What is the clinical evidence from this study?

Study design: Review. Population: Perioperative care and anesthesiology. Intervention: Artificial intelligence and telemedicine.

What does this research mean for the field?

Artificial intelligence and telemedicine show promising potential to significantly influence all phases of perioperative care and aid in developing precision medicine in anesthesiology, despite remaining implementation hurdles. Novelty: ClaimNovelty.SYNTHESIS. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

To examine current clinical applications, operational advantages, and implementation barriers of artificial intelligence and telemedicine across all stages of perioperative anesthesiology care.

February 15, 2022Minerva Anestesiologica

Artificial intelligence and telemedicine in anesthesia: potential and problems

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Key result

AI and telemedicine show potential to influence perioperative care and advance precision medicine despite hurdles.

Why the study?

Novel technologies like artificial intelligence, machine learning, and telemedicine could transform health care, but their current applications, potential influence, and hurdles in anesthesiology and perioperative care warrant review.

Design

Review

Authors

VBValentina BelliniUniversity of Parma MVMarina ValenteUniversity of Parma AGA. GaddiSocietà Italiana di Fisica

Discussion

Member takes

Implication

Should not yet alter perioperative practice; leaves open need for prospective validation of AI and telemedicine.

Key Points

To examine current clinical applications, operational advantages, and implementation barriers of artificial intelligence and telemedicine across all stages of perioperative anesthesiology care.
Narrative review synthesizing evidence on the application of artificial intelligence, machine learning, and telemedicine across preoperative, intraoperative, and postoperative workflows.
Artificial intelligence models optimize perioperative care by enhancing individual risk prediction, streamlining operating room management, and improving cost-effectiveness.
Telemedicine facilitates critical anesthetic touchpoints, including virtual preoperative evaluations, continuous remote patient tracking, and specialized postoperative follow-up.
Significant technical, systemic, and workflow hurdles currently restrict the seamless integration of these technologies into standard daily practice.

Structured PICO

Intervention

Artificial intelligence (AI), machine learning (ML), and telemedicine

AI and telemedicine show promise in transforming perioperative care and anesthesiology, though implementation hurdles remain.

Limitations

Several hurdles remain to be overcome before these tools could be integrated in daily practice

Cite This Study

Bellini et al. (2022) conducted a review in Perioperative care and anesthesiology. Artificial intelligence and telemedicine was evaluated. Artificial intelligence and telemedicine show promising potential to significantly influence all phases of perioperative care and aid in developing precision medicine, despite remaining hurdles.

synapsesocial.com/papers/6a12ec1f45487b7639a765de https://doi.org/10.23736/s0375-9393.21.16241-8

Topics

Artificial intelligence in cardiology

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Artificial intelligence and telemedicine in anesthesia: potential and problems

Discussion

Member takes

Implication

Key Points

Structured PICO

Limitations

Cite This Study

Topics

Artificial intelligence and telemedicine in anesthesia: potential and problems

Discussion

Member takes

Implication

Key Points

Structured PICO

Limitations

Cite This Study

Also Consider

Topics

Also Consider