1. Background

As part of a maternal and newborn health collaborative care initiative in Malawi, D-tree seeks to demonstrate that strengthening the care pathway between community and facility levels can improve health outcomes and patient experiences, while reducing costs to the health system. Collaborative care refers to a model in which community health workers (HSAs) and facility-based providers work in an intentional, coordinated way to manage care for the same patients across the continuum–moving beyond one-directional referrals to a system where information, responsibility, and follow-up are shared bi-directionally across levels. Rather than treating community and facility care as separate, a collaborative care model is designed so that each level builds on the other's work, enabling continuity, reducing gaps, and improving the overall quality of care a patient receives. A health economist is needed to provide cost-related expertise during the intervention design phase, ensuring D-tree has the economic evidence and methodological guidance needed to design an intervention that is positioned to demonstrate cost-effectiveness and efficiency gains.

Note: D-tree is in the process of selecting a specific clinical focus area within maternal and newborn health–for example, care for women with high-risk pregnancies or management of premature or low birthweight newborns–for this collaborative care initiative in Malawi. Through strategic engagement MOH and other stakeholders, we will select the specific focus area prior to the consultant beginning their work. This SOW references maternal and newborn health broadly as a placeholder, but the consultant's work will be scoped to the selected focus area once confirmed.

2. Objective

To provide health economics expertise that equips D-tree with the evidence, benchmarks, and methodological guidance needed to design an intervention that incorporates cost-reduction strategies and is positioned to demonstrate measurable health system cost savings, cost-effectiveness, and efficiency improvements. D-tree will lead the translation of these economic inputs into intervention design decisions.

3. What We Need From the Health Economist

The health economist provides specialized economic knowledge, analysis, and methodology guidance.

A. Understanding Current Cost Drivers

What are the primary cost drivers in the current maternal and newborn care pathway in Malawi (e.g., late presentation or delayed referral leading to complications, inefficient referral systems, hospitalizations for complications, gaps in postnatal follow-up)? Where are the greatest inefficiencies or cost leakages in the current system that a collaborative care intervention could realistically address?

B. Economic Evidence for Intervention Design

The economist provides the cost evidence and analysis that will inform design decisions.

What intervention design features are most likely to reduce costs to the health system, based on evidence from comparable settings? For example:

Earlier identification and management of danger signs at community level (reducing severe cases and emergency presentations)
Improved referral completion and counter-referral (reducing repeat visits or delayed care)
Stronger coordination between HSAs and facility staff (reducing redundant data collection and improving care continuity)
Digital tools that reduce time spent gathering redundant information or context

What evidence exists from comparable settings about cost savings from strengthening community-to-facility maternal and newborn care pathways? What are realistic expectations for cost reduction within a 1-year implementation period, and what assumptions underpin those estimates? How should we think about the investment costs of the intervention itself (training, tools, supervision) relative to the expected savings?

C. Anticipating Cost-Effectiveness Measurement and Designing for Evaluability

D-tree anticipates conducting a baseline evaluation in 2027, ahead of piloting the collaborative care model. The purpose of this section is to ensure the intervention design is informed by likely cost-effectiveness measures from the outset, so that D-tree is positioned to demonstrate impact when a full evaluation is conducted in the future.

What cost-effectiveness measures are most likely to be used in an evaluation of this type of intervention (e.g., cost per DALY averted, cost per maternal or neonatal death averted, cost per case appropriately managed)? Given these likely measures, what should D-tree be paying attention to in its design choices?
What averted-cost metrics are evaluators likely to focus on (e.g., complications prevented, reduced in-patient admissions, cases managed at lower level facilities v. hospitals)? For each, what intervention design features would most directly drive those savings?
What cost data will a future evaluation likely need to capture at community, facility, and health system levels? Collaborate with D-tree to assess whether routine monitoring systems and digital tools are generating data in the right format and frequency, or whether modifications should be built into the design.
How should we think about government costs vs. program/donor costs from an intervention design perspective? Are there design choices that shift costs toward government-funded inputs, making the program more sustainable and the cost argument more compelling for the Government of Malawi?
What are the most common methodological limitations in cost-effectiveness evaluations of community health programs in LMICs, and what should D-tree be aware of when designing the intervention and its data systems?

D. Building the Investment Case

What economic evidence would be most compelling for the Government of Malawi and potential funders to justify continued investment and scale-up of this model? How should we frame the return on investment for a government-integrated collaborative care program versus the counterfactual (no intervention)? What benchmarks from comparable programs or countries should we reference to contextualize our findings?

4. Deliverables

Analysis of current cost drivers in the Malawi maternal and newborn care pathway, identifying where the greatest inefficiencies exist and which are most amenable to intervention
Summary of economic evidence on cost-reduction strategies from comparable settings, with guidance on which design features are most likely to generate savings
Joint memo with clinical expert linking priority health outcome indicators to their cost implications and quantifiable savings potential
Summary of likely cost-effectiveness measures and averted-cost metrics that a future evaluation would use, with recommendations for how the intervention's monitoring systems and digital tools could be configured to generate the data needed
Brief investment case framing document outlining the economic argument for the Government of Malawi and funders, including relevant benchmarks from comparable programs

5. Expert Profile

Advanced degree in health economics, public health economics, or related field
Demonstrated experience conducting cost-effectiveness analyses of health interventions in low- and middle-income countries
Experience with costing studies in primary health care or community health systems, with a focus on maternal and/or newborn health preferred
Familiarity with economic evaluation methods used in global health (e.g., CEA, cost-benefit analysis, budget impact analysis)
Experience in Sub-Saharan Africa or similar LMIC contexts preferred; familiarity with the Malawi health system an advantage
Track record of producing evidence used for policy advocacy or investment cases

6. Level of Effort and Timeline

Estimated 6 days from June-July 2026. Unless the consultant is based in Malawi, engagement will include remote consultations and document review. Potential for one trip to Malawi if the consultant is based nearby and budgetarily feasible.

7. Budget Requirements

The consultant will submit a proposed budget as part of the application, which will be reviewed and approved by D-tree. Please include a simple budget of your daily rate (if a group is applying, please list each individual and their individual daily rates) and the number of days. If applicable, any other anticipated costs should be specified and explained.

8. Application

To apply for this role, please submit your application through this link.

Upload yourCV in theCV section
Upload yourcover letter and budgetin theCover Letter section

Please note that by applying to this position, you consent to your name being checked against a terrorist watch list prior to any consultancy engagement. Deadline for submitting applications:May 15, 2026.

D-tree remote jobs

Consultant: Health Economist – Cost and Efficiency Analysis