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- Ramani-Chander, Anusha, et al.
(author)
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Applying systems thinking to identify enablers and challenges to scale-up interventions for hypertension and diabetes in low-income and middle-income countries : protocol for a longitudinal mixed-methods study
- 2022
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In: BMJ Open. - : BMJ Publishing Group Ltd. - 2044-6055. ; 12
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Journal article (peer-reviewed)abstract
- Introduction: There is an urgent need to reduce the burden of non-communicable diseases (NCDs), particularly in low-and middle-income countries, where the greatest burden lies. Yet, there is little research concerning the specific issues involved in scaling up NCD interventions targeting low-resource settings. We propose to examine this gap in up to 27 collaborative projects, which were funded by the Global Alliance for Chronic Diseases (GACD) 2019 Scale Up Call, reflecting a total funding investment of approximately US$50 million. These projects represent diverse countries, contexts and adopt varied approaches and study designs to scale-up complex, evidence-based interventions to improve hypertension and diabetes outcomes. A systematic inquiry of these projects will provide necessary scientific insights into the enablers and challenges in the scale up of complex NCD interventions.Methods and analysis: We will apply systems thinking (a holistic approach to analyse the inter-relationship between constituent parts of scaleup interventions and the context in which the interventions are implemented) and adopt a longitudinal mixed-methods study design to explore the planning and early implementation phases of scale up projects. Data will be gathered at three time periods, namely, at planning (T-P), initiation of implementation (T-0) and 1-year postinitiation (T-1). We will extract project-related data from secondary documents at T-P and conduct multistakeholder qualitative interviews to gather data at T-0 and T-1. We will undertake descriptive statistical analysis of T-P data and analyse T-0 and T-1 data using inductive thematic coding. The data extraction tool and interview guides were developed based on a literature review of scale-up frameworks.Ethics and dissemination: The current protocol was approved by the Monash University Human Research Ethics Committee (HREC number 23482). Informed consent will be obtained from all participants. The study findings will be disseminated through peer-reviewed publications and more broadly through the GACD network.
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| 2. |
- Zhao, Yang, et al.
(author)
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Medical costs and out-of-pocket expenditures associated with multimorbidity in China: Quantile regression analysis
- 2021
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In: BMJ Global Health. - 2059-7908. ; 6
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Journal article (peer-reviewed)abstract
- Objective Multimorbidity is a growing challenge in low-income and middle-income countries. This study investigates the effects of multimorbidity on annual medical costs and the out-of-pocket expenditures (OOPEs) along the cost distribution. Methods Data from the nationally representative China Health and Retirement Longitudinal Study (CHARLS 2015), including 10 592 participants aged ≥45 years and 15 physical and mental chronic diseases, were used for this nationally representative cross-sectional study. Quantile multivariable regressions were employed to understand variations in the association of chronic disease multimorbidity with medical cost and OOPE. Results Overall, 69.5% of middle-Aged and elderly Chinese had multimorbidity in 2015. Increased number of chronic diseases was significantly associated with greater health expenditures across every cost quantile groups. The effect of chronic diseases on total medical cost was found to be larger among the upper tail than those in the lower tail of the cost distributions (coefficients 12, 95% CI 6 to 17 for 10th percentile; coefficients 296, 95% CI 71 to 522 for 90th percentile). Annual OOPE also increased with chronic diseases from the 10th percentile to the 90th percentile. Multimorbidity had larger effects on OOPE and was more pronounced at the upper tail of the health expenditure distribution (regression coefficients of 8 and 84 at the 10th percentile and 75th percentile, respectively). Conclusion Multimorbidity is associated with escalating healthcare costs in China. Further research is required to understand the impact of multimorbidity across different population groups.
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