Anesthesiology Performance Improvement and Reporting Exchange (ASPIRE) Quality Metrics in Patients Undergoing Decompressive Craniectomy and Endoscopic Clot Evacuation after Spontaneous Supratentorial Intracerebral Hemorrhage: A Retrospective Observational Study.

BACKGROUND: We report adherence to 6 Anesthesiology Performance Improvement and Reporting Exchange (ASPIRE) quality metrics (QMs) relevant to patients undergoing decompressive craniectomy or endoscopic clot evacuation after spontaneous supratentorial intracerebral hemorrhage (sICH). METHODS: In this retrospective observational study, we describe adherence to the following ASPIRE QMs: acute kidney injury (AKI-01); mean arterial pressure < 65 mm Hg for less than 15 minutes (BP-03); myocardial injury (CARD-02); treatment of high glucose (> 200 mg/dL, GLU-03); reversal of neuromuscular blockade (NMB-02); and perioperative hypothermia (TEMP-03). RESULT: The study included 95 patients (70% male) with median (interquartile range) age 55 (47 to 66) years and ICH score 2 (1 to 3) undergoing craniectomy (n=55) or endoscopic clot evacuation (n=40) after sICH. In-hospital mortality attributable to sICH was 23% (n=22). Patients with American Society of Anesthesiologists physical status class 5 (n=16), preoperative reduced glomerular filtration rate (n=5), elevated cardiac troponin (n=21) and no intraoperative labs with high glucose (n=71), those who were not extubated at the end of the case (n=62) or did not receive a neuromuscular blocker given (n=3), and patients having emergent surgery (n=64) were excluded from the analysis for their respective ASPIRE QM based on predetermined ASPIRE exclusion criteria. For the remaining patients, the adherence to ASPIRE QMs were: AKI-01, craniectomy 34%, endoscopic clot evacuation 1%; BP-03, craniectomy 72%, clot evacuation 73%; CARD-02, 100% for both groups; GLU-03, craniectomy 67%, clot evacuation 100%; NMB-02, clot evacuation 79%, and; TEMP-03, clot evacuation 0% with hypothermia. CONCLUSION: This study found variable adherence to ASPIRE QMs in sICH patients undergoing decompressive craniectomy or endoscopic clot evacuation. The relatively high number of patients excluded from individual ASPIRE metrics is a major limitation.

A Machine Learning Approach for Predicting Real-time Risk of Intraoperative Hypotension in Traumatic Brain Injury.

BACKGROUND: Traumatic brain injury (TBI) is a major cause of death and disability. Episodes of hypotension are associated with worse TBI outcomes. Our aim was to model the real-time risk of intraoperative hypotension in TBI patients, compare machine learning and traditional modeling techniques, and identify key contributory features from the patient monitor and medical record for the prediction of intraoperative hypotension. METHODS: The data included neurosurgical procedures in 1005 TBI patients at an academic level 1 trauma center. The clinical event was intraoperative hypotension, defined as mean arterial pressure <65 mm Hg for 5 or more consecutive minutes. Two types of models were developed: one based on preoperative patient-level predictors and one based on intraoperative predictors measured per minute. For each of these models, we took 2 approaches to predict the occurrence of a hypotensive event: a logistic regression model and a gradient boosting tree model. RESULTS: The area under the receiver operating characteristic curve for the intraoperative logistic regression model was 0.80 (95% confidence interval [CI]: 0.78-0.83), and for the gradient boosting model was 0.83 (95% CI: 0.81-0.85). The area under the precision-recall curve for the intraoperative logistic regression model was 0.16 (95% CI: 0.12-0.20), and for the gradient boosting model was 0.19 (95% CI: 0.14-0.24). Model performance based on preoperative predictors was poor. Features derived from the recent trend of mean arterial pressure emerged as dominantly predictive in both intraoperative models. CONCLUSIONS: This study developed a model for real-time prediction of intraoperative hypotension in TBI patients, which can use computationally efficient machine learning techniques and a streamlined feature-set derived from patient monitor data.

