Leveraging e-health for enhanced cancer care service models in middle-income contexts: Qualitative insights from oncology care providers

Author:

Melhem Samar J12ORCID,Nabhani-Gebara Shereen1,Kayyali Reem1

Affiliation:

1. Department of Pharmacy, School of Life Sciences, Pharmacy and Chemistry, Kingston University London, Kingston upon Thames, Surrey, UK

2. Department of Biopharmaceutics and Clinical Pharmacy, School of Pharmacy, The University of Jordan, Amman, Jordan

Abstract

Background Global cancer research has predominantly favoured high-income countries (HICs). The unique challenges in low- and middle-income countries (LMICs) demand tailored research approaches, accentuated further by the disparities highlighted during the COVID-19 pandemic. Aim and objectives This research endeavoured to dissect the intricacies of cancer care in LMICs, with Jordan serving as a case study. Specifically, the study aimed to conduct an in-depth analysis of the prevailing cancer care model and assess the transformative potential of eHealth technologies in bolstering cancer care delivery. Methods Utilising a qualitative methodology, in-depth semi-structured interviews with oncology healthcare professionals were executed. Data underwent inductive thematic analysis as per Braun and Clarke's guidelines. Results From the analysed data, two dominant themes surfaced. Firstly, “The current state of cancer care delivery” was subdivided into three distinct subthemes. Secondly, “Opportunities for enhanced care delivery via e-health” underscored the urgency of digital health reforms. Conclusion The need to restrategise cancer care in LMICs is highlighted by this study, using the Jordanian healthcare context as a reference. The transformative potential of e-health initiatives has been illustrated. However, the relevance of this study might be limited by its region-specific approach. Future research is deemed essential for deeper exploration into the integration of digital health within traditional oncology settings across diverse LMICs, emphasising the significance of telemedicine in digital-assisted care delivery reforms.

Publisher

SAGE Publications

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Optimizing Cancer Patient Classification Forecasting With Bayesian Pattern Recognition;International Journal of Healthcare Information Systems and Informatics;2024-08-14

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