scholarly journals Development of an Electronic Data Collection System to Support a Large-Scale HIV Behavioral Intervention Trial: Protocol for an Electronic Data Collection System

10.2196/10777 ◽  
2018 ◽  
Vol 7 (12) ◽  
pp. e10777 ◽  
Author(s):  
W Scott Comulada ◽  
Wenze Tang ◽  
Dallas Swendeman ◽  
Amy Cooper ◽  
Jeremy Wacksman ◽  
...  
Keyword(s):  
Data Collection ◽  
Behavioral Intervention ◽  
Large Scale ◽  
Trial Protocol ◽  
Intervention Trial ◽  
Collection System ◽  
Electronic Data ◽  
Data Collection System ◽  
Electronic Data Collection

scholarly journals A Novel Electronic Data Collection System for Large-Scale Surveys of Neglected Tropical Diseases

PLoS ONE ◽  
2013 ◽  
Vol 8 (9) ◽  
pp. e74570 ◽  
Author(s):  
Jonathan D. King ◽  
Joy Buolamwini ◽  
Elizabeth A. Cromwell ◽  
Andrew Panfel ◽  
Tesfaye Teferi ◽  
...  
Keyword(s):  
Data Collection ◽  
Large Scale ◽  
Neglected Tropical Diseases ◽  
Tropical Diseases ◽  
Collection System ◽  
Electronic Data ◽  
Data Collection System ◽  
Electronic Data Collection

scholarly journals Data quality and cost-effectiveness analyses of electronic and paper-based interviewer-administered public health surveys: a systematic review (Preprint)

2020 ◽  
Author(s):  
Atinkut Alamirrew Zeleke ◽  
Tolga Naziyok ◽  
Fleur Fritz ◽  
Lara Christianson ◽  
Rainer Röhrig
Keyword(s):  
Public Health ◽  
Cost Effectiveness ◽  
Data Collection ◽  
Data Quality ◽  
Cost Reduction ◽  
Health Surveys ◽  
Collection System ◽  
Electronic Data ◽  
Data Collection System ◽  
Electronic Data Collection

BACKGROUND Population-level survey (PLS) is an essential standard method used in public health research. It supports to quantify sociodemographic events and support public health policy development and intervention designs with evidence. During survey, data collection mechanisms seem the most determinant to avoid mistakes before they happen. The use of electronic devices such as smartphones and tablet computers improve the quality and cost-effectiveness of public health surveys. However, there is a lack of systematically analyzed evidence to show the potential impact of electronic-based data collection tools on data quality and cost reduction in interviewer-administered surveys compared to the standard paper-based data collection system OBJECTIVE This systematic review aims to evaluate the impact of interviewer-administered electronic device data collection methods concerning data quality and cost reduction in PLS compared to the traditional paper-based methods. METHODS A systematic search was conducted in MEDLINE, CINAHL, PsycINFO, the Web of Science, EconLit and Cochrane CENTRAL, and CDSR to identify relevant studies from 2008 to 2018. We included randomized and non-randomized studies that examine data quality and cost reduction outcomes. Moreover, usability, user experience, and usage parameters from the same studies were included. Two independent authors screened the title, abstract, and finally extracted data from the included papers. A third author mediated in case of disagreement. The review authors used EndNote for de-duplication and Rayyan for screening RESULTS The search strategy from the electronic databases found 3,817 articles. After de-duplication, 2,533 articles were screened, and 14 articles fulfilled the inclusion criteria. None of the studies was designed as a randomized control trial. Most of the studies have a quasi-experimental design, like comparative experimental evaluation studies nested on the other ongoing cross-sectional surveys. 4 comparative evaluations, 2 pre-post intervention comparative evaluation, 2 retrospectives comparative evaluation, and 4 one arm non-comparative studies were included in our review. Meta-analysis was not possible because of the heterogeneity in study design, the type, and level of outcome measurements and the study settings. Individual article synthesis showed that data from electronic data collection systems possessed good quality data and delivered faster when compared to the paper-based data collection system. Only two studies linked the cost and data quality outcomes to describe the cost-effectiveness of electronic-based data collection systems. Despite the poor economic evaluation qualities, most of the reported results were in favor of EDC for the large-scale surveys. The field data collectors reported that an electronic data collection system was a feasible, acceptable and preferable tool for their work. Onsite data error prevention, fast data submission, and easy to handle devices were the comparative advantages of electronic data collection systems. Technical difficulties, accidental data loss, device theft, security concerns, power surges, and internet connection problems were reported as challenges during the implementation. CONCLUSIONS Though positive evidence existed about the comparative advantage of electronic data capture over paper-based tools, the included studies were not methodologically rigorous enough to combine. We need more rigorous studies that demonstrate the comparative evidence of paper and electronic-based data collection systems in public health surveys on data quality, work efficiency, and cost reduction CLINICALTRIAL The review protocol is registered in the International Prospective Register for Systematic Reviews (PROSPERO) CRD42018092259. The protocol of this article was also pre-published (JMIR Res Protoc 2019;8(1): e10678 doi:10.2196/10678).