Association between acute phase perioperative glucose parameters and postoperative outcomes in diabetic and non-diabetic patients undergoing non-cardiac surgery.

BACKGROUND: The relationship between acute phase perioperative hyperglycemia and postoperative outcome is poorly understood. METHODS: Retrospective cohort study of diabetic and non-diabetic adult patients undergoing non-cardiac surgery. Mean glucose and glycemic variability during the intraoperative and immediate postoperative periods were compared to length of stay, 30-day mortality, and postoperative complications. RESULTS: . DIABETIC PATIENTS (N = 1096): Higher glycemic variability was associated with longer hospital length of stay (0.32 day per 10 mg/dL) and greater 30-day mortality risk (OR = 1.42). Higher mean glucose (OR = 1.07) and glycemic variability (OR = 1.11) were associated with higher risk of complications. NON-DIABETIC PATIENTS (N = 1012): Both higher mean glucose (0.29 day per 10 mg/dL) and higher glycemic variability (0.68 day per 10 mg/dL) were associated with longer hospital length of stay. Both higher mean glucose (OR = 1.13) and higher glycemic variability (OR = 1.21) were associated with greater risks of complications. CONCLUSIONS: Poor acute phase perioperative glycemic control is associated with poor outcome, but differently in diabetic and non-diabetic patients suggesting different glycemic management strategies for the two patient groups.

Explainable machine-learning predictions for the prevention of hypoxaemia during surgery.

Although anaesthesiologists strive to avoid hypoxemia during surgery, reliably predicting future intraoperative hypoxemia is not currently possible. Here, we report the development and testing of a machine-learning-based system that, in real time during general anaesthesia, predicts the risk of hypoxemia and provides explanations of the risk factors. The system, which was trained on minute-by-minute data from the electronic medical records of over fifty thousand surgeries, improved the performance of anaesthesiologists when providing interpretable hypoxemia risks and contributing factors. The explanations for the predictions are broadly consistent with the literature and with prior knowledge from anaesthesiologists. Our results suggest that if anaesthesiologists currently anticipate 15% of hypoxemia events, with this system's assistance they would anticipate 30% of them, a large portion of which may benefit from early intervention because they are associated with modifiable factors. The system can help improve the clinical understanding of hypoxemia risk during anaesthesia care by providing general insights into the exact changes in risk induced by certain patient or procedure characteristics.

Preoperative Low-Dose Aspirin Exposure and Outcomes After Emergency Neurosurgery for Traumatic Intracranial Hemorrhage in Elderly Patients.

BACKGROUND: Antiplatelet medications are usually discontinued before elective neurosurgery, but this is not an option for emergent neurosurgery. We performed a retrospective cohort study to examine whether preoperative aspirin use was associated with worse outcomes after emergency neurosurgery in elderly patients. METHODS: We analyzed all cases of emergency neurosurgical procedures for traumatic intracranial hemorrhage from 2008 to 2012 at a level 1 trauma center. Demographics, comorbidities, and outcomes were compared for patients ≥65 years by preoperative aspirin exposure. Exclusion criteria were: (1) polytrauma, (2) concomitant use of other preoperative anticoagulants or antiplatelet agents, (3) surgical indication other than subdural, extradural, or intraparenchymal hemorrhage, and (4) repeat neurosurgical procedures within a single admission. Estimated intraoperative blood loss, postprocedural intracranial bleeding requiring reoperation, death in hospital, intensive care unit, and hospital lengths of stay and perioperative blood product transfusion from 48 hours before 48 hours after surgery were the study outcomes. We also examined whether platelet transfusion had an impact on outcomes for patients on aspirin. RESULTS: The cohort included 171 patients. Patients receiving preoperative aspirin (n = 87, 95% taking 81 mg/day) were the same age as patients not receiving aspirin (n = 84; 78.3 ± 7.8 vs 75.9 ± 7.9 years, P > .05), had slightly higher admission Glasgow Coma Scale scores (12.8 ± 3.4 vs 11.4 ± 4, P = .02) and tended to have more coronary artery disease (P< .05). Adjusted for Glasgow Coma Scale and coronary artery disease, patients receiving preoperative aspirin had a higher odds of perioperative platelet transfusion (adjusted odds ratio 9.89, 95% confidence interval, 4.24-26.25). There were no other differences in outcomes between the 2 groups. Preoperative or intraoperative platelet transfusion was not associated with better outcomes among aspirin patients. CONCLUSIONS: In patients age ≥65 years undergoing emergency neurosurgery for traumatic intracranial hemorrhage, preoperative low-dose aspirin treatment was not associated with increased perioperative bleeding, hospital lengths of stay, or in-hospital mortality.

