Qualitative and quantitative evaluation of the use of Twitter as a tool of antimicrobial stewardship

Cumbraos-Sánchez, María José ; Hermoso, Ramón (Universidad de Zaragoza) ; Íñiguez, David (Universidad de Zaragoza) ; Paño-Pardo, José Ramón (Universidad de Zaragoza) ; Allende Bandrés, María Ángeles ; Latorre Martínez, María Pilar (Universidad de Zaragoza)

Resumen: Introduction: Social media networks have transformed the sources of information, including health information. In particular, the microblogging service Twitter has been used as a learning tool in the field of medicine as well as a tool for disease surveillance and outbreak management. As antimicrobial resistance is one of the biggest concerns of public health, we aimed to review how Twitter is being used as a tool for antimicrobial stewardship (AMS). Methods: We used the software Kampal Social® to collect, analyze and monitor tweets from the whole Twitter network to assess the activity that takes place about antibiotics. The study was carried out in three phases: data acquisition, during which we collected data over a six-month period (from 21 September 2016 to 8 February 2017) by monitoring selected users, hashtags and keywords that we knew to be related to AMS; data cleansing, which involved identifying users who were not related to the topic, thus creating a new collection process to remove those users and add newly discovered ones; and, finally, data acquisition and analysis (From 1 April 2017 to 7 March 2018), during which we collected data using the new users obtained in the cleansing phase. We qualitatively characterized the most influential users, we analysed the use of hashtags and the flow of information (the most retweeted users and the global network formed by all the users). Results: Using the tool Kampal Social®, and after a cleansing phase to remove irrelevant information, we worked with a dataset of 1, 765, 388 tweets. Studying the qualitative characterization of the top-ten influencers, we found that most of them are institutional users, but individual users, such as physicians, and an important medical journal also appeared. Regarding hashtags, ‘#antibiotics’ was the one with the most occurrences. Hashtags follow a regular distribution over time, with some defined peaks connected to important dates and reports about antibiotics. As for the flow of information, we obtained a rather dense network of interconnections formed by all the users who had sent a message, which means that a strong relation exists between the different organizations, professionals and users in general. Conclusions: Institutions, medical journals, physicians and pharmacists are key opinion leaders in the topic of antibiotics, so they must incorporate social media into their communication strategy to spread the AMS message. More evidence is needed regarding the optimal method of communication to spread information throughout the general population. The development of tools capable of collecting and querying large amounts of Twitter data helped us to assess the impact of antibiotic awareness campaigns and to gain an idea of how Twitter is being used to spread the message about AMS. © 2019 Elsevier B.V.

Idioma: Inglés

DOI: 10.1016/j.ijmedinf.2019.103955

Año: 2019

Publicado en: INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS 131 (2019), 103955 [10 pp.]
ISSN: 1386-5056

Factor impacto JCR: 3.025 (2019)

Categ. JCR: HEALTH CARE SCIENCES & SERVICES rank: 26 / 102 = 0.255 (2019) - Q2 - T1
Categ. JCR: MEDICAL INFORMATICS rank: 11 / 27 = 0.407 (2019) - Q2 - T2
Categ. JCR: COMPUTER SCIENCE, INFORMATION SYSTEMS rank: 55 / 155 = 0.355 (2019) - Q2 - T2

Factor impacto SCIMAGO: 0.954 - Health Informatics (Q1)

Financiación: info:eu-repo/grantAgreement/ES/DGA/E30-17R
Financiación: info:eu-repo/grantAgreement/ES/DGA-FSE/T35-17D
Financiación: info:eu-repo/grantAgreement/ES/DGA/S42-17R-CREVALOR
Financiación: info:eu-repo/grantAgreement/ES/MCIU/PGC2018-094684-B-C22

Tipo y forma: Article (Published version)

Área (Departamento): Área Organización de Empresas (Dpto. Direcc.Organiza.Empresas)
Área (Departamento): Area Medicina (Dpto. Medicina, Psiqu. y Derm.)
Área (Departamento): Área Física Teórica (Dpto. Física Teórica)
Área (Departamento): Área Lenguajes y Sistemas Inf. (Dpto. Informát.Ingenie.Sistms.)