Paperless registration during survey enumerations and large oral cholera mass vaccination in Zanzibar, the United Republic of Tanzania

Ali, Mohammad; Deen, Jaqueline L.; Khatib, Ahmed; Enwere, Godwin; Seidlein, Lorenz von; Reyburn, Rita; Ali, Said M.; Chang, Na Yoon; Perroud, Valérie; Marodon, Frédérique; Saleh, Abdul A.; Hashim, Ramadhan; Lopez, Anna Lena; Beard, James; Ley, Benedikt; Thriemer, Kamala; Puri, Mahesh; Sah, Binod; Jiddawi, Mohamed Saleh; Clemens, John D.

doi:10.2471/blt.09.070334

Cited by 32 publications

(36 citation statements)

References 8 publications

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“…The ODK software provides most of the functions that we required, but certain things, like being able to edit a form once it has been finalised, are currently not possible. Other research sites, including HDSSs, have developed their own software for such purposes [1,21,22], which was beyond our current capacity.…”

Section: Discussionmentioning

confidence: 99%

“…Electronic data collection (EDC) has become common in low-resource settings, and has been useful in many types of health research, including large one-off household surveys [1], on-going clinic-based studies [2], and in long-term community field sites [3]. Introducing EDC to a rural research site with existing long-running protocols requires several issues to be considered:

Availability of appropriate hardware and software : Devices have improved in quality in recent years, but in low-resource settings sourcing and maintaining equipment can be difficult, due to lack of local services [4].

…”

Section: Introductionmentioning

confidence: 99%

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Implementing electronic data capture at a well-established health and demographic surveillance site in rural northern Malawi

McLean

Dube

Saul

et al. 2017

Global Health Action

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This article aims to assess multiple issues of resources, staffing, local opinion, data quality, cost, and security while transitioning to electronic data collection (EDC) at a long-running community research site in northern Malawi. Levels of missing and error fields, delay from data collection to availability, and average number of interviews per day were compared between EDC and paper in a complex, repeated annual household survey. Three focus groups with field and data staff with experience using both methods, and in-depth interviews with participants were carried out. Cost for each method were estimated and compared. Missing data was more common on paper questionnaires than on EDC, and a similar number were carried out per day. Fieldworkers generally preferred EDC, but data staff feared for their employment. Most respondents had no strong preference for a method. The cost of the paper system was estimated to be higher than using EDC. The existing infrastructure and technical expertise could be adapted to using EDC, but changes have an impact on data processing jobs as fewer, and better qualified staff are required. EDC is cost-effective, and, for a long-running site, may offer further savings, as devices can be used in multiple studies and perform several other functions. EDC is accepted by fieldworkers and respondents, has good levels of quality and timeliness, and security can be maintained. EDC is well-suited for use in a well-established research site using and developing existing infrastructure and expertise.

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Section: Discussionmentioning

confidence: 99%

…”

Section: Introductionmentioning

confidence: 99%

Implementing electronic data capture at a well-established health and demographic surveillance site in rural northern Malawi

McLean

Dube

Saul

et al. 2017

Global Health Action

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“…The anticipation is that electronic data capturing tools may overcome substantial limitations of the paper-based system regarding saving time, improving the data quality, and minimizing overall cost [6,7,9,13,14]. Evaluations of such systems require periodic and setting context evidence to support the growing claim on their efficiency, effectiveness, and impacts [15,16].…”

Section: Scientific Backgroundmentioning

confidence: 99%

Evaluation of Electronic and Paper-Pen Data Capturing Tools for Data Quality in a Public Health Survey in a Health and Demographic Surveillance Site, Ethiopia: Randomized Controlled Crossover Health Care Information Technology Evaluation (Preprint)

Zeleke¹,

Worku²,

Demissie³

et al. 2018

Preprint

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Background: Periodic demographic health surveillance and surveys are the main sources of health information in developing countries. Conducting survey in requires extensive use of paper-pen and manual work and lengthy processes to generate the required information. Despite the rise of popularity in using electronic data collection systems to alleviate the problems, sufficient evidence is not available to support the use of electronic data capture tools in interviewer administered data collection processes.Objective: The purpose of this study was to compare data quality parameters in the data collected using mobile electronic and standard paper-based data capture tools in one of health and demographic surveillance sites in northwest Ethiopia Methods: A randomized controlled crossover Healthcare IT-Evaluation was conducted from May 10 to June 3 rd , 2016 in demographic and surveillance site. Twelve interview administrator, as two individuals in six groups (one with a tablet computer and the other with paper-based questionnaire), were assigned in the six towns of the surveillance premises. Data collectors switch data collection method based on computer generated random order. Data was cleaned using Mysql program and transferred to SPSS and R statistical software for analysis. Descriptive and mixed ordinal logistic analyses employed. The qualitative interview audio record was transcribed, and the usability of this open data kit (ODK) based system was assessed using system usability scale (SUS) and interview mapping in the isometric dialogue principles for system usability.Result: From the submitted 1,251 complete records/questionnaires in each tools, 42 % (522) of the paper and pen data capture (PPDC) and 29 % (285) of the electronic data capture (EDC) tool questionnaires had one or more types of data quality errors. The overall error rates were 1.67% and 0.6% for PPDC and EDC respectively. The chances of more errors on PPDC tool were multiplied by 1.015 for each additional question in the interview compared to EDC. The SUS score of the data collectors was 85.6. In qualitative data response mapping, EDC had more positive suitability of task responses with few error tolerance characteristics. Conclusion:EDC possessed significantly better data quality and efficient compared with PPDC, explained in fewer errors, instant data submission, and easy handling. The EDC proved to be a usable data collection tool in the rural study setting. The consistent power source and decent 2 internet connection, standby technical support, and security assurance for the device users suggested by the data collectors before full-fledged the implementation of the system.

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“…The outcome variable, respondents' vaccination status, was obtained from the mass vaccination database that had been compiled with the use of personal digital assistants by the International Vaccine Institute, Seoul. 24 Receipt of two complete doses of OCV was coded with a value of 1 (viz., fully immunized) and receipt of one or zero doses with a value of 0 (not immunized).…”

Section: Discussionmentioning

confidence: 99%

“…This two-dose vaccine was offered without charge in two rounds in January and February 2009. 24 Nine temporary vaccination posts were set up on each island in the target communities; posts were open daily for at least eight hours and staffed with local health personnel and villagers.…”

Section: Introductionmentioning

confidence: 99%

Social and cultural determinants of oral cholera vaccine uptake in Zanzibar

Scheffold

Ali

Hutubessy

et al. 2012

Human Vaccines & Immunotherapeutics

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Paperless registration during survey enumerations and large oral cholera mass vaccination in Zanzibar, the United Republic of Tanzania

Cited by 32 publications

References 8 publications

Implementing electronic data capture at a well-established health and demographic surveillance site in rural northern Malawi

Implementing electronic data capture at a well-established health and demographic surveillance site in rural northern Malawi

Evaluation of Electronic and Paper-Pen Data Capturing Tools for Data Quality in a Public Health Survey in a Health and Demographic Surveillance Site, Ethiopia: Randomized Controlled Crossover Health Care Information Technology Evaluation (Preprint)

Social and cultural determinants of oral cholera vaccine uptake in Zanzibar

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