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 (δ = -0.26% [confidence interval, -0.38% to -0.11%], P < 0.001) and hypertension with phenylephrine infusion episodes (δ = -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.

Near real-time notification of gaps in cuff blood pressure recordings for improved patient monitoring.

Blood pressure monitoring during anesthesia is an American Society of Anesthesiology standard. However, the anesthesia provider sometimes fails to engage the patient monitor to make periodic (generally every 3-5 min) measurements of Non-Invasive Blood Pressure (NIBP), which can lead to extended periods (>5 min) when blood pressure is not monitored. We describe a system to automatically detect such gaps in NIBP measurement and notify clinicians in real-time to initiate measurement. We applied a decision support system called the Smart Anesthesia Messenger (SAM) to notify the anesthesia provider if NIBP measurements have not been made in the last 7 min. Notification messages were generated only if direct arterial blood pressure was not being monitored. NIBP gaps were analyzed for 9 months before and after SAM notification was initiated (12,000 cases for each period). SAM notification was able to reduce the occurrence of extended NIBP gaps >15 min from 15.7 ± 4.5 to 6.7 ± 2.0 instances per 1,000 cases (p < 0.001). In addition, for extended gaps (>15 min) the mean gap duration declined from 23.1 ± 2.0 to 18.6 ± 1.1 min after SAM notification was initiated (p < 0.001). However, for 7-15 min gaps, SAM notification was not effective in reducing the occurrence. The maximum gap encountered before SAM was 64 min, while it was 27 min with SAM notification. Real-time notification using SAM is an effective way to reduce both the number of instances and the duration of inadvertent, extended (>15 min) gaps in blood pressure measurements in the operating room. However, the frequency of gaps <15 min could not be reduced using the current configuration of SAM.

Improving documentation of a beta-blocker quality measure through an anesthesia information management system and real-time notification of documentation errors.

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.

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.