scholarly journals Quality Improvement in Juvenile Idiopathic Arthritis: a Mixed-methods Implementation Pilot of the CAPTURE-JIA Dataset

2022 ◽  
Author(s):  
Flora Mcerlane ◽  
Chris Anderson ◽  
Saskia Lawson-Tovey ◽  
Barbara Lee ◽  
Chris Lee ◽  
...  
Keyword(s):  
Juvenile Idiopathic Arthritis ◽  
Quality Improvement ◽  
Mixed Methods ◽  
Data Collection ◽  
Clinical Care ◽  
Data Collection Tool ◽  
Collection System ◽  
Electronic Data ◽  
Data Collection System ◽  
Electronic Data Collection

Abstract BackgroundA significant proportion of children and young people with juvenile idiopathic arthritis (JIA) do not achieve inactive disease during the first two years following diagnosis. Refinements to clinical care pathways have the potential to improve clinical outcomes but a lack of consistent and contemporaneous clinical data presently precludes standard setting and implementation of meaningful quality improvement programmes. This study was the first to pilot clinical data collection and analysis using the CAPTURE-JIA dataset, and to explore patient and clinician-reported feasibility and acceptability data.MethodsA multiphase mixed-methods approach enabled prospective collection of quantitative data to examine the feasibility and efficacy of dataset collection and of qualitative data informing the context and processes of implementation. An initial paper pilot informed the design of a bespoke electronic data collection system (the Agileware system), with a subsequent electronic pilot informing the final CAPTURE-JIA data collection tool. ResultsPaper collection of patient data was feasible but time-consuming in the clinical setting. Phase 1 paper pilot data (121 patients) identified three themes: problematic data items (14/62 data items received >40% missing data), formatting of data collection forms and a clinician-highlighted need for digital data collection, informing Phase 2 electronic data collection tool development. Patients and families were universally supportive of the collection and analysis of anonymised patient data to inform clinical care. No apparent preference for paper / electronic data collection was reported by families. Phase 3 electronic pilot data (38 patients) appeared complete and the system reported to be easy to use. Analysis of the study dataset and a dummy longitudinal dataset confirmed that all eleven JIA national audit questions can be answered using the electronic system. ConclusionsMulticentre CAPTURE-JIA data collection is feasible and acceptable, with a bespoke data collection system highlighted as the most satisfactory solution. The study is informing ongoing work towards a streamlined and flexible national paediatric data collection system to drive quality improvement in clinical care.

Combining Adobe Forms and Dropbox to Obtain a Low-Cost Electronic Data Collection System

2019 ◽  
Vol 25 (3) ◽  
pp. 250-256 ◽  
Author(s):  
María Yoldi-Negrete ◽  
Ingrid Pamela Morales-Cedillo ◽  
Iñaki Navarro-Castellanos ◽  
Ana Fresán-Orellana ◽  
Rubén Panduro-Flores ◽  
...  
Keyword(s):  
Data Collection ◽  
Low Cost ◽  
Collection System ◽  
Electronic Data ◽  
Data Collection System ◽  
Electronic Data Collection

scholarly journals Development of an Electronic Data Collection System to Support a Large-Scale HIV Behavioral Intervention Trial: Protocol for an Electronic Data Collection System (Preprint)

2018 ◽  
Author(s):  
W Scott Comulada ◽  
Wenze Tang ◽  
Dallas Swendeman ◽  
Amy Cooper ◽  
Jeremy Wacksman ◽  
...  
Keyword(s):  
Data Collection ◽  
Data Security ◽  
Text Messaging ◽  
Large Scale ◽  
Text Messages ◽  
Intervention Trial ◽  
Electronic Data ◽  
Electronic Data Collection ◽  
Intervention Delivery ◽  
Study Participants

