Integrating patient voice into hospital performance management - PEGFA Seminar

Greenwich Campus

SL007

This event is part of PEGFA’s seminar series where current research papers are presented and discussed. It will be split into two sessions. In the second talk we will hear Linxi Shi present their paper on 'Integrating patient voice into hospital performance management: a pilot study of NLP-based patient feedback analysis', which is described in the abstract below. 

More details on the first talk and other PEGFA seminars

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Public hospitals are increasingly expected to strengthen patient-centred care, yet internal performance management systems remain largely dominated by financial and operational priorities. Although patient satisfaction feedback is widely collected, it is often used mainly for external reporting or public ranking rather than for internal learning and managerial improvement. The rapid advancement of data analytics and Natural Language Processing (NLP) offers a promising opportunity to transform unstructured qualitative feedback into managerial insights that can inform hospital management accounting and performance systems. This study recognises that patient feedback constitutes not merely a source of data but also a culturally constructed form of expression. The ways in which patients articulate satisfaction, disappointment, or trust are shaped by linguistic norms, politeness conventions, and social expectations. For instance, patients from high-context or collectivist cultures may employ indirect language or mild expressions to communicate dissatisfaction, which can lead to misinterpretation by sentiment analysis models trained on literal word polarity. Likewise, organisational culture influences whether hospital managers regard such digital analyses as credible and actionable information or merely as symbolic artefacts. Thus, the effectiveness of NLP in generating performance-related insights for internal control depends not only on algorithmic sophistication but also on the cultural readiness of both patients and hospital staff to interpret and utilise this information meaningfully. Building upon the NLP-based analysis, the study further explores the roles of management accountants in processing and translating such performance-related information into managerial decision-making and control mechanisms within hospitals. In doing so, it sheds light on how management accountants engage with and adapt to emerging AI-driven developments in performance measurement and management. Ultimately, the study aims to bridge the technological and organisational dimensions of hospital performance management by integrating patient voice analytics into the design and use of management accounting systems, offering both theoretical and practical insights into the digital transformation of public healthcare management.

Presenter:
Linxi Shi

Co-authors:
Jun Wang, Mohit Kumar Singh

Location:
University of Greenwich, Stephen Lawrence Building, SL007

Teams (Online) details:

Meeting ID: 319 421 430 872 5
Passcode: N9eW6W66

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