Bala G. Nair

Feedback Mechanisms Including Real-Time Electronic Alerts to Achieve Near 100% Timely Prophylactic Antibiotic Administration in Surgical Cases

BACKGROUND: Administration of prophylactic antibiotics during surgery is generally performed by the anesthesia providers. Timely antibiotic administration within the optimal time window before incision is critical for prevention of surgical site infections. However, this often becomes a difficult task for the anesthesia team during the busy part of a case when the patient is being anesthetized. METHODS: Starting with the implementation of an anesthesia information management system (AIMS), we designed and implemented several feedback mechanisms to improve compliance of proper antibiotic delivery and documentation. This included generating e-mail feedback of missed documentation, distributing monthly summary reports, and generating real-time electronic alerts with a decision support system. RESULTS: In 20,974 surgical cases for the period, June 2008 to January 2010, the interventions of AIMS install, e-mail feedback, summary reports, and real-time alerts changed antibiotic compliance by −1.5%, 2.3%, 4.9%, and 9.3%, respectively, when compared with the baseline value of 90.0% ± 2.9% when paper anesthesia records were used. Highest antibiotic compliance was achieved when using real-time alerts. With real-time alerts, monthly compliance was >99% for every month between June 2009 and January 2010. CONCLUSIONS: Installation of AIMS itself did not improve antibiotic compliance over that achieved with paper anesthesia records. However, real-time guidance and reminders through electronic messages generated by a computerized decision support system (Smart Anesthesia Messenger, or SAM) significantly improved compliance. With such a system a consistent compliance of >99% was achieved.

Anesthesia information management system-based near real-time decision support to manage intraoperative hypotension and hypertension

BACKGROUND:Intraoperative hypotension and hypertension are associated with adverse clinical outcomes and morbidity. Clinical decision support mediated through an anesthesia information management system (AIMS) has been shown to improve quality of care. We hypothesized that an AIMS-based clinical decision support system could be used to improve management of intraoperative hypotension and hypertension. METHODS:A near real-time AIMS-based decision support module, Smart Anesthesia Manager (SAM), was used to detect selected scenarios contributing to hypotension and hypertension. Specifically, hypotension (systolic blood pressure <80 mm Hg) with a concurrent high concentration (>1.25 minimum alveolar concentration [MAC]) of inhaled drug and hypertension (systolic blood pressure >160 mm Hg) with concurrent phenylephrine infusion were detected, and anesthesia providers were notified via “pop-up” computer screen messages. AIMS data were retrospectively analyzed to evaluate the effect of SAM notification messages on hypotensive and hypertensive episodes. RESULTS:For anesthetic cases 12 months before (N = 16913) and after (N = 17132) institution of SAM messages, the median duration of hypotensive episodes with concurrent high MAC decreased with notifications (Mann Whitney rank sum test, P = 0.031). However, the reduction in the median duration of hypertensive episodes with concurrent phenylephrine infusion was not significant (P = 0.47). The frequency of prolonged episodes that lasted >6 minutes (sampling period of SAM), represented in terms of the number of cases with episodes per 100 surgical cases (or percentage occurrence), declined with notifications for both hypotension with >1.25 MAC inhaled drug episodes (&dgr; = −0.26% [confidence interval, −0.38% to −0.11%], P < 0.001) and hypertension with phenylephrine infusion episodes (&dgr; = −0.92% [confidence interval, −1.79% to −0.04%], P = 0.035). For hypotensive events, the anesthesia providers reduced the inhaled drug concentrations to <1.25 MAC 81% of the time with notifications compared with 59% without notifications (P = 0.003). For hypertensive episodes, although the anesthesia providers’ reduction or discontinuation of the phenylephrine infusion increased from 22% to 37% (P = 0.030) with notification messages, the overall response was less consistent than the response to hypotensive episodes. CONCLUSIONS:With automatic acquisition of arterial blood pressure and inhaled drug concentration variables in an AIMS, near real-time notification was effective in reducing the duration and frequency of hypotension with concurrent >1.25 MAC inhaled drug episodes. However, since phenylephrine infusion is manually documented in an AIMS, the impact of notification messages was less pronounced in reducing episodes of hypertension with concurrent phenylephrine infusion. Automated data capture and a higher frequency of data acquisition in an AIMS can improve the effectiveness of an intraoperative clinical decision support system.

