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

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


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).


2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Ariel Esteban Bardach ◽  
Andrea Olga Alcaraz ◽  
Agustín Ciapponi ◽  
Osvaldo Ulises Garay ◽  
Andrés Pichón Riviere ◽  
...  

Abstract Background Around 6% of total deaths are related to alcohol consumption worldwide. Mathematical models are important tools to estimate disease burden and to assess the cost-effectiveness of interventions to address this burden. Methods We carried out a systematic review on models, searching main health literature databases up to July 2017. Pairs of reviewers independently selected, extracted data and assessed the quality of the included studies. Discrepancies were resolved by consensus. We selected those models exploring: a) disease burden (main metrics being attributable deaths, disability-adjusted life years, quality-adjusted life years) or b) economic evaluations of health interventions or policies, based on models including the aforementioned outcomes. We grouped models into broad families according to their common central methodological approach. Results Out of 4295 reports identified, 63 met our inclusion criteria and were categorized in three main model families that were described in detail: 1) State transition -i.e Markov- models, 2) Life Table-based models and 3) Attributable fraction-based models. Most studies pertained to the latter one (n = 29, 48.3%). A few miscellaneous models could not be framed into these families. Conclusions Our findings can be useful for future researchers and decision makers planning to undertake alcohol-related disease burden or cost-effectiveness studies. We found several different families of models. Countries interested in adopting relevant public health measures may choose or adapt the one deemed most convenient, based on the availability of existing data at the local level, burden of work, and public health and economic outcomes of interest.


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