Key result
Big Data and large registries offer anesthesiology a way to explore rare perioperative complications and outcomes to encourage further hypotheses testing.
Big Data and large registries in anesthesiology provide valuable insights into rare perioperative complications and outcomes, despite methodological and security challenges.
Registry data may generate hypotheses on rare perioperative events; leaves open clinical translation without prospective validation.
PURPOSE OF REVIEW: This narrative review will discuss what value Big Data has to offer anesthesiology and aims to highlight recently published articles of large databases exploring factors influencing perioperative outcome. Additionally, the future perspectives of Big Data and its major pitfalls will be discussed. RECENT FINDINGS: The potential of Big Data has given an incentive to create nationwide and anesthesia-initiated registries like the MPOG and NACOR. These large databases have contributed in elucidating some of the rare perioperative complications, such as declined cognition after exposure to general anesthesia and epidural hematomas in parturients. Additionally, they are useful in finding patterns such as similar outcome in subtypes of beta-blockers and lower incidence of pneumonia in preoperative influenza vaccinations in the elderly. SUMMARY: Big Data is becoming increasingly popular with the collaborative collection of registries offering anesthesia a way to explore rare perioperative complications and outcome to encourage further hypotheses testing. Although Big Data has its flaws in security, lack of expertise and methodological concerns, the future potential of analytics combined with genomics, machine learning and real-time decision support looks promising.
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Liem et al. (2018) conducted a review in Perioperative complications. Big Data analytics was evaluated. Big Data and large registries offer anesthesiology a way to explore rare perioperative complications and outcomes to encourage further hypotheses testing.
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