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Harmonising Assistive Technology Assessment Data: A Case Study in Nepal.

Jamie Danemayer¹, Ben Oldfrey¹, Pratisthit Lal Shrestha²

¹Global Disabilty Innovation Hub, University College London, UK.

Studies in Health Technology and Informatics

|August 28, 2023

Summary

Harmonizing assistive technology (AT) data from multiple surveys in Nepal created a unified dataset. This method allows for trend analysis to better understand and meet the evolving AT needs of diverse populations.

Keywords:

Harmonisation Statistical matching Survey Data

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Area of Science:

Public Health
Data Science
Disability Studies

Background:

Understanding assistive technology (AT) needs in changing populations is crucial.
Integrating disparate datasets can reveal new insights but requires data harmonization.
Existing AT data often exists in separate, non-comparable surveys.

Purpose of the Study:

To explore the potential of harmonizing assistive technology (AT) assessment data.
To create a unified longitudinal dataset from multiple population-based surveys.
To demonstrate a method for trend analysis of AT needs in dynamic populations.

Main Methods:

Harmonized AT assessment data from three Nepal population-based surveys: Living Conditions of Persons with Disabilities (2014-2015), Multiple Indicator Cluster Survey (2019), and rapid Assistive Technology Assessment (2022).
Integrated data from different years into a single longitudinal dataset.
Developed a methodology for unifying disparate AT survey data.

Main Results:

A harmonized dataset was successfully created from three distinct AT surveys.
The harmonized dataset enables trend analysis for monitoring AT needs.
The approach demonstrated the value of situating disparate datasets.

Conclusions:

Data harmonization is a valuable method for integrating multiple AT surveys.
The demonstrated methodology can be applied in other settings for AT needs assessment.
Further validation of the proposed harmonization methodology is recommended.