A comparative assessment of action plans on antimicrobial resistance from OECD and G20 countries using natural language processing. Issue 6 (June 2022)

• Record Type: Journal Article
• Authors: Özçelik, Ece A; Doucet, Cédric; Kang, Hyunjin; Levy, Noémie; Feldhaus, Isabelle; Hashiguchi, Tiago Cravo Oliveira; Lerouge, Aliénor; Cecchini, Michele
• Is Part Of: Health policy. Volume 126:Issue 6(2022)
• Page Start: 522
• Page End: 533
• Publication Date: 2022-06
• Subjects: Antimicrobial resistance -- National action plans -- Global action plan on AMR -- OECD -- G20 -- Natural language processing; Medical education -- Periodicals; Medical policy -- Periodicals; Delivery of Health Care -- Periodicals; Education, Medical -- Periodicals; Health Education -- Periodicals; Health Planning -- Periodicals; Public Policy -- Periodicals; Enseignement médical -- Périodiques; Politique sanitaire -- Périodiques; Medical education; Medical policy; Periodicals; Electronic journals; Electronic journals; 362.1
• DOI: 10.1016/j.healthpol.2022.03.011
• Languages: English
• ISSNs: 0168-8510

Abstract

Highlights: The study compares the content of action plans on antimicrobial resistance. Natural language processing methods were used to assemble a textual database. Terms associated with optimizing antimicrobial use had the highest frequency. Distinct patterns emerged in term frequencies associated with various interventions. Interventions that distinctly occur in each action plans vary. Abstract: Following the launch of the Global Action Plan on antimicrobial resistance (AMR-GAP) in 2015, most OECD and G20 countries developed their own national action plans (AMR-NAPs). This is the first paper that deploys natural language processing (NLP) techniques to systematically measure and compare the extent to which AMR-NAPs from 21 OECD and G20 countries align with the AMR-GAP in terms of the strategic objectives and interventions. We quantify the extent of alignment based on two NLP metrics: term-frequency (TF) and term-frequency-inverse document frequency (TF-IDF). Quantifying TF allows us to compare the relative prominence of strategic objectives and interventions, whereas quantifying TF-IDF enables us to identify interventions that occur more frequently in each AMR-NAP. Similar to the AMR-GAP, in our sample, terms associated with optimizing antimicrobial use in human and animal health have the highest frequency (TF = 0. 287), whereas terms linked to raising AMR awareness and education have the lowest frequency (TF = 0.066). Substantial cross-country variation exists in the distribution of interventions that are distinctly frequent in each AMR-NAP. We also report new evidence on the selected policy design and monitoring and evaluation features of these documents. Our results suggest a high degree of congruence between the AMR-GAP and AMR-NAPs, with notable diversity in the spate of interventions that OECD and G20 countries discuss in their action plans.