Dinh Nhi, Agarwal Smisha, Avery Lisa, Ponnappan Priya, Chelangat Judith, Amendola Paul, Labrique Alain, Bartlett Linda
Department of International Health, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States.
Centre for Global Public Health, University of Manitoba, Winnipeg, MB, Canada.
JMIR Form Res. 2022 Jun 20;6(6):e34741. doi: 10.2196/34741.
iDeliver, a digital clinical support system for maternal and neonatal care, was developed to support quality of care improvements in Kenya.
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.
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.
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.
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.
iDeliver是一款用于孕产妇和新生儿护理的数字临床支持系统，旨在支持肯尼亚改善护理质量。
采用实施研究方法，我们评估了iDeliver随时间推移的采用情况和保真度，并评估了使用它来提供卫生部常规报告的可行性。
我们分析了从iDeliver中定期收集的数据，该系统于2018年12月至2020年9月在特兰斯马拉西县医院实施。为了评估其采用情况，我们评估了随时间推移在iDeliver中记录的实际机构分娩比例。我们通过研究护理人员在分娩工作流程各阶段的数据录入完整性以及使用情况是否反映了iDeliver的预期功能，来评估iDeliver使用的保真度。我们还检查了肯尼亚卫生部优先考虑的孕产妇和新生儿指标的数据完整性。
iDeliver共记录了1164例分娩，占该机构22个月内分娩总数的45.31%（1164/2569）。这种登记采用率随时间显著提高，每季度平均提高6.7%（标准误2.1）（P = 0.005），从2018年第四季度的9.6%（15/157）提高到2020年第三季度的64%（235/367）。在iDeliver的整个工作流程中，所有变量的总体完成率每季度平均显著提高2.9%（标准误0.4）（P < 0.001），从2018年第四季度的22.25%（257/1155）提高到2020年第三季度的49.21%（8905/18095）。出院-分娩总结阶段的数据完成率最高（16796/23280，72.15%），分娩体征阶段的数据完成率最低（848/5820，14.57%）。卫生部关键指标的完成率每季度平均也显著提高4.6%（标准误0.5）（P < 0.001），从2018年第四季度的27.1%（69/255）提高到2020年第三季度的83.75%（3346/3995）。
iDeliver的采用情况和数据完整性随时间显著改善。对iDeliver使用保真度的评估表明，一些功能更容易使用，因为提供者有时间输入数据；然而，在分娩活跃期使用较少，而此时提供者必然要照顾产妇和新生儿。这些关于iDeliver使用采用情况和保真度的见解促使团队调整应用程序，以反映用户的使用文化，并进一步改进iDeliver的实施。