Reducing wastage of inhalation anesthetics using real-time decision support to notify of excessive fresh gas flow.

Background:Reduced consumption of inhalation anesthetics can be safely achieved by reducing excess fresh gas flow (FGF). In this study the authors describe the use of a real-time decision support tool to reduce excess FGF to lower, less wasteful levels. Method:The authors applied a decision support tool called the Smart Anesthesia Manager™ (University of Washington, Seattle, WA) that analyzes real-time data from an Anesthesia Information Management System to notify the anesthesia team if FGF exceeds 1 l/min. If sevoflurane consumption reached 2 minimum alveolar concentration-hour under low flow anesthesia (FGF < 2 l/min), a second message was generated to increase FGF to 2 l/min, to comply with Food and Drug Administration guidelines. To evaluate the tool, mean FGF between surgical incision and the end of procedure was compared in four phases: (1) a baseline period before instituting decision rules, (2) Intervention-1 when decision support to reduce FGF was applied, (3) Intervention-2 when the decision rule to reduce flow was deliberately inactivated, and (4) Intervention-3 when decision rules were reactivated. Results:The mean ± SD FGF reduced from 2.10 ± 1.12 l/min (n = 1,714) during baseline to 1.60 ± 1.01 l/min (n = 2,232) when decision rules were instituted (P < 0.001). When the decision rule to reduce flow was inactivated, mean FGF increased to 1.87 ± 1.15 l/min (n = 1,732) (P < 0.001), with an increasing trend in FGF of 0.1 l/min/month (P = 0.02). On reactivating the decision rules, the mean FGF came down to 1.59 ± 1.02 l/min (n = 1,845). Through the Smart Anesthesia Messenger™ system, the authors saved 9.5 l of sevoflurane, 6.0 l of desflurane, and 0.8 l isoflurane per month, translating to an annual savings of

Smart Anesthesia Manager

104,916. Conclusions:Real-time notification is an effective way to reduce inhalation agent usage through decreased excess FGFs.

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Anesthesia information management systems (AIMS) are being increasingly used in the operating room to document anesthesia care. We developed a system, Smart Anesthesia ManagerTM (SAM) that works in conjunction with an AIMS to provide clinical and billing decision support. SAM interrogates AIMS database in near real time, detects issues related to clinical care, billing and compliance, and material waste. Issues and the steps for their resolution are brought to the attention of the anesthesia provider in real time through “pop-up” messages overlaid on top of AIMS screens or text pages. SAM improved compliance to antibiotic initial dose and redose to 99.3 ± 0.7% and 83.9 ± 3.4% from 88.5 ± 1.4% and 62.5 ± 1.6%, respectively. Beta-blocker protocol compliance increased to 94.6 ± 3.5% from 60.5 ± 8.6%. Inadvertent gaps (>;15 min) in blood pressure monitoring were reduced to 34 ± 30 min/1000 cases from 192 ± 58 min/1000 cases. Additional billing charge capture of invasive lines procedures worth

(SAM)—A Real-time Decision Support System for Anesthesia Care during Surgery

144,732 per year and 1,200 compliant records were achieved with SAM. SAM was also able to reduce wastage of inhalation anesthetic agents worth

A System for Anesthesia Drug Administration Using Barcode Technology: The Codonics Safe Label System and Smart Anesthesia Manager.

120,168 per year.

Improving Documentation of a Beta-Blocker Quality Measure Through an Anesthesia Information Management System and Real-Time Notification of Documentation Errors

