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Understanding COVID-19 Impacts on the Health Workforce: AI-Assisted Open-Source Media Content Analysis.

Anita Pienkowska¹, Mathieu Ravaut², Maleyka Mammadova¹

¹Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore.

JMIR Formative Research

|June 13, 2024

Summary

The COVID-19 pandemic significantly impacted the health workforce, with insufficient pay and PPE shortages being key issues. Addressing these through adequate compensation and protective equipment is crucial for future pandemic preparedness.

Keywords:

AI COVID-19 COVID-19 pandemic NLP SARS-COV-2 WHO World Health Organization artificial intelligence death risk decision-making efficiency health care worker health workforce human-generated analysis innovation innovative method intervention media content analysis mental health natural language processing news article news coverage public health public surveillance strategic policy surveillance

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Area of Science:

Public Health
Health Workforce Studies
Computational Social Science

Background:

Investigating the COVID-19 pandemic's effects on the health workforce.
Developing a framework using natural language processing (NLP) and human analysis for news articles.
Complementing scientific literature with media insights for policy support.

Purpose of the Study:

Systematically scan media intelligence not captured by traditional academic channels.
Inform on COVID-19 impacts, contributing factors, and policy responses for the health workforce.
Assess the feasibility of rapidly gathering health workforce insights from open sources.

Main Methods:

NLP-assisted media content analysis of news articles (Jan 2020-June 2022).
Utilized WHO EIOS system data (3,299,158 articles).
Employed rules-based classification, NLP summarization, and deductive-inductive analysis.

Main Results:

Analysis of 5,131 articles revealed key disruptors: insufficient remuneration, PPE shortages, and occupational risks.
Industrial actions and mental health burdens were linked to inadequate compensation.
Workload and staff shortages escalated as the pandemic progressed.

Conclusions:

AI-assisted media content analysis is effective for studying the health workforce.
Prioritizing remuneration and PPE is vital for mitigating pandemic impacts.
Reactive measures for emotional toll and workload are essential for health system resilience.