Methylprednisolone Therapy in Acute Traumatic Spinal Cord Injury: Analysis of a Regional Spinal Cord Model Systems Database.

BACKGROUND: The objective of this study was to assess the relationship between exposure to methylprednisolone (MP) and improvements in motor function among patients with acute traumatic spinal cord injury (TSCI). MP therapy for patients with TSCI is controversial because of the current conflicting evidence documenting its benefits and risks. METHODS: We conducted a retrospective cohort study from September 2007 to November 2014 of 311 patients with acute TSCI who were enrolled into a model systems database of a regional, level I trauma center. We linked outcomes and covariate data from the model systems database with MP exposure data from the electronic medical record. The primary outcomes were rehabilitation discharge in American Spinal Injury Association (ASIA) motor scores (sum of 10 key muscles bilaterally as per International Standards for Neurological Classification of Spinal Cord Injury, range, 0-100) and Functional Independence Measure (FIM) motor scores (range, 13-91). Secondary outcomes measured infection risk and gastrointestinal (GI) complications among MP recipients. For the primary outcomes, multivariable linear regression was used. RESULTS: There were 160 MP recipients and 151 nonrecipients. Adjusting for age, sex, weight, race, respective baseline motor score, surgical intervention, injury level, ASIA Impairment Scale (AIS) grade, education, and insurance status, there was no association with improvement in discharge ASIA motor function or FIM motor score among MP recipients: -0.34 (95% CI, -2.8, 2.1) and 0.75 (95% CI, -2.8, 4.3), respectively. Adjusting for age, sex, race, weight, injury level, and receipt of surgery, no association with increased risk of infection or GI complications was observed. CONCLUSIONS: This retrospective cohort study involving patients with acute TSCI observed no short-term improvements in motor function among MP recipients compared with nonrecipients. Our findings support current recommendations that MP use in this population should be limited.

Risks of Routinely Clamping External Ventricular Drains for Intrahospital Transport in Neurocritically Ill Cerebrovascular Patients.

