Anesthesiology & Pain Medicine >> Research >> Centers >> AIMS Research
Dr. Stefan Lombaard teaches residents in simulation lab
Dr. Bala Nair demonstrating the Smart Anesthesia Messenger (SAM™) at the UW Medical Center surgery pavilion.

AIMS Research:
Anesthesia Information
Management System
Research Group

What is AIMS Research?

The Anesthesia Information Management System (AIMS) Research Group conducts practical research on improving perioperative patient safety and quality of care using electronic tools.

Areas of Interest

Smart Anesthesia ManagerTM - SAM
Adding Intelligence to Anesthesia Information Management Systems

What is SAM?

SAM (Smart Anesthesia Manager™) is a software package developed by University of Washington that works in parallel with an Anesthesia Information Management System (AIMS). The primary function of SAM is to provide real-time decision support and guidance to anesthesia providers. It obtains near real-time data from AIMS and finds issues related to quality of care, patient safety, billing and compliance. Ongoing issues are notified to the anesthesia providers with directions to resolve them. The notification is either in the form of “pop-up” messages overlaid on top on the AIMS screen or text pages. Additionally, SAM provides point of care tools to determine the correct billing codes, provide barcode confirmation of medications and facilitate safe patient handoff.

SAM overview

Why real-time decision support?

During a surgical procedure, an anesthesia provider performs the important tasks of keeping the patient safely anesthetized and physiologically stable. This involves concurrent real-time interpretation and execution of several steps in parallel, including adequately maintaining physiological parameters, ventilating the patient, administering anesthetic drugs and maintaining fluid balance –all in response to anesthesia (physiological changes), ongoing surgery (blood loss) and patient responses (heart function). To execute these simultaneous steps, the anesthesia provider has to efficiently and effectively capture and disseminate information from multiple devices and systems, and make rapid decisions and interventions that are based on best practice and evidence. In addition, the anesthesia provider also keeps documentation of patient care steps in an anesthesia record, which serves as the primary medical legal and billing document for anesthesia care. Due to the complexity of anesthesia care and the rapid-pace in an operating room, oversights and errors, such as delayed (or even missed) administration of needed medication or delayed correction of anesthesia problems, are not infrequent.

Real-time detection and notification of clinical issues has been shown to be highly effective in improving patient safety, quality of care, revenue capture and waste reduction by University of Washington and several other institutions. Real-time decision support significantly improves vigilance of the anesthesia provider in a high data velocity environment (Operating room) prone to multiple distractions.


  • Real-time decision support system for the operating room
  • >99% compliant SCIP (Surgical Care Improvement Project—The Joint Commission) measures (Antibiotic delivery, β-blocker management)
  • Near 100% revenue capture related to Invasive lines and 1-lung ventilation
  • Near 100% CMS (Medicare) compliance by ensuring complete and correct documentation
  • Improved patient safety
    • reduced gaps in BP monitoring,
    • fewer unsafe hypo and hypertension events,
    • voice confirmation of medication administration
  • Improved adherence to institutional protocols:
    • Glucose management (improvement by 100%),
    • Traumatic Brain Injury Care
    • Postoperative Nausea & Vomiting prophylaxis (in development)
  • Reduced wastage of inhalational agents through lower Fresh Gas Flow (~ 30% reduction)
  • Barcode confirmation of medication delivery
  • Hand off tool for safe patient transfer between providers
  • Framework for implementing, following and auditing checklists
  • Coding utility to find Anesthesia Crosswalk codes with the best RVU
  • Communication tool

Improvements with SAM seen at UW Medical Center:

SAM highlights

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Example SAM features:

Decision Support tool

SAM improvements

Glucose management tool

SAM features

Anesthesia crosswalk Search Tool

SAM features

Voice confirmation of bar-coded drug delivery

SAM features

Handoff tool

SAM features

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Comparison of SAM and AIMS Decision Support features

SAM & AIMS comparison

Grant Support:

Ongoing Research Support:

  • Coulter Foundation, Evaluation of Smart Anesthesia Manager™ (SAM) Integrated with Multiple Anesthesia Information Systems to Deliver Real-time Decision Support and Guidance.
    • Integration of SAM with two additional Anesthesia systems
    • PI: Bala G. Nair, PhD   
  • NIH /R01 NS072308-01 Implementation Science to Increase Use of Evidence Based Pediatric Brain Injury Guidelines.
    • Support for development and implementation of decision support and guidance in SAM for traumatic brain injury protocol
    • PI: Monica Vavilala, MD
  • Anesthesia Patient Safety Foundation (APSF), “Study of the Implementation and Performance of the APSF Pre-Anesthetic Induction Patient Safety (PIPS) Checklist”
    • Support for development and implementation of checklists in SAM
    • PI: T. Andrew Bowdle, MD, PhD

Completed Research Support:

  • Laura Cheney Patient Safety Award, University of Washington, “Improving patient safety with SAM”
    • Development of blood pressure management decision support in SAM
    • PI: Bala G. Nair, PhD   
  • Technology Gap Innovation Fund (TGIF), UW Technologies, “Smart Anesthesia Messenger (SAM)”
    • Development of rules builder engine in SAM
    • PI: Bala G. Nair, PhD   
  • Patient Safety Innovation Fund (PSIP), UW Medicine, “Improving Intraoperative Glycemic Control Using a Real-time Decision Support System”,
    • Development of decision support for glucose management in SAM
    • PI: Bala G. Nair, PhD