BACKGROUND:Many anesthetic drug errors result from vial or syringe swaps. Scanning the barcodes on vials before drug preparation, creating syringe labels that include barcodes, and scanning the syringe label barcodes before drug administration may help to prevent errors. In contrast, making syringe labels by hand that comply with the recommendations of regulatory agencies and standards-setting bodies is tedious and time consuming. A computerized system that uses vial barcodes and generates barcoded syringe labels could address both safety issues and labeling recommendations. METHODS:We measured compliance of syringe labels in multiple operating rooms (ORs) with the recommendations of regulatory agencies and standards-setting bodies before and after the introduction of the Codonics Safe Label System (SLS). The Codonics SLS was then combined with Smart Anesthesia Manager software to create an anesthesia barcode drug administration system, which allowed us to measure the rate of scanning syringe label barcodes at the time of drug administration in 2 cardiothoracic ORs before and after introducing a coffee card incentive. Twelve attending cardiothoracic anesthesiologists and the OR satellite pharmacy participated. RESULTS:The use of the Codonics SLS drug labeling system resulted in >75% compliant syringe labels (95% confidence interval, 75%–98%). All syringe labels made using the Codonics SLS system were compliant. The average rate of scanning barcodes on syringe labels using Smart Anesthesia Manager was 25% (730 of 2976) over 13 weeks but increased to 58% (956 of 1645) over 8 weeks after introduction of a simple (coffee card) incentive (P < 0.001). CONCLUSIONS:An anesthesia barcode drug administration system resulted in a moderate rate of scanning syringe label barcodes at the time of drug administration. Further, adaptation of the system will be required to achieve a higher utilization rate.

Associations between Age and Dosing of Volatile Anesthetics in 2 Academic Hospitals

BACKGROUND Continuation of perioperative beta-blockers for surgical patients who are receiving beta-blockers prior to arrival for surgery is an important quality measure (SCIP-Card-2). For this measure to be considered successful, name, date, and time of the perioperative beta-blocker must be documented. Alternately, if the beta-blocker is not given, the medical reason for not administering must be documented. METHODS Before the study was conducted, the institution lacked a highly reliable process to document the date and time of self-administration of beta-blockers prior to hospital admission. Because of this, compliance with the beta-blocker quality measure was poor (-65%). To improve this measure, the anesthesia care team was made responsible for documenting perioperative beta-blockade. Clear documentation guidelines were outlined, and an electronic Anesthesia Information Management System (AIMS) was configured to facilitate complete documentation of the beta-blocker quality measure. In addition, real-time electronic alerts were generated using Smart Anesthesia Messenger (SAM), an internally developed decision-support system, to notify users concerning incomplete beta-blocker documentation. RESULTS Weekly compliance for perioperative beta-blocker documentation before the study was 65.8 +/- 16.6%, which served as the baseline value. When the anesthesia care team started documenting perioperative beta-blocker in AIMS, compliance was 60.5 +/- 8.6% (p = .677 as compared with baseline). Electronic alerts with SAM improved documentation compliance to 94.6 +/- 3.5% (p < .001 as compared with baseline). CONCLUSIONS To achieve high compliance for the beta-blocker measure, it is essential to (1) clearly assign a medical team to perform beta-blocker documentation and (2) enhance features in the electronic medical systems to alert the user concerning incomplete documentation.

A novel computerized fading memory algorithm for glycemic control in postoperative surgical patients.

BACKGROUND:The inverse relationship between age and dose requirement for potent volatile anesthetics is well established, but the question of whether anesthetic providers consider this relationship in practice remains unanswered. We sought to determine whether there is an association between patient age and the mean dose of volatile anesthetic delivered during maintenance of anesthesia. METHODS:This was a retrospective cross-sectional study of patients receiving a single potent volatile anesthetic at 2 academic hospitals using data recorded in an anesthesia information management system. Multivariate linear models were constructed at each hospital to examine the relationship between age and mean minimum alveolar concentration (MAC) fraction delivered during the maintenance of anesthesia. RESULTS:A total of 7878 cases at the 2 hospitals were included for analysis. For patients aged <65 years, we observed decreasing doses of volatile anesthetics as age increased. Per decade, mean delivered MAC fraction decreased by an estimated 1.8% (95% confidence interval, 1.5–2.2, P < 0.0001), smaller than the 6.7% decrease suggested by previous studies of human anesthetic requirements. At age >65 years, the magnitude of the inverse association between age and MAC fraction was higher (3.8% decrease per decade; 95% confidence interval, 2.9–4.7). CONCLUSIONS:Increasing age is associated with decreased absolute doses of potent volatile anesthetics, an association that seems to strengthen as patients enter the geriatric age range. The observed decreases in absolute anesthetic dose were less than those predicted by previous research and therefore represent an overall increase in “age-adjusted dose” as patients grow older.