Please use this identifier to cite or link to this item: https://doi.org/10.1186/s12913-022-08940-0
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dc.titleEffects 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
dc.contributor.authorAninanya, Gifty Apiung
dc.contributor.authorWilliams, John E
dc.contributor.authorWilliams, Afua
dc.contributor.authorOtupiri, Easmon
dc.contributor.authorHoward, Natasha
dc.date.accessioned2023-03-20T08:14:49Z
dc.date.available2023-03-20T08:14:49Z
dc.date.issued2022-12-26
dc.identifier.citationAninanya, Gifty Apiung, Williams, John E, Williams, Afua, Otupiri, Easmon, Howard, Natasha (2022-12-26). 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. BMC HEALTH SERVICES RESEARCH 22 (1). ScholarBank@NUS Repository. https://doi.org/10.1186/s12913-022-08940-0
dc.identifier.issn1472-6963
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/238266
dc.description.abstractBackground: Computerized 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. Methods: We 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. Results: Interviewees 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. Conclusion: Combining 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.
dc.language.isoen
dc.publisherBMC
dc.sourceElements
dc.subjectComputerised-decision support system
dc.subjectPerformance-based incentives
dc.subjectmHealth
dc.subjectMaternal and neonatal health
dc.subjectGhana
dc.typeArticle
dc.date.updated2023-03-19T11:30:27Z
dc.contributor.departmentDEAN'S OFFICE (SSH SCH OF PUBLIC HEALTH)
dc.description.doi10.1186/s12913-022-08940-0
dc.description.sourcetitleBMC HEALTH SERVICES RESEARCH
dc.description.volume22
dc.description.issue1
dc.published.statePublished
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