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  1. Nair B, Grunzweig K, Peterson GN, Horibe M, Neradilek MB, Newman S, Van Norman G, Schwid HA, Hao W, Hirsch IB, Dellinger PE; Intraoperative Blood Glucose Management: Impact of a Real-Time Decision Support System on Adherence to Institutional Protocol. 2014 (pub ahead of print J Clin Monit Comput). Impact Factor: 1.7
  2. Jelacic S, Bowdle A, Nair BG, Kusulos D, Bower L, Togashi K; A Safety System for Anesthesia Drug Administration Using Barcode Technology: The Codonics Safe Label System and Smart Anesthesia Manager. Anesthesia & Analgesia 121(2):410-21; 2015. Impact Factor: 3.1
  3. Nair BG, Horibe M, Newman S, Wu W, Peterson GN, Schwid HA. AIMS-based Near Real-time Decision Support to Manage Intraoperative Hypotension and Hypertension. Anesth Analg 118(1):206-14; 2014. Impact Factor: 3.1
  4. Nair BG, Horibe M, Newman S, Wu W, Schwid HA; Near Real-time Notification of Gaps in Cuff Blood Pressure Recordings for Improved Patient Monitoring. J Clin Monit Comput. 27(3):265-71; 2013. Impact Factor: 1.7
  5. Nair BG, Peterson GN, Neradilek MB, Newman SF, Huang EY, Schwid HA. Reducing Wastage of Inhalation Anesthetics using Real-time Decision Support to Notify of Excessive Fresh Gas Flow. Anesthesiology 118(4):874-84; 2013. Impact Factor: 5.4
  6. Nair BG, Newman SF, Peterson GN, Schwid HA; Smart Anesthesia Manager™ - A Real-time Decision Support System for Anesthesia Care during Surgery. IEEE Trans Biomed Eng. 60(1):207-10; 20132012. Impact Factor: 2.3
  7. Nair BG, Peterson GN, Newman S, Wu W, Schwid HA; Improved Documentation of β-blocker Quality Measure through Anesthesia Information Management System and Real-time Notification of
    Documentation Errors. Jt Comm J Qual Patient Saf. 38(6):283-8; 2012. Impact Factor: 2.4
  8. Nair BG, Newman SF, Peterson GN, Schwid HA; Automated electronic reminders to improve redosing of antibiotics during surgical cases: comparison of two approaches. Surg Infect; 12(1):57-63; 2011. Impact Factor: 1.8
  9. Nair BG, Newman S, Peterson GN, Wu W, Schwid HA; Feedback Mechanisms Including Real-Time Electronic Alerts to Achieve Near 100% Timely Prophylactic Antibiotic Administration in Surgical Cases. Anesthesia & Analgesia; 111(5):1293-1300; 2010. Impact Factor: 3.1

News articles:

  1. UW Medicine Magazine: Laura Cheney Patient Safety Award
  2. Anesthesiology News (National Magazine, February 2011)
  3. Anesthesiology News (National Magazine, May 2015)
  4. Anesthesiology News (National Magazine, June 2015)

Abstracts and Presentations:

  1. Development and Use of Smart Anesthesia Manager, An AIMS Based Real-Time Decision Support Module. Oral Presentation (invited). Society for Technology in Anesthesia Annual Meeting 2015. Phoenix, AZ
  2. Evaluation Of A Decision Support System To Improve Timely Perioperative Antibiotic Redosing And Charge Capture Of Invasive Line Placements. International Anesthesia Research Society Annual Meeting 2014. Poster presentation. Montréal, Canada
  3. Smart Anesthesia Monitor- A Real Time Rules Based Decision Support Tool for Anesthesia and Surgical Care.UHC Annual Meeting 2013, Oral presentation (invited), Atlanta, GA
  4. Smart Anesthesia Manager™. Real-time Decision Support: Bala G. Nair Ph.D (International Conference on Anesthesia & Perioperative Care, San Antonio, TX, Oral Presentation, 2012)
  5. Improved Patient Monitoring through Real-time Notification of Gaps in Cuff Blood Pressure Recordings: Bala G. Nair Ph.D, Shu-Fang Newman, M.S., Howard A. Schwid, M.D. (American Society of Anesthesiologists, Oral Presentation 2011)
  6. Wastage Reduction of Inhalation Agents through Real-time Notification of Excess Fresh Gas Flow Bala G. Nair Ph.D, Gene N. Peterson, M.D., Ph.D., Shu-Fang Newman, M.S., Howard A. Schwid, M.D. (American Society of Anesthesiologists, Poster Presentation 2011)
  7. Improved billing of invasive line procedures through real-time notification of documentation errors: Bala G. Nair Ph.D, Shu-Fang Newman, M.S., Howard A. Schwid, M.D. (American Society of Anesthesiologists, Oral Presentation 2010)

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