YAPAY ZEKÂ DESTEKLİ HASTANE YÖNETİMİ VE LİDERLİĞİ: BİBLİYOMETRİK BİR ANALİZ

Öz

Günümüzde yapay zekâ (YZ) hastane yönetimi ve liderliği süreçlerinde stratejik bir dönüştürücü güç hâline gelmiştir. Bu çalışmanın amacı, 2015-2025 yılları arasında YZ destekli hastane yönetimi ve liderliği alanındaki bilimsel üretimi sistematik biçimde incelemektir. Çalışma alana ilişkin tematik eğilimlerin belirlenmesinde stratejik yol gösterici olarak özgün bir değere sahiptir. Çalışmada nicel bibliyometrik analiz yaklaşımı benimsenmiştir. Veriler 10 Kasım 2025 tarihinde Web of Science veri tabanından elde edilmiştir. Yayın türü (makale ve derleme), zaman aralığı (2015-2025) ve dil kriteri (İngilizce) filtrelemesi ile veri ön işleme (CR normalizasyonu) uygulanmıştır. Analiz, performans analizi ve bilimsel haritalama analizi olarak iki ana eksende yürütülmüştür. Analizler, RStudio (v4.5.2) ve Bibliometrix R paketi web arayüzü olan Biblioshiny (v5.0) kullanılarak gerçekleştirilmiştir. Alana ilişkin 6.394 kayıt tespit edilmiş yapılan filtreleme ve normalizasyon işlemlerinin ardından 4.669 kayıt analize dâhil edilmiştir. 2015-2025 yılları arasında yayın sayısı yaklaşık 74 kat artmıştır. Literatür büyük ölçüde Asya ve Amerika merkezli araştırma grupları tarafından şekillendirilmektedir. “machine learning”, “deep learning”, “prognostics and health management” ve “anomaly detection” teknik temalarının yönetim ve liderlik literatürüyle bütünleştiği görülmektedir. En fazla katkı yapan ülkeler Çin, ABD ve İran olurken araştırmaların odak noktası; veri odaklı karar verme, öngörücü yönetim ve dijital liderlik alanlarıdır. YZ, hastane yönetiminde stratejik yönetişim ve liderlik süreçlerini yeniden şekillendirmektedir. Literatür teknik uygulamalardan yönetimsel modellere doğru genişlemektedir. Çalışma, YZ destekli hastane yönetimi ve liderliğine ilişkin boşlukları görünür kılmakta ve gelecekteki araştırmalara yön verecek kavramsal bir çerçeve sunmaktadır.

Anahtar Kelimeler

• Yapay Zekâ
• Hastane Yönetimi
• Dijital Liderlik
• Makine Öğrenmesi
• Bibliyometrik Analiz

ARTIFICIAL INTELLIGENCE-ENHANCED HOSPITAL MANAGEMENT AND LEADERSHIP: A BIBLIOMETRIC ANALYSIS

Öz

In the current era, artificial intelligence (AI) has become a strategic transformative force in hospital management and leadership processes. The aim of this study is to systematically examine scientific production in the field of AI-enhanced hospital management and leadership between 2015-2025. The study has unique value as a strategic guide in identifying thematic trends in the field. A quantitative bibliometric analysis approach was adopted in the study. Data were obtained from the Web of Science database on November 10, 2025. Data preprocessing (CR normalization) was applied by filtering publication type (article and review), time period (2015-2025), and language criterion (English). The analysis was conducted along two main axes: performance analysis and scientific mapping analysis. Analyses were performed using RStudio (v4.5.2) and Biblioshiny (v5.0), the web interface of the Bibliometrix R package. 6,394 records related to the field were identified and after the filtering and normalization processes, 4,669 records were included in the analysis. The number of publications increased approximately 74-fold between 2015-2025. The literature is largely shaped by research groups based in Asia and the Americas. The technical themes of “machine learning”, “deep learning”, “prognostics and health management” and “anomaly detection” appear to be integrated with management and leadership literature. While the countries that contributed the most were China, the USA and Iran, the focus of the research is on data-driven decision-making, predictive management and digital leadership. AI is reshaping strategic governance and leadership processes in hospital management. The literature is expanding from technical applications to managerial models. The study highlights gaps in AI-enabled hospital management and leadership and provides a conceptual framework to guide future research.

Anahtar Kelimeler

• Artificial Intelligence
• Hospital Management
• Digital Leadership
• Machine Learning
• Bibliometric Analysis

Kaynakça

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