The Future of Critical Care: Innovations in Patient-Centered Technology

Authors

  • Corina VERNIC Department of Medical Informatics and Biostatistics, “Victor Babeş” University of Medicine and Pharmacy, Timişoara, Square Eftimie Murgu, no. 2, 300041 Timişoara, Romania
  • Balázs CSUTAK Department of Anesthesia and Intensive Care, Emergency County Clinical Hospital "Pius Brînzeu" Timişoara, Liviu Rebreanu Blvd, no. 156, 300723 Timişoara, Romania
  • Ovidiu Horea BEDREAG Department of Anesthesia and Intensive Care, “Victor Babeş” University of Medicine and Pharmacy, Timişoara, Square Eftimie Murgu, no. 2, 300041 Timişoara, Romania
  • Sebastian-Aurelian ŞTEFĂNIGĂ Department of Computer Science, West University of Timişoara, 300223 Timişoara, Romania
  • Călin MUNTEAN Department of Medical Informatics and Biostatistics, “Victor Babeş” University of Medicine and Pharmacy, Timişoara, Square Eftimie Murgu, no. 2, 300041 Timişoara, Romania

Keywords:

Centricity, Artificial Intelligence (AI), AI-driven intervention

Abstract

In the landscape of modern healthcare, the evolution of critical care has been marked by the integration of innovative technologies and the emergence of patient-centered approaches. This study aimed to explore the potential of Artificial Intelligence (AI) in shaping the future of critical care, using data collected from Centricity High Acuity data warehouse from the Anesthesia and Intensive Care Clinic and the operating theater from Emergency County Clinical Hospital "Pius Brînzeu" Timişoara. The existing healthcare landscape is characterized by the complex balance between technological advances and patient-centered care. The advent of AI presents an opportunity to revolutionize critical care, offering real-time insights and personalized interventions. This research seeks to harness the capabilities of AI to enhance patient outcomes in critical care scenarios. The study was conducted at a tertiary care hospital, using a mixed-methods approach that involved retrospective analysis of patient data from Centricity. The AI algorithms were trained on historical data to predict patient deterioration patterns, enabling timely interventions and proactive management. Results demonstrated that the integration of AI-driven insights from Centricity High Acuity data warehouse significantly improves patient outcomes. AI-assisted interventions led to reduced instances of adverse events, shorter lengths of stay, and improved resource utilization. The AI algorithms demonstrated high accuracy in predicting patient deterioration, enabling early interventions and preventing complications. In conclusion, the integration of AI technology using data from Centricity High Acuity data warehouse holds immense promise for the future of patient-centered critical care. The results indicate that AI-driven interventions can enhance patient outcomes, reduce healthcare costs, and improve resource utilization. As healthcare continues to embrace AI, the potential for transformative advancements in critical care is evident, paving the way for a new era of innovative and personalized patient-centered care.

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Published

10.09.2023

How to Cite

1.
VERNIC C, CSUTAK B, BEDREAG OH, ŞTEFĂNIGĂ S-A, MUNTEAN C. The Future of Critical Care: Innovations in Patient-Centered Technology. Appl Med Inform [Internet]. 2023 Sep. 10 [cited 2024 Jun. 17];45(Suppl. S1):S20. Available from: https://ami.info.umfcluj.ro/index.php/AMI/article/view/970

Issue

Section

Special Issue - RoMedINF