ArticleBMC health services research2022
Effects of computerized decision support on maternal and neonatal health-worker performance in the context of combined implementation with performance-based incentivisation in Upper East Region, Ghana: a qualitative study of professional perspectives.
Article in BMC health services research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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Who cites it
5 citing papers in PubMed, 7 citations in OpenAlex.
- Integrated Digital Decision-Making Systems in Maternal Nursing and Maternity Care: A Scoping Review.Journal of multidisciplinary healthcare · 2026Review
- A Novel Approach to Assessing the Potential of Electronic Decision Support Systems to Improve the Quality of Antenatal Care in Nepal.Global health, science and practice · 2025Article
- Empowering Community Health Workers With Scripted Medicine: Design Science Research Study.JMIR human factors · 2025Article
- The role of mHealth intervention to improve maternal and child health: A provider-based qualitative study in Southern Ethiopia.PloS one · 2024Article
- Advances in Clinical Decision Support Systems: Contributions from the 2022 Literature.Yearbook of medical informatics · 2023Article
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Authors and funding
5 authors at 5 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundComputerized decision support systems (CDSS) and performance-based incentives (PBIs) can improve health-worker performance. However, there is minimal evidence on the combined effects of these interventions or perceived effects among maternal and child healthcare providers in low-resource settings. We thus aimed to explore the perceptions of maternal and child healthcare providers of CDSS support in the context of a combined CDSS-PBI intervention on performance in twelve primary care facilities in Ghana's Upper East Region.
methodsWe conducted a qualitative study drawing on semi-structured key informant interviews with 24 nurses and midwives, 12 health facility managers, and 6 district-level staff familiar with the intervention. We analysed data thematically using deductive and inductive coding in NVivo 10 software.
resultsInterviewees suggested the combined CDSS-PBI intervention improved their performance, through enhancing knowledge of maternal health issues, facilitating diagnoses and prescribing, prompting actions for complications, and improving management. Some interviewees reported improved morbidity and mortality. However, challenges described in patient care included CDSS software inflexibility (e.g. requiring administration of only one intermittent preventive malaria treatment to pregnant women), faulty electronic partograph leading to unnecessary referrals, increased workload for nurses and midwives who still had to complete facility forms, and power fluctuations affecting software.
conclusionCombining CDSS and PBI interventions has potential to improve maternal and child healthcare provision in low-income settings. However, user perspectives and context must be considered, along with allowance for revisions, when designing and implementing CDSS and PBIs interventions.
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