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

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).

2018 ◽  
Author(s):  
Atinkut Alamirrew Zeleke ◽  
Tolga Naziyok ◽  
Fleur Fritz ◽  
Rainer Röhrig

BACKGROUND Population-level survey is an essential standard method used in public health research to quantify sociodemographic events and support public health policy development and intervention designs with evidence. Although all steps in the survey can contribute to the data quality parameters, data collection mechanisms seem the most determinant, as they can 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 lack of systematically analyzed evidence to show the potential impact on data quality and cost reduction of electronic-based data collection tools in interviewer-administered surveys. OBJECTIVE This systematic review aims to evaluate the impact of interviewer-administered electronic device data collection methods concerning data quality and cost reduction in population-level surveys compared with the traditional paper-based methods. METHODS We will conduct a systematic search on Medical Literature Analysis and Retrieval System Online, PubMed, CINAHL, PsycINFO, Global Health, Trip, ISI Web of Science, and Cochrane Library for studies from 2007 to 2018 to identify relevant studies. The review will include randomized and nonrandomized studies that examine data quality and cost reduction outcomes. Moreover, usability, user experience, and usage parameters from the same study will be summarized. Two independent authors will screen the title and abstract. A third author will mediate in cases of disagreement. If the studies are considered to be combinable with minimal heterogeneity, we will perform a meta-analysis. RESULTS The preliminary search in PubMed and Web of Science showed 1491 and 979 resulting hits of articles, respectively. The review protocol is registered in the International Prospective Register of Systematic Reviews (CRD42018092259). We anticipate January 30, 2019, to be the finishing date. CONCLUSIONS This systematic review will inform policymakers, investors, researchers, and technologists about the impact of an electronic-based data collection system on data quality, work efficiency, and cost reduction. CLINICALTRIAL PROSPERO CRD42018092259; http://www.crd.york.ac.uk/PROSPERO/display_record.php?ID= CRD42018092259 INTERNATIONAL REGISTERED REPORT PRR1-10.2196/10678


2022 ◽  
Author(s):  
Flora Mcerlane ◽  
Chris Anderson ◽  
Saskia Lawson-Tovey ◽  
Barbara Lee ◽  
Chris Lee ◽  
...  

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.


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 ◽  
...  

PLoS ONE ◽  
2013 ◽  
Vol 8 (9) ◽  
pp. e74570 ◽  
Author(s):  
Jonathan D. King ◽  
Joy Buolamwini ◽  
Elizabeth A. Cromwell ◽  
Andrew Panfel ◽  
Tesfaye Teferi ◽  
...  

2016 ◽  
Vol 24 (2) ◽  
pp. 136-145 ◽  
Author(s):  
David Karlsson ◽  
Toomas Timpka ◽  
Jenny Jacobsson ◽  
Juan-Manuel Alonso ◽  
Jan Kowalski ◽  
...  

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.


2016 ◽  
Vol 07 (03) ◽  
pp. 672-681 ◽  
Author(s):  
Aluísio Barros ◽  
Cauane Blumenberg

SummaryThis paper describes the use of Research Electronic Data Capture (REDCap) to conduct one of the follow-up waves of the 2004 Pelotas birth cohort. The aim is to point out the advantages and limitations of using this electronic data capture environment to collect data and control every step of a longitudinal epidemiological research, specially in terms of time savings and data quality.We used REDCap as the main tool to support the conduction of a birth cohort follow-up. By exploiting several REDCap features, we managed to schedule assessments, collect data, and control the study workflow. To enhance data quality, we developed specific reports and field validations to depict inconsistencies in real time.Using REDCap it was possible to investigate more variables without significant increases on the data collection time, when comparing to a previous birth cohort follow-up. In addition, better data quality was achieved since negligible out of range errors and no validation or missing inconsistencies were identified after applying over 7,000 interviews.Adopting electronic data capture solutions, such as REDCap, in epidemiological research can bring several advantages over traditional paper-based data collection methods. In favor of improving their features, more research groups should migrate from paper to electronic-based epidemiological research.Citation: Blumenberg C, Barros AJD. Electronic data collection in epidemiological research: The use of REDCap in the Pelotas birth cohorts


Sign in / Sign up

Export Citation Format

Share Document