Implementation outcomes assessment of a digital clinical support tool for intrapartum care in rural Kenya: observational analysis
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Authors
Dinh, Nhi
Agarwal, Smisha
Avery, Lisa
Ponnappan, Priya
Chelangat, Judith
Amendola, Paul
Labrique, Alain
Bartlett, Linda
Issue Date
2022-06-20
Type
Article
Language
en_US
Keywords
Newborn , Neonatal Health , Maternal Health , Intrapartum Care , Labor and Delivery , Kenya , Digital Clinical Decision Support , Health Information Systems , Digital Health , Implementation Research
Alternative Title
Abstract
Background:
iDeliver, a digital clinical support system for maternal and neonatal care, was developed to support quality of care improvements in Kenya.
Objective:
Taking an implementation research approach, we evaluated the adoption and fidelity of iDeliver over time and assessed the feasibility of its use to provide routine Ministry of Health (MOH) reports.
Methods:
We analyzed routinely collected data from iDeliver, which was implemented at the Transmara West Sub-County Hospital from December 2018 to September 2020. To evaluate its adoption, we assessed the proportion of actual facility deliveries that was recorded in iDeliver over time. We evaluated the fidelity of iDeliver use by studying the completeness of data entry by care providers during each stage of the labor and delivery workflow and whether the use reflected iDeliver’s envisioned function. We also examined the data completeness of the maternal and neonatal indicators prioritized by the Kenya MOH.
Results:
A total of 1164 deliveries were registered in iDeliver, capturing 45.31% (1164/2569) of the facility’s deliveries over 22 months. This uptake of registration improved significantly over time by 6.7% (SE 2.1) on average in each quarter-year (P=.005), from 9.6% (15/157) in the fourth quarter of 2018 to 64% (235/367) in the third quarter of 2020. Across iDeliver’s workflow, the overall completion rate of all variables improved significantly by 2.9% (SE 0.4) on average in each quarter-year (P<.001), from 22.25% (257/1155) in the fourth quarter of 2018 to 49.21% (8905/18,095) in the third quarter of 2020. Data completion was highest for the discharge-labor summary stage (16,796/23,280, 72.15%) and lowest for the labor signs stage (848/5820, 14.57%). The completion rate of the key MOH indicators also improved significantly by 4.6% (SE 0.5) on average in each quarter-year (P<.001), from 27.1% (69/255) in the fourth quarter of 2018 to 83.75% (3346/3995) in the third quarter of 2020.
Conclusions:
iDeliver’s adoption and data completeness improved significantly over time. The assessment of iDeliver’ use fidelity suggested that some features were more easily used because providers had time to enter data; however, there was low use during active childbirth, which is when providers are necessarily engaged with the woman and newborn. These insights on the adoption and fidelity of iDeliver use prompted the team to adapt the application to reflect the users’ culture of use and further improve the implementation of iDeliver.
Description
Citation
Dinh, N., Agarwal, S., Avery, L., Ponnappan, P., Chelangat, J., Amendola, P., Labrique, A., & Bartlett, L. (2022). Implementation Outcomes Assessment of a Digital Clinical Support Tool for Intrapartum Care in Rural Kenya: Observational Analysis. JMIR formative research, 6(6), e34741. https://doi.org/10.2196/34741
Publisher
JMIR Formative Research