BACKGROUND Advancing technology has increased functionality and permitted more complex study designs for behavioral interventions. Investigators need to keep pace with these technological advances for electronic data capture (EDC) systems to be appropriately executed and utilized at full capacity in research settings. Mobile technology allows EDC systems to collect near real-time data from study participants, deliver intervention directly to participants’ mobile devices, monitor staff activity, and facilitate near real-time decision making during study implementation. OBJECTIVE This paper presents the infrastructure of an EDC system designed to support a multisite HIV biobehavioral intervention trial in Los Angeles and New Orleans: the Adolescent Medicine Trials Network “Comprehensive Adolescent Research & Engagement Studies” (ATN CARES). We provide an overview of how multiple EDC functions can be integrated into a single EDC system to support large-scale intervention trials. METHODS The CARES EDC system is designed to monitor and document multiple study functions, including, screening, recruitment, retention, intervention delivery, and outcome assessment. Text messaging (short message service, SMS) and nearly all data collection are supported by the EDC system. The system functions on mobile phones, tablets, and Web browsers. RESULTS ATN CARES is enrolling study participants and collecting baseline and follow-up data through the EDC system. Besides data collection, the EDC system is being used to generate multiple reports that inform recruitment planning, budgeting, intervention quality, and field staff supervision. The system is supporting both incoming and outgoing text messages (SMS) and offers high-level data security. Intervention design details are also influenced by EDC system platform capabilities and constraints. Challenges of using EDC systems are addressed through programming updates and training on how to improve data quality. CONCLUSIONS There are three key considerations in the development of an EDC system for an intervention trial. First, it needs to be decided whether the flexibility provided by the development of a study-specific, in-house EDC system is needed relative to the utilization of an existing commercial platform that requires less in-house programming expertise. Second, a single EDC system may not provide all functionality. ATN CARES is using a main EDC system for data collection, text messaging (SMS) interventions, and case management and a separate Web-based platform to support an online peer support intervention. Decisions need to be made regarding the functionality that is crucial for the EDC system to handle and what functionality can be handled by other systems. Third, data security is a priority but needs to be balanced with the need for flexible intervention delivery. For example, ATN CARES is delivering text messages (SMS) to study participants’ mobile phones. EDC data security protocols should be developed under guidance from security experts and with formative consulting with the target study population as to their perceptions and needs. INTERNATIONAL REGISTERED REPOR PRR1-10.2196/10777

Electronic data capture on athletes’ pre-participation health and in-competition injury and illness at major sports championships: An extended usability study in Athletics

2016 ◽  
Vol 24 (2) ◽  
pp. 136-145 ◽  
Author(s):  
David Karlsson ◽  
Toomas Timpka ◽  
Jenny Jacobsson ◽  
Juan-Manuel Alonso ◽  
Jan Kowalski ◽  
...  
Keyword(s):  
Data Collection ◽  
Self Report ◽  
Usability Study ◽  
Medical Terminology ◽  
Collection System ◽  
Electronic Data ◽  
Data Collection System ◽  
Electronic Data Collection ◽  
Key Issues ◽  
Individual Sports

This study set out to identify factors critical for the usability of electronic data collection in association with championships in individual sports. A qualitative analysis of electronic data collection system usability for collection of data on pre-participation health from athletes and in-competition injury and illness from team physicians was performed during the 2013 European Athletics Indoor Championships. A total of 15 athletes and team physicians participated. Athletes were found to experience few problems interacting with the electronic data collection system, but reported concerns about having to reflect on injury and illness before competitions and the medical terminology used. Team physicians encountered problems when first navigating through the module for clinical reporting, but they were not subjected to motivational problems. We conclude that athletes’ motivation to self-report health data and the design of the human–computer interface for team physicians are key issues for the usability of electronic data collection systems in association with championships in individual sports.

scholarly journals Electronic Data Management for Vaccine Trials in Low Resource Settings: Upgrades, Scalability, and Impact of ODK

2021 ◽  
Vol 9 ◽  
Author(s):  
Michael Marks ◽  
Sham Lal ◽  
Hannah Brindle ◽  
Pierre-Stéphane Gsell ◽  
Matthew MacGregor ◽  
...  
Keyword(s):  
Data Collection ◽  
Clinical Research ◽  
Data Management ◽  
Open Source ◽  
Large Scale ◽  
Democratic Republic Of Congo ◽  
World Health ◽  
Electronic Data ◽  
Diverse Range ◽  
Electronic Data Collection

Background: ODK provides software and standards that are popular solutions for off-grid electronic data collection and has substantial code overlap and interoperability with a number of related software products including CommCare, Enketo, Ona, SurveyCTO, and KoBoToolbox. These tools provide open-source options for off-grid use in public health data collection, management, analysis, and reporting. During the 2018–2020 Ebola epidemic in the North Kivu and Ituri regions of Democratic Republic of Congo, we used these tools to support the DRC Ministère de la Santé RDC and World Health Organization in their efforts to administer an experimental vaccine (VSV-Zebov-GP) as part of their strategy to control the transmission of infection.Method: New functions were developed to facilitate the use of ODK, Enketo and R in large scale data collection, aggregation, monitoring, and near-real-time analysis during clinical research in health emergencies. We present enhancements to ODK that include a built-in audit-trail, a framework and companion app for biometric registration of ISO/IEC 19794-2 fingerprint templates, enhanced performance features, better scalability for studies featuring millions of data form submissions, increased options for parallelization of research projects, and pipelines for automated management and analysis of data. We also developed novel encryption protocols for enhanced web-form security in Enketo.Results: Against the backdrop of a complex and challenging epidemic response, our enhanced platform of open tools was used to collect and manage data from more than 280,000 eligible study participants who received VSV-Zebov-GP under informed consent. These data were used to determine whether the VSV-Zebov-GP was safe and effective and to guide daily field operations.Conclusions: We present open-source developments that make electronic data management during clinical research and health emergencies more viable and robust. These developments will also enhance and expand the functionality of a diverse range of data collection platforms that are based on the ODK software and standards.

Sign in / Sign up

Export Citation Format

Share Document