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Investigating barriers to adherence to antimalarial prescribing guidelines in public healthcare facilities in Arba Minch, South Ethiopia: A qualitative study

by Abate Atimut Dereje, Dereje Geleta, Tadesse Menjetta, Abinet Takele, Susana Vaz Nery, Techalew Shimelis

Background

Early diagnosis and prompt treatment of malaria cases are a crucial component of curative and preventive interventions. There have been reports of healthcare workers overprescribing antimalarial agents against guidelines, but the barriers they face in adhering to the guidelines are not well studied. This study aimed to investigate barriers to adherence to guidelines in prescribing antimalarial drugs in public healthcare facilities in Arba Minch, South Ethiopia.

Method

A cross-sectional descriptive exploratory qualitative method was employed. We included ten participants from public healthcare facilities, including health centres, a hospital, a city health office, and a zonal health bureau. A key informant interview technique was used to collect data. All interviews were audio-recorded, transcribed, and analyzed. Data analysis was performed using ATLAS.ti, version 7.5 software. The results were presented thematically and narrated to support the main themes.

Results

Public healthcare facilities primarily used blood smear microscopy to test all malaria-suspected patients. However, in cases of microscopy service interruptions or when confirming negative results, rapid diagnostic tests (RDTs) were employed in some facilities. Limited availability of microscopes and reagents, and electric power interruptions hindered reliable microscopy services. Drug stock-outs, patient expectations for antimalarial drugs, self-treatment, and delayed care-seeking are barriers to adherence to malaria treatment guidelines. The main reason for non-adherence to withholding antimalarial drugs after negative tests was greater trust in clinical findings over laboratory results. Confidence in experience contributed to trust in clinical judgment, while perceived inexperience and negligence, inconsistent RDT and microscopy results, and poor-quality control assessment results undermined trust in laboratories. Despite supporting the guidelines, study participants emphasized the need for flexibility to allow empirical treatment and highlighted the lack of training and mentoring for healthcare workers.

Conclusion

To improve adherence to malaria treatment guidelines, it is essential to ensure consistent lab operations, enhance quality assurance, maintain effective communication between lab personnel and prescribers, and provide healthcare and patient education. Implementing training and mentoring programs and promoting evidence-based practices are also crucial.

Mapping fine-scale spatial risk patterns of gestational diabetes over time in Australia: a nationwide geospatial study

Por: Takele · W. W. · Lim · S. · Adhinugraha · K. · Taniar · D. · Dalli · L. L. · Boyle · J. A.
Objective

To examine the geospatial distribution of gestational diabetes mellitus (GDM) over time in Australia.

Design

An ecological study was conducted using data from the National Diabetes Services Scheme (GDM cases). Data at Statistical Area Level 2 (SA2) level, a medium-sized spatial unit, on population denominators (women who gave birth) were obtained from the Australian Bureau of Statistics. The spatiotemporal distribution of GDM was explored at the SA2 level over three periods: 2016–2017, 2018–2019 and 2020–2021. Hotspot and cluster analyses were undertaken using Getis-Ord Gi* and local Moran’s I statistics.

Setting

A nationwide study in Australia was conducted between 2016 and 2021.

Participants

Women diagnosed with GDM and those who gave birth were included.

Outcome measures

Age-standardised and crude incidence of GDM per SA2.

Results

During 2016–2021, 1 718 963 eligible women who gave birth in Australia were included. Hotspot areas of GDM were consistently observed in Victoria (Southwest and North Melbourne); Western Australia (South and Southwest Perth); Australian Capital Territory (ACT) (East and North Canberra); Queensland (North Brisbane) and New South Wales (West and Southwest Sydney and Southeast New South Wales). ACT (South Canberra), North Tasmania, Northern Territory (North Darwin) and Victoria (South East Melbourne) had new hotspot regions recorded in the last two consecutive study periods.

Conclusion

GDM incidence varies by geographical area over time, with hotspots in specific regions suggesting the need for geographically targeted policy interventions to curb the growing burden of GDM.

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