Abstract
This paper presents the findings from two studies of the PartoPen system – a digital pen software application that enhances the partograph, a paper-based labor-monitoring tool used in developing regions. Previous studies have shown that correct use of the partograph significantly reduces pregnancy complications; however, partographs are not always correctly completed due to resource and training challenges. The PartoPen addresses these challenges by providing real-time decision support, instructions, and patient-specific reminders. The preliminary studies described in this paper examine how the PartoPen system affects classroom-based partograph training among nursing students at the University of Nairobi, and partograph completion in labor theater use by nurse midwives at Kenyatta National Hospital in Nairobi, Kenya. Initial results indicate that using the PartoPen system enhances student performance on partograph worksheets, and that use of the PartoPen system in labor wards positively affects partograph completion rates and nurses’ level of expertise using the partograph form.
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Acknowledgements
This research is funded by a Gates Grand Challenge in Global Health grant, a National Science Foundation Graduate Research Fellowship, and by the ATLAS Institute at the University of Colorado Boulder. We would like to thank the leadership of KNH, PMH, and the UoN, particularly Dr. John Ong’ech and Dr. Grace Omoni, for their support and cooperation during the PartoPen studies, and all of the students, nurses, and staff who participated in the studies. Research assistants Maya Appley, Addie Crawley, Sara Rosenblum, and Vincent Ochieng contributed significantly to this study.
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Appendix: KNH Partograph Form
Appendix: KNH Partograph Form
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Underwood, H., Ong’ech, J., Omoni, G., Wakasiaka, S., Sterling, S.R., Bennett, J.K. (2014). Improving Partograph Training and Use in Kenya Using the Partopen Digital Pen System. In: Fernández-Chimeno, M., et al. Biomedical Engineering Systems and Technologies. BIOSTEC 2013. Communications in Computer and Information Science, vol 452. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-44485-6_28
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