The cost of ensuring ‘leaving no one behind’

Posted by Temitope Oke on November 30, 2023
Acknowledgements: with thanks to contributors Jennifer Armitage and Adesoji Ologun

About High Impact Clients

Kiran, a 22-year-old woman is 5 months pregnant and lives in Balochistan province in Pakistan. The province is the least populated with approximately 5% of the total population and is mostly isolated because if its mountainous and arid terrain[1]. She lives on less than $2 per day and she has mobility difficulties. She recently commenced ante-natal care clinic but will not be attending clinic regularly because she is unable to physically access the ante-natal clinic because of lack of adequate facilities.

Kiran is an example of a High Impact Client (HIC) that will benefit from health programmes targeted at eradicating poverty in all its forms, end discrimination and exclusion and reduce inequalities and vulnerabilities that leave people behind and undermine the potential of individuals and of humanity as a whole[2].

Purpose of the Equity Costing Analysis

LAMP therefore set out on this journey to estimate the cost of leaving no one behind on a donor-funded multi-country programme implemented in East and Central Africa as well as South-East Asia.

The purpose of the Equity Costing Analysis was to estimate the cost of reaching the high impact clients targeted by the donor-funded programme so that the information can be used to improve decision making on future programmes.

Estimating the Unit Cost of reaching High Impact Clients

While it can be simple to estimate the unit cost of reaching HICs by estimating the number of beneficiaries of the interventions from coverage figures available on the programme and the cost of reaching them, this is not always the case. This is because often, in addition to reaching HICs, programmes also target other persons in the general population, so it was important for the analysis to identify the cost of reaching these HICs specifically as well as the number of actual beneficiaries. As a result, the study estimated the total cost of reaching HICs and non-HICs, the cost of implementing activities specifically targeted at HICs only, known as additional cost of reaching HICs, and the cost of reaching the general population (non-HICs).

The analysis was based on existing data available within the programme in order to minimise the burden of data collection on the teams who were busy running the programme. Cost data was collected from the programme budget, workplans and activity reports.

The analysis set out to estimate the unit cost of reaching HICs based on the assumption that implementing partners would be able to identify the additional activities and cost incurred in reaching HICs. However, there was no clear distinction between the cost of reaching HICs and non-HICs for activities implemented by the programme because there was inadequate data on the profile of the general population and HICs in the target countries. Furthermore, the cost of reaching HICs was embedded in the overall activity implementation cost so was not captured separately by the programme.

Challenges with estimating the additional cost of reaching HICs and the unit cost of reaching HICs

  • Identification of high impact clients: The categories of HICs targeted in the countries by the implementing partners was not properly defined because the same client can be under 20, poor and have a disability. Also, HICs and non-HICs could not be delineated because the programme reached HICs using activities targeted at non-HICs.
  • Identification of interventions targeted at the HICs: IPs retrospectively identified the activities implemented to specifically target HICs so it may be possible to have either under-reported or over-reported these activities due to recall bias.
  • Estimation of additional cost of reaching HICs: This became a challenge because the additional costs estimated included cost of programmes that may or may not have targeted both HICs and non-HICs which resulted in over or under-estimation of the ‘additional’ cost of reaching HICs identified in the study.
  • Quality of cost data available from the programme: The financial system of the programme was not set up to collect the data for the analysis because it was not conceptualized at the onset of the programme.
  • Limitations related to outcome measures: The outcome indicators only considered the number of times the beneficiary encounters the system / number of beneficiaries using the system(users), this does not consider the quality of services delivered.

Recommendations for future programming

Future programmes can capture HIC data better by using measures such as wealth quintile available in Demographic Health Surveys and poverty assessment tools that can guide programming for the poor. Poverty and disability registers[3] can be used to track programme beneficiaries to collect information on social measures of equity while geospatial analysis can be used to identify geographic remoteness and assess differences across areas such as urban/rural, humanitarian, or natural disaster settings.

A programme should include a framework for operationalising equity during programme design. This includes identifying groups, individuals or communities that face inequities, clearly defining activities to address these disparities, developing data collection tools to collect the information related to these activities, ensuring financial management system is optimized to properly categorizes costs related to reaching vulnerable populations and evaluates the results related to the interventions implemented.

Conclusion

People like Kiran exist in different implementation areas and they will remain the focus of donor and nationally funded programmes.  As a result, these programmes should continue to explore ways to measure and demonstrate increasing access to services for poor, people with disabilities, people living in hard-to-reach areas and adolescents. In addition, future donor-funded programmes could explore further analysis using methodologies like distributional cost-effectiveness analysis (DCEA) which offers a framework for incorporating equity concerns into cost effectiveness analysis.


[1] Special Development Scheme for the Uplift Of 20 Poorest Districts In Pakistan  https://www.pc.gov.pk/web/poorestdistricts

[2] Universal Values Principle Two: Leave No One Behind

[1] Missing Billion Initiative and Clinton Health Access Initiative, Reimagining health systems that expect, accept and connect 1 billion people with disabilities, MBI and CHAI, 2022.

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