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상급종합병원의 간호 관련 고객의 소리 분석: 텍스트네트워크 분석 및 토픽모델링

Translated title of the contribution: Voice of Customer Analysis of Nursing Care in a Tertiary Hospital: Text Network Analysis and Topic Modeling
  • Hyunjung Ko
  • , Nara Han
  • , Seulki Jeong
  • , Jeong A. Jeong
  • , Hye Ryoung Yun
  • , Eun Sil Kim
  • , Young Jun Jang
  • , Eun Ju Choi
  • , Chun Hoe Lim
  • , Min Hee Jung*
  • , Jung Hee Kim
  • , Dong Hyu Cho
  • , Seok Hee Jeong
  • *Corresponding author for this work
  • Jeonbuk National University

Research output: Contribution to journalJournal articlepeer-review

Abstract

Purpose: This study aimed to explore customer perspectives of nursing services in tertiary hospitals. Methods: The data comprised mobile Voice Of Customer (VOC) data related to “nursing” or “nurses” generated from June 25, 2019, to December 31, 2022, in a tertiary hospital. A total of 44,727 VOC data points were collected, of which 4,040 were selected for the final analysis. Text network analysis and topic modeling were conducted using NetMiner 4.5.1. Results: Topic modeling identified five topics for positive aspects and four topics for areas requiring improvement. The positive aspects were: 1) sincere nursing care; 2) rapid response from professional medical staff; 3) teamwork for delivering customer-centric services; 4) provision and coordination of system-based healthcare services; and 5) customer-focused responsiveness. The areas requiring improvement were: 1) demand for skilled nursing care tailored to customer expectations; 2) demand for enhanced communication and reduced mechanical responses; 3) demand for appropriate handling of diverse situations; and 4) demand for overall improvements to the healthcare system, including reservation systems. Conclusion: These results may be used to enhance customer and patient experiences in tertiary hospitals and are necessary for utilization from a hospital management perspective.

Translated title of the contributionVoice of Customer Analysis of Nursing Care in a Tertiary Hospital: Text Network Analysis and Topic Modeling
Original languageKorean
Pages (from-to)529-542
Number of pages14
JournalJournal of Korean Academy of Nursing Administration
Volume30
Issue number5
DOIs
StatePublished - 2024.12

Keywords

  • Consumer satisfaction
  • Data mining
  • Nurses
  • Nursing services
  • Social network analysis

Quacquarelli Symonds(QS) Subject Topics

  • Nursing
  • Education & Training

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