The Anesthesia Informatics Research group has long been a leader in Anesthesia Information Management System (AIMS) implementation and research. The Department of Anesthesiology was among the first to implement an AIMS in the early 1990s, and since then we have been on the forefront of utilizing anesthesia data for sophisticated administrative and research functions. In the past several years our effort has been focused on creating an integrated data warehouse that combines intraoperative physiologic data with perioperative clinical and administrative data to create a single source for large scale data mining. Current projects include multi-disciplinary efforts to examine the role of genetics in response to common anesthetic drugs and to apply "big data" analysis techniques to intraoperative physiologic data. We also continue to provide support for departmental clinical and administrative activities.
Perioperative Genomics Program
The Department of Anesthesiology has partnered with the Charles Bronfman Institute for Personalized Medicine (IPM) to develop a program in Perioperative Genomics. This new initiative led by cardiac anesthesiologist Matthew A Levin, MD brings together high-resolution intraoperative physiologic data with high resolution genotype data to enable novel research on the phenotype and genotype of the response to anesthetic and surgical stress. These data sources are unified via iGAS1 – an automated pipeline that links the Department’s perioperative data warehouse to BioMe.
BioMe is the IPM’s electronic medical record-linked biobank that enables researchers to rapidly and efficiently conduct genetic, epidemiologic, molecular, and genomic studies on large collections of research specimens linked with medical information. BioMe has enrolled over 38,000 patients, over 19,000 of who have collectively undergone nearly 54,000 anesthetics. Genotype data has been generated for approximately 73% of the patients who have had anesthetics. Several studies are underway to characterize the genomics of intraoperative drug response and of vasoplegia – a state of refractory hypotension sometimes seen after cardiopulmonary bypass.
The program is actively seeking anesthesiologists with experience and interest in perioperative genomics to join our research.
Recognition and Publications
Our research has been recognized by industry organizations and published in academic journals.
Wax DB, Hill B, Levin MA. Ventilator Data Extraction with a Video Display Image Capture and Processing System. J Med Syst. 2017 Jun;41(6):101. doi: 10.1007/s10916-017-0751-2. Epub 2017 May 20. PMID: 28526944
Levin MA, Joseph TT, Jeff JM, Nadukuru R, Ellis SB, Bottinger EP, Kenny EE. iGAS: A framework for using electronic intraoperative medical records for genomic discovery. J Biomed Inform. 2017 Mar;67:80-89. doi: 10.1016/j.jbi.2017.02.005. Epub 2017 Feb 11. PMID:28193464
Wax DB, McCormick PJ. A Real-Time Decision Support System for Anesthesiologist End-of-Shift Relief. Anesth Analg. 2017 Feb;124(2):599-602. doi: 10.1213/ANE.0000000000001515. PMID: 27861437
Wax DB, Feit JB. Accuracy of Vasopressor Documentation in Anesthesia Records. J Cardiothorac Vasc Anesth. 2016 Jun;30(3):656-8. doi: 10.1053/j.jvca.2015.10.020. Epub 2015 Nov 2. PMID: 26796248
Levin MA, Wanderer JP, Ehrenfeld JM. Data, Big Data, and Metadata in Anesthesiology. Anesth Analg. 2015 Dec;121(6):1661-7. doi: 10.1213/ANE.0000000000000716. PMID: 26579664
Our group maintains the following facilities for the Department of Anesthesiology:
- Department of Anesthesiology IT infrastructure (LAN, servers, workstations)
- Anesthesia Information Management Systems (CompuRecord and EPIC)
- Departmental Research Data Warehouse
- ORwatch (a web-based real-time tool for perioperative management and monitoring)
Our team is made up of the following Department of Anesthesiology faculty and staff.
IT Technical Engineer