ANT Perspective of Healthcare Big Data for Service Delivery in South Africa

ANT Perspective of Healthcare Big Data for Service Delivery in South Africa

Tiko Iyamu, Sibulela Mgudlwa
Copyright: © 2022 |Pages: 19
DOI: 10.4018/978-1-6684-3662-2.ch051
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Abstract

In South Africa, there has been for many years challenges in how healthcare big data are accessed, used, and managed by facilities, particularly the small health facilities. The challenges arise from inaccuracy and inconsistency of patients' data and have impact on diagnoses, medications, and treatments, which consequently contributes to fatalities in South Africa, particularly in the rural areas of the country. The problem of inaccuracy and inconsistency of patients' data is often caused by lack of or poor analysis (or analytics) of data. Thus, the objective of this research was to understand the factors that influence the use and management of patients' big data for healthcare service delivery. The qualitative methods were applied, and a South African healthcare facility was used as a case in the study. Actor network theory (ANT) was employed as a lens to guide the analysis of the qualitative data. Based on the findings from the analysis, a model was developed, which is intended to guide analytics of big data for healthcare purposes, towards improving service delivery in the country.
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2. Actor-Network Theory

Actor-network theory (ANT) focuses on how human and nonhuman actors form stable, heterogeneous networks of aligned interests through processes of translations and negotiations (Callon, 1986; Law, 1992). According to Latour (2005), ANT is holistic in its incorporation of humans and non-human into actor-network. This means that human and nonhuman actors have relationship, which ultimately shapes each other (Law, 1992). Despite possible human actors’ different understandings and intentions, they are able to associate and influence each other (Latour, 2005). In ANT, translations are the interactions that happen between actors and their many manifestations (Callon, 1986). Translations entails four moments: problematization, interessement, enrolment and mobilisation (Callon, 1986). Accessing, use and management of healthcare big data involve processes of interaction and negotiations between: humans, human and nonhuman, and nonhumans.

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