Implementation of a Newborn Clinical Decision Support Software (NoviGuide) in a Rural District Hospital in Eastern Uganda: Feasibility and Acceptability Study

Abstract

Background Lack of trained health care workers and nonadherence to national guidelines are key barriers to achieving high-quality newborn care in health care facilities in low- and middle-income countries. Traditional didactic approaches addressing these barriers fail to account for high staff turnover rates and result in temporary behavior change. NoviGuide, a clinical decision support software designed to standardize neonatal care through point-of-care assessments, has the potential to align bedside practice to national guidelines in settings lacking subspecialty neonatal providers. Objective This study aims to determine the adaptation, adoption, feasibility, acceptability, and sustainability of NoviGuide and its impact on nurse-midwives’ knowledge in a rural hospital in eastern Uganda. Methods This mixed methods observational study was guided by the Proctor framework. Experts reviewed the clinical content of NoviGuide to ensure fidelity to Uganda guidelines. We enrolled nurses and midwives providing newborn care at Tororo District Hospital, trained them on NoviGuide use, and followed them for 12 months. We assessed adoption, feasibility, acceptability, and sustainability by analyzing NoviGuide use data, comparing it with maternity registry data and administering the System Usability Scale (SUS) and the Center for Health Care Evaluation Provider Satisfaction Questionnaire. We compared the mean knowledge assessment score at baseline, 6 months, and 12 months using a two-tailed t test. Results Five Ugandan experts suggested two minor changes to NoviGuide: the inclusion of an unsterile birth environment as an indication for empiric antibiotics and the addition of a reminder to follow-up with newborns with temperatures between 37.7°C and 37.9°C. Of the 19 nurse-midwives enrolled in February 2017, 74% (n=14) completed the follow-up in March 2018. The participants entered a total of 1705 assessments of varying newborn characteristics into NoviGuide throughout the day, evening, and night nursing shifts. The SUS score at the end of the study was very high (93.5, above the average of 68). Participants had a positive perception about NoviGuide, reporting that NoviGuide saved time (mean 5, SD 0) and prevented mistakes (mean 5, SD 0), and that they felt more confident in taking care of newborns when they used NoviGuide (mean 5, SD 0). Participants were highly satisfied with NoviGuide (mean 4.86, SD 0.36), although they lacked medical supplies and materials needed to follow NoviGuide recommendations (mean 3.3, SD 1.22). The participants’ knowledge scores improved by a mean change of 3.7 (95% CI 2.6-4.8) at 6 months and 6.7 (95% CI 4.6-8.2) at 12 months (P<.001). Conclusions NoviGuide was easily adapted to the Uganda guidelines. Nurse-midwives used NoviGuide frequently and reported high levels of satisfaction despite challenges with medical supplies and high staff turnover. NoviGuide improved knowledge and confidence in newborn care without in-person didactic training. NoviGuide use has the potential to scale up quality newborn care by facilitating adherence to national guidelines.

External validation of a mobile clinical decision support system for diarrhea etiology prediction in children: A multicenter study in Bangladesh and Mali

“…Mobile CDSSs have been successfully used to improve hypertension control in India, and have been developed for neonatal care in Ghana, Kenya, and Uganda. [34][35][36][37][38][39] In Bangladesh, electronic CDSSs have also been shown to improve WHO diarrhea guideline adherence including reducing non-indicated antibiotic use by 28.5% in children under five. 15 While prior studies of CDSS targeting antibiotic use have focused on improving adherence to guidelines, our prediction tool provides the clinician with an estimation of viral diarrhea etiology.…”

“…While a lack of research persists regarding CDSSs in LMICs, their use has risen recently due to the increasingly ubiquitous use of smartphones globally. Mobile CDSSs have been successfully used to improve hypertension control in India, and have been developed for neonatal care in Ghana, Kenya, and Uganda Watson et al, 2019 ; Anchala et al, 2015 ; Muhindo et al, 2021 ; Bucher et al, 2021 ; Amoakoh et al, 2017 ; Bilal et al, 2018 . In Bangladesh, electronic CDSSs have also been shown to improve WHO diarrhea guideline adherence including reducing non-indicated antibiotic use by 28.5% in children under five Khan et al, 2020 .…”

External Validation of a Mobile Clinical Decision Support System for Diarrhea Etiology Prediction in Children: A Multicenter Study in Bangladesh and Mali

“…Mobile CDSSs have been successfully used to improve hypertension control in India, and have been developed for neonatal care in Ghana, Kenya, and Uganda. [32][33][34][35][36][37] In Bangladesh, electronic CDSSs have also been shown to improve WHO diarrhea guideline adherence including reducing non-indicated antibiotic use by 28.5% in children under five. 14 While prior studies of CDSS targeting antibiotic use have focused on improving adherence to guidelines, our prediction tool provides the clinician with an estimation of etiology.…”

Development and implementation experience of a learning healthcare system for facility based newborn care in low resource settings: The Neotree

“…This compares favourably with other digital systems, for example, a national review of UK Emergency Department Electronic Health Records reported a median SUS of 53 47 and is similar to a digital clinical decision support tool piloted in Uganda, mean SUS 93.5, n = 12. 21 In 2018 Neotree-beta was implemented in Sally Mugabe Central Hospital in Zimbabwe (annual delivery rate ~12 000) as a Quality Improvement tool for neonatal sepsis. 42 Discharge data capture and laboratory data capture functions were added.…”