderated (synchronous) data collected using video-conferencing software (e.g., Zoom). First, we review existing approaches for designing and executing moderated online studies with young children. We also present concrete examples of studies that implemented choice and verbal measures (Studies 1 and 2) and looking time (Studies 3 and 4) across both in-person and online moderated data collection methods. Direct comparison of the two methods within each study as well as a meta-analysis of all studies suggest that the results from the two methods are comparable, providing empirical support for the validity of moderated online data collection. Finally, we discuss current limitations of online data collection and possible solutions, as well as its potential to increase the accessibility, diversity, and replicability of developmental science.
| S-EPMC8595939 | biostudies-literature
Project description:Preterm birth is commonly defined as any birth before 37 weeks completed weeks of gestation. An estimated 15 million infants are born preterm globally, disproportionately affecting low and middle income countries (LMIC). It contributes directly to estimated one million neonatal deaths annually and is a significant contributor to childhood morbidity. However, in many clinical settings, the information available to calculate completed weeks of gestation varies widely. Accurate dating of the last menstrual period (LMP), as well as access to clinical and ultrasonographic evaluation are important components of gestational age assessment antenatally. This case definition assign levels of confidence to categorisation of births as preterm, utilising assessment modalities which may be available across different settings. These are designed to enable systematic safety evaluation of vaccine clinical trials and post-implementation programmes of immunisations in pregnancy.
| S-EPMC5139808 | biostudies-other
Project description:Background: Electronic data collection is increasingly available as a means to collect pain-related clinical trial data; however, effectiveness and costs relative to traditional data collection are uncertain. Aims: The aim of this study was to evaluate data quality, protocol adherence, satisfaction, and resource requirements of electronic data collection (i.e., Internet-based electronic submission) compared to traditional data collection methods (i.e., paper-based diaries and telephone interviews) in a perioperative factorial randomized controlled trial. Methods: This study was an open-label two-arm parallel randomized controlled trial. Women (18-75 years) undergoing breast cancer surgery were allocated to either electronic or traditional data collection and completed pain-related questionnaires at baseline, postoperative period, and 3-month follow-up (NCT02240199). Results: We acquired outcome data at all time points from 78 randomized patients, 38 in the electronic group and 40 in the traditional group. The number of data queries (e.g., erroneously entered data) per patient was higher in the electronic data group (4.92 [SD = 4.67] vs. 1.88 [SD = 1.51]; P < 0.001). No between-group differences were observed for compliance with medications, data completeness, loss to follow-up, or patient or research assistant satisfaction. More research assistant time per patient was spent collecting data in the traditional group (42.6 min [SD = 12.8] vs. 9.92 min [SD = 7.6]; P < 0.001); however, costs per patient were higher in the electronic group ($176.85 [SD = 2.90] vs. $16.33 [SD = 4.90]; P < 0.001). Conclusion: Electronic data collection is feasible for perioperative pain clinical trials. Additional trials, including different surgical populations, are needed to confirm our findings and optimize use of electronic data capture methods.
| S-EPMC8730625 | biostudies-literature