Evidence map›Paper›PMID 29157182›Full record

ArticleGlobal health action2017

Do surveys with paper and electronic devices differ in quality and cost? Experience from the Rufiji Health and demographic surveillance system in Tanzania.

Oscar Mukasa, Hildegalda P Mushi, Nicolas Maire, Amanda Ross, Don de Savigny

Abstract readComparative Study
In one paragraph

Article in Global health action, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
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  7. Validation of the INDDEX24 mobile appThe British journal of nutrition · 2022
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Oscar Mukasaa Impact evaluation Thematic Section , Ifakara Health Institute (IHI) , Dar es Salaam , Tanzania.
Hildegalda P Mushia Impact evaluation Thematic Section , Ifakara Health Institute (IHI) , Dar es Salaam , Tanzania.
Nicolas Maireb Department of Epidemiology and Public Health , Swiss Tropical and Public Health Institute (Swiss TPH), University of Basel , Basel , Switzerland.ORCID http://orcid.org/0000-0002-1961-9343
Amanda Rossb Department of Epidemiology and Public Health , Swiss Tropical and Public Health Institute (Swiss TPH), University of Basel , Basel , Switzerland.ORCID http://orcid.org/0000-0001-6027-5645
Don de Savignyb Department of Epidemiology and Public Health , Swiss Tropical and Public Health Institute (Swiss TPH), University of Basel , Basel , Switzerland.ORCID http://orcid.org/0000-0002-6903-4722

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundData entry at the point of collection using mobile electronic devices may make data-handling processes more efficient and cost-effective, but there is little literature to document and quantify gains, especially for longitudinal surveillance systems.

objectiveTo examine the potential of mobile electronic devices compared with paper-based tools in health data collection.

methodsUsing data from 961 households from the Rufiji Household and Demographic Survey in Tanzania, the quality and costs of data collected on paper forms and electronic devices were compared. We also documented, using qualitative approaches, field workers, whom we called 'enumerators', and households' members on the use of both methods. Existing administrative records were combined with logistics expenditure measured directly from comparison households to approximate annual costs per 1,000 households surveyed.

resultsErrors were detected in 17% (166) of households for the paper records and 2% (15) for the electronic records (p < 0.001). There were differences in the types of errors (p = 0.03). Of the errors occurring, a higher proportion were due to accuracy in paper surveys (79%, 95% CI: 72%, 86%) compared with electronic surveys (58%, 95% CI: 29%, 87%). Errors in electronic surveys were more likely to be related to completeness (32%, 95% CI 12%, 56%) than in paper surveys (11%, 95% CI: 7%, 17%).The median duration of the interviews ('enumeration'), per household was 9.4 minutes (90% central range 6.4, 12.2) for paper and 8.3 (6.1, 12.0) for electronic surveys (p = 0.001). Surveys using electronic tools, compared with paper-based tools, were less costly by 28% for recurrent and 19% for total costs. Although there were technical problems with electronic devices, there was good acceptance of both methods by enumerators and members of the community.

conclusionsOur findings support the use of mobile electronic devices for large-scale longitudinal surveys in resource-limited settings.

Indexed as

Costs and Cost AnalysisData AccuracyElectronic Health RecordsPaperAdultHealth SurveysHumansMalePopulation SurveillanceTanzaniadata managementhealth and demographic surveillance systemshealth information systemspublic health

Identifiers

PMID29157182
PMCPMC5700525

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.