Supporting the revision of the health benefits package in Uganda: A constrained optimisation approach.

This study demonstrates how the linear constrained optimization approach can be used to design a health benefits package (HBP) which maximises the net disability adjusted life years (DALYs) averted given the health system constraints faced by a country, and how the approach can help assess the marginal value of relaxing health system constraints. In the analysis performed for Uganda, 45 interventions were included in the HBP in the base scenario, resulting in a total of 26.7 million net DALYs averted. When task shifting of pharmacists' and nutrition officers' tasks to nurses is allowed, 73 interventions were included in the HBP resulting in a total of 32 million net DALYs averted (a 20% increase). Further, investing only $58 towards hiring additional nutrition officers' time could avert one net DALY; this increased to $60 and $64 for pharmacists and nurses respectively, and $100,000 for expanding the consumable budget, since human resources present the main constraint to the system.

A framework to support the integration of priority setting in the preparedness, alert, control and evaluation stages of a disease pandemic.

The COVID-19 pandemic, where the need-resource gap has necessitated decision makers in some contexts to ration access to life-saving interventions, has demonstrated the critical need for systematic and fair priority setting and resource allocation mechanisms. Disease outbreaks are becoming increasingly common and priority setting lessons from previous disease outbreaks could be better harnessed to inform decision making and planning for future disease outbreaks. The purpose of this paper is to discuss how priority setting and resource allocation could, ideally, be integrated into the WHO pandemic planning and preparedness framework and used to inform the COVID-19 pandemic recovery plans and plans for future outbreaks. Priority setting and resource allocation during disease outbreaks tend to evoke a process similar to the 'rule of rescue'. This results in inefficient and unfair resource allocation, negative effects on health and non-health programs and increased health inequities. Integrating priority setting and resource allocation activities throughout the four phases of the WHO emergency preparedness framework could ensure that priority setting during health emergencies is systematic, evidence informed and fair.

Determinants of safety climate at primary care level in Ghana, Malawi and Uganda: a cross-sectional study across 138 selected primary healthcare facilities.

BACKGROUND: Safety climate is an essential component of achieving Universal Health Coverage, with several organisational, unit or team-level, and individual health worker factors identified as influencing safety climate. Few studies however, have investigated how these factors contribute to safety climate within health care settings in low- and middle-income countries (LMICs). The current study examines the relationship between key organisational, unit and individual-level factors and safety climate across primary health care centres in Ghana, Malawi and Uganda. METHODS: A cross-sectional, self-administered survey was conducted across 138 primary health care facilities in nine districts across Uganda, Ghana and Malawi. In total, 760 primary health workers completed the questionnaire. The relationships between individual (sex, job satisfaction), unit (teamwork climate, supportive supervision), organisational-level (district managerial support) and safety climate were tested using structural equation modelling (SEM) procedures. Post hoc analyses were also carried out to explore these relationships within each country. RESULTS: Our model including all countries explained 55% of the variance in safety climate. In this model, safety climate was most strongly associated with teamwork (ß = 0.56, p < 0.001), supportive supervision (ß = 0.34, p < 0.001), and district managerial support (ß = 0.29, p < 0.001). In Ghana, safety climate was positively associated with job satisfaction (ß = 0.30, p < 0.05), teamwork (ß = 0.46, p < 0.001), and supportive supervision (ß = 0.21, p < 0.05), whereby the model explained 43% of the variance in safety climate. In Uganda, the total variance explained by the model was 64%, with teamwork (ß = 0.56, p < 0.001), supportive supervision (ß = 0.43, p < 0.001), and perceived district managerial support (ß = 0.35, p < 0.001) all found to be positively associated with climate. In Malawi, the total variance explained by the model was 63%, with teamwork (ß = 0.39, p = 0.005) and supportive supervision (ß = 0.27, p = 0.023) significantly and positively associated with safety climate. DISCUSSION/CONCLUSIONS: Our findings highlight the importance of unit-level factors-and in specific, teamwork and supportive supervision-as particularly important contributors to perceptions of safety climate among primary health workers in LMICs. Implications for practice are discussed.

Evaluation of a health systems knowledge translation network for Africa (KTNET): a study protocol.

BACKGROUND: Despite the increasing investment in health-related research in Sub-Saharan Africa, a large gulf remains between what is known and what is practiced in health systems. Knowledge translation programs aim to ensure that a wide range of stakeholders are aware of and use research evidence to inform their health and health-care decision-making. The purpose of this study is to provide insight into the impacts on capacity building for knowledge translation and knowledge translation activities by a coalition of eight research groups in Africa. METHODS/DESIGN: We will use a mixed methods approach. Key informant interviews and document reviews will be employed to evaluate changes in knowledge translation capacity and to evaluate the effects of knowledge translation on potential users of research. Quarterly teleconferences will be done to evaluate the impacts of knowledge translation activities on users of research. Using website tracking, we will be able to explore the influence of knowledge translation networking and dynamics of the knowledge translation network. DISCUSSION: We have adopted the dynamic knowledge transfer model and the Landry framework to come up with a framework for this study so as to explore the capacity of producers and users of research to generate, disseminate, and use research findings, while highlighting their strengths and weaknesses. This information will be useful for guiding implementers that seek to build capacity on knowledge translation so as to promote the utilization of research findings for informing programs, practice, and policy.