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Review

Big Data in Studying Acute Pain and Regional Anesthesia

by 1,2,* and 1,2,*
1
Department of Anaesthesiology, Intensive Care and Pain Therapy, Saarland University Medical Center and Saarland University Faculty of Medicine, 66421 Homburg, Saarland, Germany
2
Outcomes Research Consortium, Cleveland, OH 44195, USA
*
Authors to whom correspondence should be addressed.
Academic Editor: Winfried Meissner
J. Clin. Med. 2021, 10(7), 1425; https://doi.org/10.3390/jcm10071425
Received: 23 February 2021 / Revised: 14 March 2021 / Accepted: 23 March 2021 / Published: 1 April 2021
The digital transformation of healthcare is advancing, leading to an increasing availability of clinical data for research. Perioperative big data initiatives were established to monitor treatment quality and benchmark outcomes. However, big data analyses have long exceeded the status of pure quality surveillance instruments. Large retrospective studies nowadays often represent the first approach to new questions in clinical research and pave the way for more expensive and resource intensive prospective trials. As a consequence, the utilization of big data in acute pain and regional anesthesia research has considerably increased over the last decade. Multicentric clinical registries and administrative databases (e.g., healthcare claims databases) have collected millions of cases until today, on which basis several important research questions were approached. In acute pain research, big data was used to assess postoperative pain outcomes, opioid utilization, and the efficiency of multimodal pain management strategies. In regional anesthesia, adverse events and potential benefits of regional anesthesia on postoperative morbidity and mortality were evaluated. This article provides a narrative review on the growing importance of big data for research in acute postoperative pain and regional anesthesia. View Full-Text
Keywords: anesthesia; anesthesiology; big data; registries; database research; acute pain; pain management; postoperative pain; regional anesthesia; regional analgesia anesthesia; anesthesiology; big data; registries; database research; acute pain; pain management; postoperative pain; regional anesthesia; regional analgesia
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MDPI and ACS Style

Müller-Wirtz, L.M.; Volk, T. Big Data in Studying Acute Pain and Regional Anesthesia. J. Clin. Med. 2021, 10, 1425. https://doi.org/10.3390/jcm10071425

AMA Style

Müller-Wirtz LM, Volk T. Big Data in Studying Acute Pain and Regional Anesthesia. Journal of Clinical Medicine. 2021; 10(7):1425. https://doi.org/10.3390/jcm10071425

Chicago/Turabian Style

Müller-Wirtz, Lukas M., and Thomas Volk. 2021. "Big Data in Studying Acute Pain and Regional Anesthesia" Journal of Clinical Medicine 10, no. 7: 1425. https://doi.org/10.3390/jcm10071425

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