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<p>Digital transformation is reshaping healthcare management by introducing advanced technologies that improve processes, services, and decision-making. Among these, Artificial Intelligence (AI) represents a promising tool for enhancing performance measurement (PM). This study investigates the potential of AI to support PM by focusing on outcomes perceived at the community level, a dimension rarely measured yet important to assess the public value recognized by community. Adopting an action-research approach, the study applies Sentiment Analysis (SA) to nine public hospitals in the Sicilian regional health system to develop a PM dashboard. Online mentions collected from social media, news sites, blogs, and forums were analysed through AI-based tool to generate structured indicators of sentiment and thematic insights. Results were synthesized in interactive dashboards, enabling benchmarking across hospitals and offering managers actionable information to improve communication, accountability, and service strategies. The findings highlight how AI-driven sentiment and topic analysis can support traditional PM by capturing non-investigated dimensions of perceived value at the societal level and enhancing dialogic accountability. The study advances theoretical knowledge on digital transformation in healthcare PM and offers practical implications for managers seeking to integrate AI into value recognition and strategic decision-making.</p>

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Advancing performance measurement in public healthcare organizations through artificial intelligence: evidence from action research

  • 期刊论文

  • 发表日期：

    2026年7月7日

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  • Guido Noto,
  • Mariangela Barraco,
  • Francesca De Domenico,
  • Gustavo Barresi

摘要

Digital transformation is reshaping healthcare management by introducing advanced technologies that improve processes, services, and decision-making. Among these, Artificial Intelligence (AI) represents a promising tool for enhancing performance measurement (PM). This study investigates the potential of AI to support PM by focusing on outcomes perceived at the community level, a dimension rarely measured yet important to assess the public value recognized by community. Adopting an action-research approach, the study applies Sentiment Analysis (SA) to nine public hospitals in the Sicilian regional health system to develop a PM dashboard. Online mentions collected from social media, news sites, blogs, and forums were analysed through AI-based tool to generate structured indicators of sentiment and thematic insights. Results were synthesized in interactive dashboards, enabling benchmarking across hospitals and offering managers actionable information to improve communication, accountability, and service strategies. The findings highlight how AI-driven sentiment and topic analysis can support traditional PM by capturing non-investigated dimensions of perceived value at the societal level and enhancing dialogic accountability. The study advances theoretical knowledge on digital transformation in healthcare PM and offers practical implications for managers seeking to integrate AI into value recognition and strategic decision-making.