PMID- 33480859 OWN - NLM STAT- MEDLINE DCOM- 20210430 LR - 20210430 IS - 1438-8871 (Electronic) IS - 1439-4456 (Print) IS - 1438-8871 (Linking) VI - 23 IP - 1 DP - 2021 Jan 22 TI - Data Quality and Cost-effectiveness Analyses of Electronic and Paper-Based Interviewer-Administered Public Health Surveys: Systematic Review. PG - e21382 LID - 10.2196/21382 [doi] LID - e21382 AB - BACKGROUND: A population-level survey (PLS) is an essential and standard method used in public health research that supports the quantification of sociodemographic events, public health policy development, and intervention designs. Data collection mechanisms in PLS seem to be a significant determinant in avoiding mistakes. Using electronic devices such as smartphones and tablet computers improves the quality and cost-effectiveness of public health surveys. However, there is a lack of systematic evidence to show the potential impact of electronic data collection tools on data quality and cost reduction in interviewer-administered surveys compared with the standard paper-based data collection system. OBJECTIVE: This systematic review aims to evaluate the impact of the interviewer-administered electronic data collection methods on data quality and cost reduction in PLS compared with traditional methods. METHODS: We conducted a systematic search of MEDLINE, CINAHL, PsycINFO, the Web of Science, EconLit, Cochrane CENTRAL, and CDSR to identify relevant studies from 2008 to 2018. We included randomized and nonrandomized studies that examined data quality and cost reduction outcomes, as well as usability, user experience, and usage parameters. In total, 2 independent authors screened the title and abstract, and extracted data from selected papers. A third author mediated any disagreements. The review authors used EndNote for deduplication and Rayyan for screening. RESULTS: Our search produced 3817 papers. After deduplication, we screened 2533 papers, and 14 fulfilled the inclusion criteria. None of the studies were randomized controlled trials; most had a quasi-experimental design, for example, comparative experimental evaluation studies nested on other ongoing cross-sectional surveys. A total of 4 comparative evaluations, 2 pre-post intervention comparative evaluations, 2 retrospective comparative evaluations, and 4 one-arm noncomparative studies were included. Meta-analysis was not possible because of the heterogeneity in study designs, types, study settings, and level of outcome measurements. Individual paper synthesis showed that electronic data collection systems provided good quality data and delivered faster compared with paper-based data collection systems. Only 2 studies linked cost and data quality outcomes to describe the cost-effectiveness of electronic data collection systems. 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 offered by electronic data collection systems. Challenges during implementation included technical difficulties, accidental data loss, device theft, security concerns, power surges, and internet connection problems. CONCLUSIONS: Although evidence exists of the comparative advantages of electronic data collection compared with paper-based methods, the included studies were not methodologically rigorous enough to combine. More rigorous studies are needed to compare paper and electronic data collection systems in public health surveys considering data quality, work efficiency, and cost reduction. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/10678. CI - (c)Atinkut Alamirrew Zeleke, Tolga Naziyok, Fleur Fritz, Lara Christianson, Rainer Rohrig. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 22.01.2021. FAU - Zeleke, Atinkut Alamirrew AU - Zeleke AA AUID- ORCID: 0000-0001-7838-9050 AD - Medical Informatics, Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany. AD - Division of Medical Informatics, Carl von Ossitetzky University Oldenburg, Oldenburg, Germany. FAU - Naziyok, Tolga AU - Naziyok T AUID- ORCID: 0000-0001-9102-4777 AD - Division of Medical Informatics, Carl von Ossitetzky University Oldenburg, Oldenburg, Germany. FAU - Fritz, Fleur AU - Fritz F AUID- ORCID: 0000-0002-9005-6766 AD - Institute of Medical Informatics, University of Munster, Munster, Germany. FAU - Christianson, Lara AU - Christianson L AUID- ORCID: 0000-0002-7780-255X AD - Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany. FAU - Rohrig, Rainer AU - Rohrig R AUID- ORCID: 0000-0002-0032-5118 AD - Division of Medical Informatics, Carl von Ossitetzky University Oldenburg, Oldenburg, Germany. AD - Institute for Medical Informatics, Medical Faculty of RWTH University Aachen, Aachen, Germany. LA - eng PT - Journal Article PT - Research Support, Non-U.S. Gov't PT - Systematic Review DEP - 20210122 PL - Canada TA - J Med Internet Res JT - Journal of medical Internet research JID - 100959882 SB - IM MH - Cost-Benefit Analysis/*standards MH - Cross-Sectional Studies MH - *Data Accuracy MH - Health Surveys/*economics MH - Humans MH - Public Health/*economics/*methods MH - Retrospective Studies PMC - PMC7864777 OTO - NOTNLM OT - demographic and health survey OT - electronic data collection OT - mobile phone OT - smartphone OT - tablet computer COIS- Conflicts of Interest: None declared. EDAT- 2021/01/23 06:00 MHDA- 2021/05/01 06:00 PMCR- 2021/01/22 CRDT- 2021/01/22 12:14 PHST- 2020/06/12 00:00 [received] PHST- 2020/10/28 00:00 [accepted] PHST- 2020/08/03 00:00 [revised] PHST- 2021/01/22 12:14 [entrez] PHST- 2021/01/23 06:00 [pubmed] PHST- 2021/05/01 06:00 [medline] PHST- 2021/01/22 00:00 [pmc-release] AID - v23i1e21382 [pii] AID - 10.2196/21382 [doi] PST - epublish SO - J Med Internet Res. 2021 Jan 22;23(1):e21382. doi: 10.2196/21382.