Enhancing Public Healthcare Through VADER Sentiment Analysis: A Case Study on Patient Complaints.
This study investigates the application of Valence Aware Dictionary and Sentiment Reasoner (VADER), a rule-based sentiment analysis tool, for rapidly analyzing patient complaints in healthcare environments. By leveraging VADER's efficiency in processing free-text data, the research examines how sent...
| Publicado en: | Journal of Patient Experience Vol. 13; pp. 1 - 10 |
|---|---|
| Autores principales: | , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Sage Publications Inc.
1/28/2026
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=191203480&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 191203480 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23743735 K506 jtl: Journal of Patient Experience issn: 23743735 maglogo: Y pubinfo: dt: 1/28/2026 vid: 13 pid: 344 pub: Sage Publications Inc. place: Thousand Oaks, California artinfo: ui: 191203480 191203480 191203480 10.1177/23743735251413861 191203480 ppf: 1 ppct: 9 formats: tig: atl: Enhancing Public Healthcare Through VADER Sentiment Analysis: A Case Study on Patient Complaints. aug: au: Coelho, João Vasco Barbosa, Liliana da Costa affil: Centro de Investigação e Estudos em Sociologia (CIES), Instituto Universitário de Lisboa (ISCTE-IUL), Lisbon, Portugal sug: subj: Public Health Quality Improvement Sentiment Analysis Natural Language Processing Patient Attitudes Feedback Portugal Human Hospitals, Public Data Mining Interrater Reliability Workflow Machine Learning Patient Centered Care Decision Making ab: This study investigates the application of Valence Aware Dictionary and Sentiment Reasoner (VADER), a rule-based sentiment analysis tool, for rapidly analyzing patient complaints in healthcare environments. By leveraging VADER's efficiency in processing free-text data, the research examines how sentiment analysis can support digital transformation and enhance patient experience management. The study assesses VADER's effectiveness in detecting emotional tone within patient feedback, enabling early identification of systemic issues and informing data-driven decision-making. The dataset comprises 63 written complaints collected throughout 2024 from a key surgery service in a 10 000-employee public hospital in Portugal. Sentiment analysis was conducted using Orange text mining tools integrated with VADER. Three core findings highlight VADER's value: (a) its balance of efficiency and accuracy in sentiment classification, (b) its contribution to patient-centered care strategies, and (c) its support for process optimization, particularly in triage and prioritization workflows. These insights demonstrate how sentiment analysis can help build smarter, more responsive healthcare systems through enhanced digital capabilities. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|