Maternal and Neonatal Directed Assessment of Technologies (MANDATE): Methods and Assumptions for a Predictive Model for Maternal, Fetal, and Neonatal Mortality Interventions

Non-anaesthetist-administered ketamine for emergency caesarean section in Kenya: cost-effectiveness analysis

OBJECTIVES

Lack of anaesthesia services is a frequent barrier to emergency surgeries such as caesarean delivery in Kenya. This study aimed to estimate the survival gains and cost-effectiveness of scaling up the Every Second Matters (ESM)-Ketamine programme that trains non-anaesthetist providers to administer and monitor ketamine during emergency caesarean deliveries.

SETTING

Hospitals in Kenyan counties with low rates of caesarean delivery.

PARTICIPANTS

Patients needing emergency caesarean delivery in settings without availability of standard anaesthesia service.

INTERVENTIONS

Simulated scales up of the ESM-Ketamine programme over 5 years (2020-24) was compared with status quo.

OUTCOME MEASURES

Cost of implementing the programme and corresponding additional emergency caesarean deliveries. Maternal and fetal/neonatal deaths prevented, and corresponding life-years gained due to increased provision of emergency caesarean procedures. Cost-effectiveness was assessed by comparing the cost per life-year gained of the ESM-Ketamine programme compared with status quo.

RESULTS

Over 5 years, the expected gap in emergency caesarean deliveries was 157 000. A US$1.2 million ESM-Ketamine programme reduced this gap by 28 700, averting by 316 maternal and 4736 fetal deaths and generating 331 000 total life-years gained. Cost-effectiveness of scaling up the ESM-Ketamine programme was US$44 per life-year gained in the base case and US$251 in the most pessimistic scenario-a very good value for Kenya at less than 20% of per capita GDP per life-year gained.

CONCLUSION

In areas of Kenya with significant underprovision of emergency caesarean delivery due to a lack of availability of traditional anaesthesia, an ESM-Ketamine programme is likely to enable a substantial number of life-saving surgeries at reasonable cost.

Evaluating WHO-Recommended Interventions for Preterm Birth: A Mathematical Model of the Potential Reduction of Preterm Mortality in Sub-Saharan Africa

BACKGROUND

Preterm birth, a leading cause of neonatal mortality, has the highest burden in low-income countries. In 2015, the World Health Organization (WHO) published recommendations for interventions to improve preterm outcomes. Our analysis uses the Maternal and Neonatal Directed Assessment of Technology (MANDATE) model to evaluate the potential effects that WHO-recommended interventions could have had on preterm mortality in sub-Saharan Africa in 2015.

METHODS

We modeled preterm birth subconditions causing mortality (respiratory distress syndrome, intraventricular hemorrhage, necrotizing enterocolitis, sepsis, birth asphyxia, and low birth weight). For each subcondition, models were populated with estimates of WHO-recommended intervention prevalence, case fatality, coverage, and efficacy. Various scenarios modeled improved coverage of single and combined interventions compared with baseline.

RESULTS

In 2015, approximately 500,000 neonatal deaths due to preterm birth occurred in sub-Saharan Africa. Single interventions with the greatest impact on preterm mortality included oxygen/continuous positive airway pressure (44,000 lives saved), cord care (38,500 lives saved), and breastfeeding (30,200 lives saved). Combined with improved diagnosis/transfer to a hospital, the impact of interventions showed greater reductions in mortality (oxygen/continuous positive airway pressure, 134,100 lives saved; antibiotics, 28,600 lives saved). Combined interventions had the greatest impact. Together, hospital delivery with comprehensive care for respiratory distress syndrome saved 190,600 lives, and comprehensive thermal care, breastfeeding, and prevention/treatment for sepsis saved 94,400 lives.

CONCLUSION

In 2015, WHO-recommended interventions could have saved the lives of nearly 300,000 infants born preterm in sub-Saharan Africa. Combined interventions are necessary to maximize impact. Mathematical models such as MANDATE can estimate effects on health outcomes to allow health officials to prioritize implementation strategies.

Modeling Outputs Can Be Valuable When Uncertainty Is Appropriately Acknowledged, but Misleading When Not

While modeling approaches seek to draw on the best available evidence to project health impact of improved coverage of specific interventions, uncertainty around the outputs often remains. When the modeling estimates are used for advocacy, these uncertainties should be communicated to policy makers clearly and openly to ensure they understand the model's limits and to maintain their confidence in the process.