A cross-sector approach to explore socio-ecological associations with treatment engagement behaviours in Northern Ghana.

Autor: Tuck C; Division of Population Health, Sheffield Centre for Health and Related Research, School of Medicine and Population Health, University of Sheffield, Sheffield, UK. Electronic address: cztuck1@sheffield.ac.uk., Gray L; Division of Population Health, Sheffield Centre for Health and Related Research, School of Medicine and Population Health, University of Sheffield, Sheffield, UK., Suraj H; Tamale Teaching Hospital, Tamale, Ghana., Iddrisu AT; Tamale Teaching Hospital, Tamale, Ghana., Abane TR; Tamale Teaching Hospital, Tamale, Ghana., Aryeetey R; School of Public Health, University of Ghana, Accra, Ghana., Baba BA; Ghana Health Service, Northern Regional Health Directorate, Tamale, Ghana., Akparibo R; Division of Population Health, Sheffield Centre for Health and Related Research, School of Medicine and Population Health, University of Sheffield, Sheffield, UK., Cooper R; Division of Population Health, Sheffield Centre for Health and Related Research, School of Medicine and Population Health, University of Sheffield, Sheffield, UK.
Jazyk: angličtina
Zdroj: Journal of cancer policy [J Cancer Policy] 2024 Sep; Vol. 41, pp. 100497. Date of Electronic Publication: 2024 Jul 25.
DOI: 10.1016/j.jcpo.2024.100497
Abstrakt: Background: Cancer presents a growing global burden, not least in African countries such as Ghana where high cancer treatment dropouts has been identified due to numerous social, cultural and financial reasons. There is little understanding regarding patterns of treatment access behaviour, especially in Northern Ghana, which this study was designed to explore.
Methods: Through cross-sector collaboration, we extracted and clinically validated cancer patient records available in the Tamale Teaching Hospital. These were analysed descriptively and through multi-variate logistic regression. A treatment mapping process was also applied to highlight challenges in data collection. Multiple imputation with chained equations was conducted for high levels of missing data. Sensitivity analysis was applied to assess the impact of missing data.
Results: Treatment drop-out was high even when uncertainty due to missing data was accounted for, and only 27 % of patients completely engaged with treatment. High drop-out was found for all cancers including those covered by the Ghana National Health Insurance scheme. Multi-variate logistic regression revealed that social, health condition and systemic factors influence treatment engagement until completion. High missing data was observed for liver, ovarian, colorectal, gastric, bladder, oesophageal and head and neck and skin cancers, and soft tissue sarcomas, which limited model fitting.
Conclusion: Treatment drop-out is a critical issue in Northern Ghana. There was high missing data due to the dynamic, complex and decentralised treatment pathway. Future studies are needed to understand the complex challenges in data recording.
Policy Summary: Treatment drop out is a pertinent issue that policy makers should look to address. Further discussion with stakeholders involved in cancer treatment and data collection is required to better understand challenges to routine data collection in the local setting. This will allow policy to be designed to cater for the impact of multiple intersecting health and social factors on treatment completion.
Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)
Databáze: MEDLINE
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