Are there decision support tools that might strengthen the health system for perinatal care in South African district hospitals? A review of the literature

Is Universal Health Coverage Affordable? Estimated Costs and Fiscal Space Analysis for the Ethiopian Essential Health Services Package

Estimating the required resources for implementing an essential health services package (EHSP) is vital to examine its feasibility and affordability. This study aimed to estimate the financial resources required to implement the Ethiopian EHSP from 2020 to 2030. Furthermore, we explored potential alternatives to increase the fiscal space for health in Ethiopia. We used the OneHealth Tool (OHT) to estimate the costs of expanding the EHSP service provision in the public sector in Ethiopia. Combinations of ingredient-based bottom-up and program-based summary costing approaches were applied. We predicted the fiscal space using assumptions for economic growth, government resource allocations to health, external aid for health, the magnitude of out-of-pocket expenditure, and other private health expenditures as critical factors affecting available resources devoted to health. All costs were valued using 2020 US dollars (USD). To implement the EHSP, 13.0 billion USD (per capita: 94 USD) would be required in 2030. The largest (50-70%) share of estimated costs was for medicines, commodities, and supplies, followed by human resources costs (10-17%). However, the expected available resources based on a business-as-usual fiscal space estimate would be 63 USD per capita for the same year. Therefore, the gap as a percentage of the required resources would be 33% in 2030. The resources needed to implement the EHSP would increase steadily over the projection period due mainly to increases in service coverage targets over time. Allocating gains from economic growth to increase the total government health expenditure could partly address the gap.

Preceptorship in nursing-midwifery: a training-intervention in health work

OBJECTIVES

to analyze how certified nurse-midwives identify preceptorship in a nursing-midwifery enhancing course conducted by the Universidade Federal Fluminense as a possibility of training to promote institutional support and intervention.

METHODS

a descriptive, exploratory research with qualitative approach. Six certified nurse-midwife preceptors from the Nursing-Midwifery Enhancing Course participated in the study in 2019. Two public maternity hospitals in Rio de Janeiro were settings of the research. Individual interview and thematic content analysis were used to collect and analyze data.

RESULTS

exchange of knowledge between preceptors and trainees encouraged learning and reflection stemming from delivery and birth, contributing to expansion of autonomy and professional leading role in training, health care, and management.

FINAL CONSIDERATIONS

collective meetings that promote work analysis and value the performance of certified nurse-midwives have led to intervention processes and institutional support in maternity hospitals in Rio de Janeiro, Brazil.

Implementing electronic decision-support tools to strengthen healthcare network data-driven decision-making

BACKGROUND

Ministries of health in low- and middle-income countries often lack timely quality data for data-driven decision making in healthcare networks. We describe the design and implementation of decision-support electronic tools by the Ministry of Health of the State of Chiapas, in Mexico, as part of Salud Mesoamerica Initiative.

METHODS

Three electronic decision-support tools were designed through an iterative process focused on streamlined implementation: 1) to collect and report health facility data at health facilities; 2) to compile and analyze data at health district and central level; and, 3) to support stratified sampling of health facilities. Data was collected for five composite indicators measuring availability of equipment, medicines, and supplies for maternal and child health. Quality Assurance Teams collected data, evaluated results and supported quality improvement. Data was also analyzed at the central level and health districts for decision-making.

RESULTS

Data from 300 health facilities in four health districts was collected and analyzed (November 2014-June 2015). The first wave revealed gaps on availability of equipment and supplies in more than half of health facilities. Electronic tools provided the ministry of health officers new ways to visualize data, identify patterns and make hypothesis on root-causes. Between the first and second measurement, the number of missing items decreased, and actions performed by quality improvement teams became more proactive. In the final measurement, 89.7-100% of all health facilities achieved all the required items for each indicator.

CONCLUSIONS

Our experience could help guide others seeking to implement electronic decision-support tools in low- and middle-income countries. Electronic decision-support tools supported data-driven decision-making by identifying gaps on heatmaps and graphs at the health facility, subdistrict, district or state level. Through a rapid improvement process, the Ministry of Health met targets of externally verified indicators. Using available information technology resources facilitated prompt implementation and adoption of technology.