Several reviews have consolidated the evidence on the impact of living near an urban green space on improving health and education outcomes and reducing mortality. However, there is limited evidence on the effectiveness or cost-effectiveness of specific improvements to these urban green spaces, which would help decision-makers make informed decisions on how to invest in urban green spaces. Therefore, this review synthesizes the impact of more specific changes to, or investments in, urban green spaces on health and education outcomes, synthesizes the cost-effectiveness of these interventions, and critiques the applicability of the evidence for an economic evaluation. We find that interventions targeted towards improving play areas or fitness equipment tended to have mostly positive impacts on physical activity, while interventions on improving walking path, or the overall greenery showed a more mixed impact on physical activity. There were only two studies on the impact of changes to urban green spaces on mental health, with only one finding a positive association of the intervention with depression, and there were no studies measuring the impact of changes to urban green spaces and educational outcomes. From a cost-effectiveness perspective, we find that typically very small improvements are required to make the interventions a cost-effective policy choice; however, we found several limitations with using the existing evidence to estimate the cost-effectiveness of the intervention. Overall, we found that most of the evidence does suggest that improvements to urban green spaces can lead to improvements in physical activity, but further research is needed on the impact on mental health and educational outcomes. Furthermore, additional evidence with longer time horizons, multi-sectoral benefits, distributional outcomes, and more consistent outcome measures would assist in informing cost-effectiveness and may ultimately lead to improved decision-making around investments for urban green spaces in specific contexts.

Background: The Federal Ministry of National Health Services, Regulations and Coordination (MNHSR&C) in Pakistan has committed to progress towards Universal Health Coverage (UHC) by 2030 by providing an essential package for health services (EPHS). Starting in 2019, the Disease Control Priorities 3 (DCP3) evidence framework was used to guide the development of Pakistan’s EPHS. In this paper, we describe the methods and results of a rapid costing approach used to inform the EPHS design process. Methods: A total of 167 unit costs were calculated through a context-specific, normative, ingredients-based, bottom-up economic costing approach. Costs were constructed by determining resource use from descriptions provided by MNHSR&C and validated by technical experts. Price data from publicly available sources were used. Deterministic univariate sensitivity analyses were carried out. Results: Unit costs ranged from 2019 US$ 0.27 to 2019 US$ 1,478. Interventions in the cancer package of services had the highest average cost (2019 US$ 837) while interventions in the environmental package of services had the lowest (2019 US$ 0.68). Cost drivers varied by platform; the two largest drivers were drug regimens and surgery-related costs. Sensitivity analyses suggest our results are not sensitive to changes in staff salary but are sensitive to changes in medicine pricing. Conclusion: We estimated a large number of context-specific unit costs, over a six-month period, demonstrating a rapid costing method suitable for EPHS design.

Background: Pakistan embarked on a process of designing an essential package of health services (EPHS) as a pathway towards universal health coverage (UHC). The EPHS design followed an evidence-informed deliberative process; evidence on 170 interventions was introduced along multiple stages of appraisal engaging different stakeholders tasked with prioritising interventions for inclusion. We report on the composition of the package at different stages, analyse trends of prioritised and deprioritised interventions and reflect on the trade-offs made. Methods: Quantitative evidence on cost-effectiveness, budget impact, and avoidable burden of disease was presented to stakeholders in stages. We recorded which interventions were prioritised and deprioritised at each stage and carried out three analyses: (1) a review of total number of interventions prioritised at each stage, along with associated costs per capita and disability-adjusted life years (DALYs) averted, to understand changes in affordability and efficiency in the package, (2) an analysis of interventions broken down by decision criteria and intervention characteristics to analyse prioritisation trends across different stages, and (3) a description of the trajectory of interventions broken down by current coverage and cost-effectiveness. Results: Value for money generally increased throughout the process, although not uniformly. Stakeholders largely prioritised interventions with low budget impact and those preventing a high burden of disease. Highly cost-effective interventions were also prioritised, but less consistently throughout the stages of the process. Interventions with high current coverage were overwhelmingly prioritised for inclusion. Conclusion: Evidence-informed deliberative processes can produce actionable and affordable health benefit packages. While cost-effective interventions are generally preferred, other factors play a role and limit efficiency.