A Descriptive Assessment of Healthcare Workers’ Preparedness for Digital Health Systems in Malawi

Mayamiko Nkoloma1, *, Harry Gombachika2, Chomora Mikeka3, Alfred Maluwa4

  1. Institute of Industrial Research and Innovation, Malawi Institute of Technology, Malawi University of Science and Technology, Thyolo 310106, Malawi.
  2. Malawi University of Business and Applied Sciences, Blantyre, Malawi.
  3. University of Malawi, Physics and Electronics Department, P.O. Box 280, Zomba.
  4.  Department of Research and Postgraduate Outreach, Malawi University of Science and Technology, Thyolo 310106, Malawi.

Corresponding Author: Mayamiko Nkoloma ; E-mail: phd-008id-21@must.ac.mw

Abstract

Introduction

Although Malawi has expanded various digital health initiatives under its National Digital Health Strategy, there is still limited research on how prepared frontline healthcare workers really are to adopt and use Digital Health Systems (DHS). Most previous studies have focused on system level improvements in data reporting rather than on the experiences and preparedness of the users themselves. This is a major gap as healthcare workers’ level of preparedness directly influences system performance, and data quality. This study assessed healthcare workers’ preparedness to adopt DHS in Malawi.

Methods

A cross-sectional study was conducted using a structured questionnaire administered to 615 healthcare workers in selected districts across the three regions of Malawi. Key TAM constructs were analysed using descriptive statistics and binary logistic regression.

Results

Overall preparedness levels among healthcare workers for DHS adoption were high. Behavioural intention (94.3%), job relevance (94.1%), and subjective norms (92.1%) recorded the highest scores. Significant predictors of adoption were behavioural intention (OR = 2.67, p < 0.001), job relevance (OR = 2.12, p < 0.001), perceived usefulness (OR = 1.85, p = 0.002), and subjective norms (OR = 1.58, p = 0.014). Majority of respondents from the Southern region reported having attended DHS training compared to those from the Northern region (OR = 2.337, 95% CI:1.549-3.097, p < 0.001), while no significant difference was observed for the Central region (p = 0.330). A higher proportion of male respondents reported having previously attended digital health training compared to female respondents (OR = 1.496, p = 0.019).

Conclusion

Motivational and social factors are the main predictors of DHS adoption in Malawi, while technical capacity remains a challenge. To ensure successful implementation and scale-up of digital health initiatives in Malawi, policymakers and health managers should focus on strengthening and improving user training, improving access to computers and reliable internet within health facilities, and promoting a supportive organisational culture.

Keywords: Digital health systems, Technology Acceptance Model, Healthcare workers’ preparedness, Technology adoption.

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