Data science and its application in anesthesiology

  • Shemila Abbasi
  • Usama Ahmed
  • Fauzia Anis Khan
Keywords: Electronic Health Records, Data, Data Science, Anesthesiology

Abstract

Electronic health records have brought about vast improvement in all aspects of healthcare. ‘Anesthesia Information Management System’ is a specialized form of electronic health record system that is used to record all of the events taking place during the perioperative period, such as clinical procedures performed, physiologic changes that may happen and the medications administered. Based on anesthetic data many databases have been developed internationally for quality improvement in anesthesiology and to know the research outcomes. At an individual clinical level, big anesthesia data is not yet present, unless waveforms and continuous numerical data of intraoperative physiologic variables is recorded. Though the initiative for big data has taken up by some healthcare institutions in the health data management but our country is still far behind in this field. This editorial is aimed to highlight the necessity of this system and to draw the attention of the concerned authorities to plan provision of electronic record keeping in operating rooms.

Key words: Electronic Health Records; Data; Data Science; Anesthesiology

Citation: Abbasi S, Ahmed U, Khan FA. Data science and its application in anesthesiology. Anaesth. pain intensive care 2021;26(1):1–3;

DOI: 10.35975/apic.v26i1.1757

Received: January 11, 2022, Accepted: January 14, 2022

Author Biographies

Shemila Abbasi

Assistant Professor, Department of Anesthesiology, Aga Khan University, Karachi, Pakistan.

Usama Ahmed

Fellow Pain Medicine, Department of Anesthesiology, Aga Khan University, Karachi, Pakistan

Fauzia Anis Khan

Professor, Department of Anesthesiology, Aga Khan University, Karachi, Pakistan.  

Published
02-02-2022
How to Cite
Abbasi, S., Ahmed, U., & Khan, F. (2022). Data science and its application in anesthesiology. Anaesthesia, Pain & Intensive Care, 26(1), 1-3. https://doi.org/10.35975/apic.v26i1.1757
Section
Editorial Views