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Consultant: Health Economist – Cost and Efficiency Analysis

Dtree · Lilongwe, Plot Area 13/92, 207201, Malawi · Remote · Active · BambooHR

Job facts

FieldValue
CompanyDtree
TitleConsultant: Health Economist – Cost and Efficiency Analysis
Normalized title-
Department / teamProgram
LocationLilongwe, Plot Area 13/92
Work modelRemote / Remote
Employment typeContract
Salary-
Statusactive
ATS providerBambooHR
Posted / first seen2026-05-06 / 2026-05-30
Changed / last seen2026-05-30 / 2026-06-06

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Linked records

CompanyDtree
Sourcec3063d77-acb6-4c2c-a329-b5001ab10422
ATS providerBambooHR

Description

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 your CV in the CV section Upload your cover letter and budget in the Cover 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.

Full job record

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Providerbamboohr
Provider Job Key50
TitleConsultant: Health Economist – Cost and Efficiency Analysis
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Statusactive
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Location TextLilongwe, Plot Area 13/92, 207201, Malawi
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RegionPlot Area 13/92
CityLilongwe
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Apply URLhttps://dtree.bamboohr.com/careers/50
First Seen At2026-05-30 06:04:23Z
Last Seen At2026-06-06 10:25:10Z
Last Checked At2026-06-06 10:25:10Z
Last Changed At2026-05-30 06:04:23Z
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Source Posted At2026-05-06 00:00:00Z
Source Updated At
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    "description": "<p><span style=\"color: rgb(27, 94, 123); font-size: 12pt; font-weight: bold\">1. Background</span></p>\n<p><span style=\"font-size: 10pt\">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.</span></p>\n<p><span style=\"font-size: 10pt; font-style: italic\">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. </span></p>\n<p><span style=\"color: rgb(27, 94, 123); font-size: 12pt; font-weight: bold\">2. Objective</span></p>\n<p><span style=\"font-size: 10pt\">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.</span></p>\n<p><span style=\"color: rgb(27, 94, 123); font-size: 12pt; font-weight: bold\">3. What We Need From the Health Economist</span></p>\n<p><span style=\"font-size: 10pt; font-style: italic\">The health economist provides specialized economic knowledge, analysis, and methodology guidance.</span></p>\n<p><span style=\"font-size: 10pt; font-weight: bold\">A. Understanding Current Cost Drivers</span></p>\n<p><span style=\"font-size: 10pt\">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?</span></p>\n<p><span style=\"font-size: 10pt; font-weight: bold\">B. Economic Evidence for Intervention Design</span></p>\n<p><span style=\"font-size: 10pt; font-style: italic\">The economist provides the cost evidence and analysis that will inform design decisions.</span></p>\n<p><span style=\"font-size: 10pt\">What intervention design features are most likely to reduce costs to the health system, based on evidence from comparable settings? For example:</span></p>\n<ul>\n<li><span style=\"font-size: 10pt\">Earlier identification and management of danger signs at community level (reducing severe cases and emergency presentations)</span></li>\n<li><span style=\"font-size: 10pt\">Improved referral completion and counter-referral (reducing repeat visits or delayed care)</span></li>\n<li><span style=\"font-size: 10pt\">Stronger coordination between HSAs and facility staff (reducing redundant data collection and improving care continuity)</span></li>\n<li><span style=\"font-size: 10pt\">Digital tools that reduce time spent gathering redundant information or context</span></li>\n</ul>\n<p><span style=\"font-size: 10pt\">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?</span></p>\n<p><span style=\"font-size: 10pt; font-weight: bold\">C. Anticipating Cost-Effectiveness Measurement and Designing for Evaluability</span></p>\n<p><span style=\"font-size: 10pt; font-style: italic\">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.