ArticleJournal of research practice2018
Conducting a Large Public Health Data Collection Project in Uganda: Methods, Tools, and Lessons Learned.
Article in Journal of research practice, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
Who cites it
2 citing papers in PubMed.
- Tailoring Mobile Data Collection for Intervention Research in a Challenging Context: Development and Implementation in the Malakit Study.JMIR formative research · 2022Article
- Preliminary validation of the PRImary care facility Management Evaluation tool (PRIME-Tool), a national facility management survey implemented in Ghana.BMC health services research · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors.
Funding
Abstract
We report on the implementation experience of carrying out data collection and other activities for a public health evaluation study on whether U.S. President's Emergency Plan for AIDS Relief (PEPFAR) investment improved utilization of health services and health system strengthening in Uganda. The retrospective study period focused on the PEPFAR scale-up, from mid-2005 through mid-2011, a period of expansion of PEPFAR programing and health services. We visited 315 health care facilities in Uganda in 2011 and 2012 to collect routine health management information system data forms, as well as to conduct interviews with health system leaders. An earlier phase of this research project collected data from all 112 health district headquarters, reported elsewhere. This article describes the lessons learned from collecting data from health care facilities, project management, useful technologies, and mistakes. We used several new technologies to facilitate data collection, including portable document scanners, smartphones, and web-based data collection, along with older but reliable technologies such as car batteries for power, folding tables to create space, and letters of introduction from appropriate authorities to create entrée. Research in limited-resource settings requires an approach that values the skills and talents of local people, institutions and government agencies, and a tolerance for the unexpected. The development of personal relationships was key to the success of the project. We observed that capacity building activities were repaid many fold, especially in data management and technology.
Indexed as
Identifiers
30057632PMC6058317What OpenQuestion holds
Registered trials
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.