Acceptability and uptake of an electronic decision-making tool to support the implementation of IMCI in primary healthcare facilities in KwaZulu-Natal, South Africa

Jensen, Cecilie; McKerrow, Neil; Wills, Gabrielle

doi:10.1080/20469047.2019.1697573

Cited by 19 publications

(23 citation statements)

References 13 publications

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“…The nurse-midwives used NoviGuide across a range of clinical scenarios, reported high levels of satisfaction with the software, and reported that it significantly improved their knowledge of newborn care. This study adds to the growing evidence that CDS software designed for facility-based health care workers delivering complex inpatient care can increase the use of national clinical guidelines in LMICs [32][33][34][35].…”

Section: Principal Findingsmentioning

confidence: 89%

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

Muhindo

Bress

Kalanda

et al. 2021

JMIR Mhealth Uhealth

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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.

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Section: Principal Findingsmentioning

confidence: 89%

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

Muhindo

Bress

Kalanda

et al. 2021

JMIR Mhealth Uhealth

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“…During the 5 quarterly data collection periods, the majority of eIMCI facilities had a functional computer and a moderate caseload of children under 5 years. In keeping with what was seen during the pilot implementation, the ongoing use of eIMCI was modest and varied considerably between facilities and periods [ 16 ]. The uptake of electronic IMCI algorithms also waned over time in Tanzania where healthcare workers listed technical challenges, the length of consultations, drug supply, and staffing and workload problems as key barriers to their use [ 20 ].…”

Section: Discussionmentioning

confidence: 68%

“…With this in mind, the eIMCI capacitation model adopted a standardized approach to training, mentorship and supervision. However, despite clear training participant selection criteria and ongoing coordination with the facility managers, the post-training deployment of nurse clinicians was inferior even to that seen during the pilot implementation [ 16 ], with nearly 40% of nurses unable to practice eIMCI at their facility after the course. Sub-optimal allocation is a well-known barrier to building staff competence in our context, rendering mentoring and supervisory support difficult and necessitating continuous capacitation of new staff to sustain programme implementation [ 8 , 11 ].…”

Section: Discussionmentioning

confidence: 99%

“…The eIMCI software development has been described briefly in a previous acceptability evaluation [ 16 ]. From inception, the project was conducted in collaboration with the provincial Department of Health (DoH) with the premise of roll-out within existing DoH information technology (IT) infrastructure.…”

Section: Methodsmentioning

confidence: 99%

“…The uptake of eIMCI was most strongly related to the nurses’ computer literacy levels. Common themes in the maternal interviews included improved comprehensiveness, correctness and efficiency of service [ 16 ]. A phase 2 implementation has subsequently been carried out with scale-up to additional sites within the same health district.…”

Section: Introductionmentioning

confidence: 99%

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The feasibility and ongoing use of electronic decision support to strengthen the implementation of IMCI in KwaZulu-Natal, South Africa

Jensen

McKerrow

2022

BMC Pediatr

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Background Continued efforts are required to reduce preventable child deaths. User-friendly Integrated Management of Childhood Illness (IMCI) implementation tools and supervision systems are needed to strengthen the quality of child health services in South Africa. A 2018 pilot implementation of electronic IMCI case management algorithms in KwaZulu-Natal demonstrated good uptake and acceptance at primary care clinics. We aimed to investigate whether ongoing electronic IMCI implementation is feasible within the existing Department of Health infrastructure and resources. Methods In a mixed methods descriptive study, the electronic IMCI (eIMCI) implementation was extended to 22 health facilities in uMgungundlovu district from November 2019 to February 2021. Training, mentoring, supervision and IT support were provided by a dedicated project team. Programme use was tracked, quarterly assessments of the service delivery platform were undertaken and in-depth interviews were conducted with facility managers. Results From December 2019 – January 2021, 9 684 eIMCI records were completed across 20 facilities, with a median uptake of 29 records per clinic per month and a mean (range) proportion of child consultations using eIMCI of 15% (1–46%). The local COVID-19-related movement restrictions and epidemic peaks coincided with declines in the monthly eIMCI uptake. Substantial inter- and intra-facility variations in use were observed, with the use being positively associated with the allocation of an eIMCI trained nurse (p < 0.001) and the clinician workload (p = 0.032). Conclusion The ongoing eIMCI uptake was sporadic and the implementation undermined by barriers such as low post-training deployment of nurses; poor capacity in the DoH for IT support; and COVID-19-related disruptions in service delivery. Scaling eIMCI in South Africa would rely on resolving these challenges.

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“Following the data”: Perceptions of and willingness to use clinical decision support tools to inform HIV care among Haitian clinicians

Secor,

Justafort,

Torrilus

et al. 2024

Health Policy and Technology

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Acceptability and uptake of an electronic decision-making tool to support the implementation of IMCI in primary healthcare facilities in KwaZulu-Natal, South Africa

Cited by 19 publications

References 13 publications

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

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

The feasibility and ongoing use of electronic decision support to strengthen the implementation of IMCI in KwaZulu-Natal, South Africa

“Following the data”: Perceptions of and willingness to use clinical decision support tools to inform HIV care among Haitian clinicians

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