Disability Data Collection in a Complex Humanitarian Organisation: Lessons from a Realist Evaluation.

Claire F O’Reilly,Louise Caffrey,Caroline Jagoe

doi:10.3390/ijerph181910334

Abstract

In recent years, global attention to disability inclusion in humanitarian and development contexts, notably comprising disability inclusion within the Sustainable Development Goals, has significantly increased. As a result, UN agencies and programmes are increasingly seeking to understand and increase the extent to which persons with disabilities are accounted for and included in their efforts to provide life-saving assistance. To explore the effects and effectiveness of such measurement, this paper applies a complexity-informed, realist evaluation methodology to a case study of a single measurement intervention. This intervention, ‘A9’, was the first indicator designed to measure the number of persons with disabilities assisted annually by the United Nations World Food Programme (WFP). Realist logic of analysis combined with complexity theory was employed to generate context-mechanism-outcome configurations (CMOC’s) against which primary interviews and secondary data were analysed. We show that within the complexity of the WFP system, the roll-out of the A9 measurement intervention generated delayed, counter-intuitive and unanticipated effects. In turn, path dependency and emergent behaviours meant that the intervention mechanisms of yesterday were destined to become the implementation context of tomorrow. These findings challenge the current reliance on quantitative data within humanitarian-development disability inclusion efforts and contribute to our understanding of how data can best be leveraged to support inclusion in such contexts.

Highlights

Disability inclusion (DI) is an increasingly prominent concern across humanitarian and development work
We conceptualized the implementation of disability data collection as an ‘intervention’, in that it has an underlying theory as to how it can bring about an outcome or change within the UN World Food Programme (WFP) system
We present the CMOCs in a ‘stackable’ order (Figure 1), whereby one outcome can be seen to influence the context in which subsequent mechanisms may operate

Summary

Introduction

Disability inclusion (DI) is an increasingly prominent concern across humanitarian and development work. The collection, analysis and use of disability-relevant data, disaggregated data, has been championed as a way to operationalise the DI agenda and advance the sustainable development goals (SDG) stated aim of ‘leaving no one behind’ [1,2]. We conceptualized the implementation of disability data collection as an ‘intervention’, in that it has an underlying theory (implicit or explicit) as to how it can bring about an outcome or change within the UN World Food Programme (WFP) system. While guidance exists on selecting appropriate measures Understanding how a complex system responds to disability data interventions is crucial if such data interventions are to be mainstreamed across humanitarian and development organisations

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Discussion

Conclusion