</span></p>\n<ul>\n<li><span style=\"font-size: 10pt\">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? </span></li>\n<li><span style=\"font-size: 10pt\">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? </span></li>\n<li><span style=\"font-size: 10pt\">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. </span></li>\n<li><span style=\"font-size: 10pt\">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? </span></li>\n<li><span style=\"font-size: 10pt\">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?</span></li>\n</ul>\n<p><span style=\"font-size: 10pt; font-weight: bold\">D. Building the Investment Case</span></p>\n<p><span style=\"font-size: 10pt\">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?</span></p>\n<p><span style=\"color: rgb(27, 94, 123); font-size: 12pt; font-weight: bold\">4. Deliverables</span></p>\n<ul>\n<li><span style=\"font-size: 10pt\">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</span></li>\n<li><span style=\"font-size: 10pt\">Summary of economic evidence on cost-reduction strategies from comparable settings, with guidance on which design features are most likely to generate savings</span></li>\n<li><span style=\"font-size: 10pt\">Joint memo with clinical expert linking priority health outcome indicators to their cost implications and quantifiable savings potential</span></li>\n<li><span style=\"font-size: 10pt\">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</span></li>\n<li><span style=\"font-size: 10pt\">Brief investment case framing document outlining the economic argument for the Government of Malawi and funders, including relevant benchmarks from comparable programs</span></li>\n</ul>\n<p><span style=\"color: rgb(27, 94, 123); font-size: 12pt; font-weight: bold\">5. Expert Profile</span></p>\n<ul>\n<li><span style=\"font-size: 10pt\">Advanced degree in health economics, public health economics, or related field</span></li>\n<li><span style=\"font-size: 10pt\">Demonstrated experience conducting cost-effectiveness analyses of health interventions in low- and middle-income countries</span></li>\n<li><span style=\"font-size: 10pt\">Experience with costing studies in primary health care or community health systems, with a focus on maternal and/or newborn health preferred</span></li>\n<li><span style=\"font-size: 10pt\">Familiarity with economic evaluation methods used in global health (e.g., CEA, cost-benefit analysis, budget impact analysis)</span></li>\n<li><span style=\"font-size: 10pt\">Experience in Sub-Saharan Africa or similar LMIC contexts preferred; familiarity with the Malawi health system an advantage</span></li>\n<li><span style=\"font-size: 10pt\">Track record of producing evidence used for policy advocacy or investment cases</span></li>\n</ul>\n<p><span style=\"color: rgb(27, 94, 123); font-size: 12pt; font-weight: bold\">6. Level of Effort and Timeline</span></p>\n<p><span style=\"font-size: 10pt\">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.</span></p>\n<p><span style=\"color: rgb(27, 94, 123); font-size: 12pt; font-weight: bold\">7. Budget Requirements</span></p>\n<p><span style=\"font-size: 10pt\">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.</span></p>\n<p><span style=\"color: rgb(27, 94, 123); font-size: 12pt; font-weight: bold\">8. Application</span></p>\n<p><span style=\"font-size: 10pt\">To apply for this role, please submit your application through this</span><a href=\"https://dtree.bamboohr.com/careers/50\" target=\"_blank\" rel=\"noopener noreferrer\"><span style=\"font-size: 10pt; font-weight: bold\"> link</span></a><span style=\"font-size: 10pt\">.</span></p>\n<ul>\n<li><span style=\"font-size: 10pt\">Upload your </span><span style=\"font-size: 10pt; font-weight: bold\">CV</span><span style=\"font-size: 10pt\"> in the </span><span style=\"font-size: 10pt; font-style: italic\">CV section</span></li>\n<li><span style=\"font-size: 10pt\">Upload your </span><span style=\"font-size: 10pt; font-weight: bold\">cover letter and budget </span><span style=\"font-size: 10pt\">in the </span><span style=\"font-size: 10pt; font-style: italic\">Cover Letter section</span></li>\n</ul>\n<p><span style=\"font-size: 10pt\">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: </span><span style=\"font-size: 10pt; font-weight: bold\">May 15, 2026.</span></p>\n<p><br></p>",
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