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1.  Association between the use of biomass fuels on respiratory health of workers in food catering enterprises in Nairobi Kenya 
Indoor air pollution from biomass fuel use has been found to be responsible for more than 1.6 million annual deaths and 2.7% of the global burden of disease. This makes it the second biggest environmental contributor to ill health, behind unsafe water and sanitation.
The main objective of this study was to investigate if there was any association between use of bio-fuels in food catering enterprises and respiratory health of the workers. A cross-sectional design was employed, and data collected using Qualitative and quantitative techniques.
The study found significantly higher prevalence of respiratory health outcomes among respondents in enterprises using biomass fuels compared to those using processed fuels. Biomass fuels are thus a major public health threat to workers in this sub-sector, and urgent intervention is required.
The study recommends a switch from biomass fuels to processed fuels to protect the health of the workers.
PMCID: PMC3725321  PMID: 23898361
Indoor air pollution; biomass fuels; health; respiratory; workers
2.  Two-tier charging in Maputo Central Hospital: Costs, revenues and effects on equity of access to hospital services 
Special services within public hospitals are becoming increasingly common in low and middle income countries with the stated objective of providing higher comfort services to affluent customers and generating resources for under funded hospitals. In the present study expenditures, outputs and costs are analysed for the Maputo Central Hospital and its Special Clinic with the objective of identifying net resource flows between a system operating two-tier charging, and, ultimately, understanding whether public hospitals can somehow benefit from running Special Clinic operations.
A combination of step-down and bottom-up costing strategies were used to calculate recurrent as well as capital expenses, apportion them to identified cost centres and link costs to selected output measures.
The results show that cost differences between main hospital and clinic are marked and significant, with the Special Clinic's cost per patient and cost per outpatient visit respectively over four times and over thirteen times their equivalent in the main hospital.
While the main hospital cost structure appeared in line with those from similar studies, salary expenditures were found to drive costs in the Special Clinic (73% of total), where capital and drug costs were surprisingly low (2 and 4% respectively). We attributed low capital and drug costs to underestimation by our study owing to difficulties in attributing the use of shared resources and to the Special Clinic's outsourcing policy. The large staff expenditure would be explained by higher physician time commitment, economic rents and subsidies to hospital staff. On the whole it was observed that: (a) the flow of capital and human resources was not fully captured by the financial systems in place and stayed largely unaccounted for; (b) because of the little consideration given to capital costs, the main hospital is more likely to be subsidising its Special Clinic operations, rather than the other way around.
We conclude that the observed lack of transparency may create scope for an inequitable cross subsidy of private customers by public resources.
PMCID: PMC3127984  PMID: 21635752
3.  Health sector reforms and human resources for health in Uganda and Bangladesh: mechanisms of effect 
Despite the expanding literature on how reforms may affect health workers and which reactions they may provoke, little research has been conducted on the mechanisms of effect through which health sector reforms either promote or discourage health worker performance. This paper seeks to trace these mechanisms and examines the contextual framework of reform objectives in Uganda and Bangladesh, and health workers' responses to the changes in their working environments by taking a 'realistic evaluation' approach.
The study findings were generated by triangulating both qualitative and quantitative methods of data collection and analysis among policy technocrats, health managers and groups of health providers. Quantitative surveys were conducted with over 700 individual health workers in both Bangladesh and Uganda and supplemented with qualitative data obtained from focus group discussions and key interviews with professional cadres, health managers and key institutions involved in the design, implementation and evaluation of the reforms of interest.
The reforms in both countries affected the workforce through various mechanisms. In Bangladesh, the effects of the unification efforts resulted in a power struggle and general mistrust between the two former workforce tracts, family planning and health. However positive effects of the reforms were felt regarding the changes in payment schemes. Ugandan findings show how the workforce responded to a strong and rapidly implemented system of decentralisation where the power of new local authorities was influenced by resource constraints and nepotism in recruitment. On the other hand, closer ties to local authorities provided the opportunity to gain insight into the operational constraints originating from higher levels that health staff were dealing with.
Findings from the study suggest that a) reform planners should use the proposed dynamic responses model to help design reform objectives that encourage positive responses among health workers b) the role of context has been underestimated and it is necessary to address broader systemic problems before initiating reform processes, c) reform programs need to incorporate active implementation research systems to learn the contextual dynamics and responses as well as have inbuilt program capacity for corrective measures d) health workers are key stakeholders in any reform process and should participate at all stages and e) some effects of reforms on the health workforce operate indirectly through levels of satisfaction voiced by communities utilising the services.
PMCID: PMC1800303  PMID: 17270042

Results 1-3 (3)