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Accepted for/Published in: JMIR Formative Research

Date Submitted: Nov 5, 2021
Date Accepted: Mar 31, 2022

The final, peer-reviewed published version of this preprint can be found here:

Implementation Outcomes Assessment of a Digital Clinical Support Tool for Intrapartum Care in Rural Kenya: Observational Analysis

Dinh N, Agarwal S, Avery L, Ponnappan P, Chelangat J, Amendola P, Labrique A, Bartlett L

Implementation Outcomes Assessment of a Digital Clinical Support Tool for Intrapartum Care in Rural Kenya: Observational Analysis

JMIR Form Res 2022;6(6):e34741

DOI: 10.2196/34741

PMID: 35723911

PMCID: 9253974

Implementation Outcomes Assessment of a Digital Clinical Support Tool for Intrapartum Care in Rural Kenya: An Observational Analysis

  • Nhi Dinh; 
  • Smisha Agarwal; 
  • Lisa Avery; 
  • Priya Ponnappan; 
  • Judith Chelangat; 
  • Paul Amendola; 
  • Alain Labrique; 
  • Linda Bartlett

ABSTRACT

Background:

To support quality of care improvements, iDeliver, a digital clinical support system for maternal and neonatal care, was developed.

Objective:

Taking an implementation research lens, we evaluated the adoption and fidelity of iDeliver and assessed the feasibility of its use to provide routine Ministry of Health reports.

Methods:

We analyzed routinely collected data from the iDeliver implemented at Trans Mara West sub-county Hospital (Kenya), from December 2018 to October 2020. To evaluate its adoption, we assessed the proportion of total facility deliveries over time. To examine the fidelity of iDeliver usage, we studied data completion to assess the plausibility of data entry by care providers during each stage of the labor and delivery workflow and if the usage reflected iDeliver’s envisioned function. We also examined the data completeness of maternal and neonatal indicators prioritized by the Kenyan Ministry of Health.

Results:

1164 deliveries were registered in iDeliver, capturing 47.3% of the facility’s deliveries over 22 months. Registration improved significantly from 32.3% in the first to 62.2% in the second phase of implementation (P=0.003). Across iDeliver’s workflow, the overall completion rate of all variables improved significantly from 34.1% to 48.0% in the second phase (P<0.001). Data completion was highest for the Discharge-Labor Summary (67.7%) and was lowest for Labor Signs (14.4%). The completion rate of the key Ministry of Health indicators also improved significantly (P<0.001).

Conclusions:

iDeliver’s adoption and data completeness improved significantly over time. Assessment of iDeliver’ usage fidelity suggested that some features were more easily utilized because providers had time to enter data, versus lower utilization during active childbirth when providers are necessarily engaged with the woman and baby. These insights on the adoption and fidelity of iDeliver usage prompted the team to adapt the application to reflect the users’ culture of use and further improve the implementation of iDeliver. Clinical Trial: newborn; neonatal health; maternal health; intrapartum care; labor and delivery; Kenya; digital clinical decision support; health information systems; digital health; implementation research


 Citation

Please cite as:

Dinh N, Agarwal S, Avery L, Ponnappan P, Chelangat J, Amendola P, Labrique A, Bartlett L

Implementation Outcomes Assessment of a Digital Clinical Support Tool for Intrapartum Care in Rural Kenya: Observational Analysis

JMIR Form Res 2022;6(6):e34741

DOI: 10.2196/34741

PMID: 35723911

PMCID: 9253974

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