Big Data in Studying Acute Pain and Regional Anesthesia

Area of Science:

• Healthcare Informatics
• Clinical Research
• Anesthesiology

Background:

• Digital transformation increases clinical data availability for research.
• Perioperative big data initiatives initially focused on quality surveillance.
• Big data analysis now drives novel clinical research questions.

Purpose of the Study:

• To review the growing importance of big data in acute postoperative pain research.
• To examine the role of big data in regional anesthesia research.
• To highlight how big data facilitates understanding of treatment quality and outcomes.

Main Methods:

• Narrative review of literature.
• Analysis of multicentric clinical registries and administrative databases.
• Examination of big data utilization in acute pain and regional anesthesia studies.

Main Results:

• Big data analyses have moved beyond quality surveillance to become primary research tools.
• Significant increase in big data utilization in acute pain and regional anesthesia research over the last decade.
• Millions of cases from databases have been used to address key research questions.

Conclusions:

• Big data is crucial for assessing postoperative pain, opioid use, and multimodal pain management.
• Big data aids in evaluating adverse events and the impact of regional anesthesia on patient outcomes.
• The utilization of big data is essential for advancing research in acute postoperative pain and regional anesthesia.