Sentiment analysis of patient complaints in healthcare systems using VADER: Can it contribute to a better service?

dc.contributor.authorBarbosa, L.
dc.contributor.authorCoelho, J. V.
dc.contributor.editor Mendes, Mateus
dc.contributor.editorFarinha, José Torres
dc.contributor.editorMalta,Ana Rita
dc.contributor.editorRaposo, Hugo
dc.date.accessioned2026-10-09T14:18:35Z
dc.date.issued2025
dc.date.updated2026-10-09T15:16:13Z
dc.description.abstractThis study focuses on exploring the effectiveness of using VADER (Valence Aware Dictionary and sEntiment Reasoner), a rule-based sentiment analysis tool, in swiftly analyzing patient complaints within healthcare settings aiming to develop overall digital capabilities. Currently, the use of sentiment analysis in the healthcare space is considered to be under-explored. Free-text complaints from patients often contain valuable insights into their experiences. However, analyzing large volumes of textual feedback can be time-consuming and prone to subjective interpretation. Sentiment analysis tools such as VADER can provide meaningful solutions by automatically extracting and quantifying the emotional tone of textual data. The dataset used in the study comprised the total number and written free-text of patient complaints collected during 2024, in a key surgery service of a 10,000 employee public hospital located in Portugal. Three key study findings demonstrate the benefits of using VADER to enhance healthcare patient experience management: (a) its ability to balance efficiency and accuracy in sentiment analysis without compromising precision, (b) its role in fostering a culture of patient-centered care decision-making, and (c) its support for process optimization and digitalization efforts, namely in terms of case triage and prioritization.eng
dc.event.date2025
dc.event.locationCoimbraeng
dc.event.titleInternational conference on Physical Asset Management and Data Science
dc.event.typeConferênciapt
dc.identifier.citationBarbosa, L., & Coelho, J. V. (2025). Sentiment analysis of patient complaints in healthcare systems using VADER: Can it contribute to a better service?. In M. Mendes, J. T. Farinha, A. R. Malta, & H. Raposo (Eds.), Proceedings of PAMDAS 2025 (pp. 443-453). RCM2+ - Research Centre for Asset Management and Systems Engineering. https://hdl.handle.net/10071/38707
dc.identifier.isbn978-989-8331-19-9
dc.identifier.urihttps://hdl.handle.net/10071/38707
dc.language.isoeng
dc.pagination443 - 453
dc.peerreviewedyes
dc.publisherRCM2+ - Research Centre for Asset Management and Systems Engineering
dc.relation.ispartofProceedings of PAMDAS 2025
dc.rightsopenAccess
dc.subjectNatural language processing (NLP)eng
dc.subjectSentiment analysiseng
dc.subjectText classificationeng
dc.subjectVADER sentiment analysiseng
dc.subjectBERT analysiseng
dc.subjectHealthcareeng
dc.subjectPatient experienceeng
dc.subjectPatient complaintseng
dc.titleSentiment analysis of patient complaints in healthcare systems using VADER: Can it contribute to a better service?eng
dc.typeconferenceObject
iscte.identifier.cienciahttps://ciencia.iscte-iul.pt/id/ci-pub-112788

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