BACKGROUND: Current guidelines recommend routine clamping of external ventricular drains (EVD) for intrahospital transport (IHT). The aim of this project was to describe intracranial hemodynamic complications associated with routine EVD clamping for IHT in neurocritically ill cerebrovascular patients. METHODS: We conducted a retrospective review of cerebrovascular adult patients with indwelling EVD admitted to the neurocritical care unit (NICU) during the months of September to December 2015 at a tertiary care center. All IHTs from the NICU of the included patients were examined. Main outcomes were incidence and risk factors for an alteration in intracranial pressure (ICP) and cerebral perfusion pressure after IHT. RESULTS: Nineteen cerebrovascular patients underwent 178 IHTs (79.8 % diagnostic and 20.2 % therapeutic) with clamped EVD. Twenty-one IHTs (11.8 %) were associated with post-IHT ICP ≥ 20 mmHg, and 33 IHTs (18.5 %) were associated with escalation of ICP category. Forty IHTs (26.7 %) in patients with open EVD status in the NICU prior to IHT were associated with IHT complications, whereas no IHT complications occurred in IHTs with clamped EVD status in the NICU. Risk factors for post-IHT ICP ≥ 20 mmHg were IHT for therapeutic procedures (adjusted relative risk [aRR] 5.82; 95 % CI, 1.76-19.19), pre-IHT ICP 15-19 mmHg (aRR 3.40; 95 % CI, 1.08-10.76), pre-IHT ICP ≥ 20 mmHg (aRR 12.94; 95 % CI, 4.08-41.01), and each 1 mL of hourly cerebrospinal fluid (CSF) drained prior to IHT (aRR 1.11; 95 % CI, 1.01-1.23). CONCLUSIONS: Routine clamping of EVD for IHT in cerebrovascular patients is associated with post-IHT ICP complications. Pre-IHT ICP ≥ 15 mmHg, increasing hourly CSF output, and IHT for therapeutic procedures are risk factors.

Decisional practices and patterns of intraoperative glucose management in an academic medical center.

OBJECTIVE: To understand the decisional practices of anesthesia providers in managing intraoperative glucose levels. DESIGN: This is a retrospective cohort study. SETTING: Operating rooms in an academic medical center. PATIENTS: Adult patients undergoing surgery. INTERVENTION: Intraoperative blood glucose management based on an institutional protocol. MEASUREMENTS: Glucose management data was extracted from electronic medical records to determine compliance to institutional glucose management protocol that prescribes hourly glucose measurements and insulin doses to maintain glucose levels between 100 to 140mg/dL. Effect of patient and surgery specific factors on compliance to glucose management protocol was explored. MAIN RESULTS: In 1903 adult patients compliances to hourly glucose measurements was 72.5% and correct insulin adjustments was 12.4%. Insulin was under-dosed compared to the prescribed value by a mean of 0.85U/h (95% CI 0.76-0.95). Multivariate analysis showed that compliance to hourly glucose measurements decreased with increasing length of the procedure (OR=0.92 per hour, 95% CI 0.89-0.95) but increased with ASA status codes (OR=1.25 per ASA unit, 95% CI=1.06-1.49). Greater compliance to correct insulin adjustment was found in diabetic patients compared with non-diabetic patients (OR=1.31, 95% CI 1.09-1.55). On average, providers administered progressively more insulin with an additional 0.11U/h (95% CI=0.00-0.21] for every additional 10kg/m(2) of BMI and 0.20U/h (95% CI=0.01-0.39) less in diabetic patients than in non-diabetic patients. With the above practice pattern, the mean±SD of glucose level was 158±36mg/dL. Hypoglycemic (<60mg/dL) incident rate was 0.1% (9/8301 measurements) while hyperglycemic (>180mg/dL) incident rate was 28%. Glucose levels were within the target range (100-140mg/dL) only 28% of the time. CONCLUSIONS: Low compliance and considerable variability in initiating and following institutional glucose management protocol were observed.

The Effect of Intraoperative Blood Glucose Management on Postoperative Blood Glucose Levels in Noncardiac Surgery Patients.

BACKGROUND: Postoperative hyperglycemia has been associated with poor surgical outcome. The effect of intraoperative glucose management on postoperative glucose levels and the optimal glycemic threshold for initiating insulin are currently unknown. METHODS: We performed a retrospective cohort study of surgery patients who required intraoperative glucose management with data extracted from electronic medical records. In patients who required glucose management, intraoperative glucose levels and insulin therapy were compared against postoperative glucose levels during 3 periods: first postoperative level within 1 hour, within the first 12 hours, and 24 hours of the postoperative period. Logistic regression models that adjusted for patient and surgical factors were used to determine the association between intraoperative glucose management and postoperative glucose levels. RESULTS: In 2440 patients who required intraoperative glucose management, an increase in mean intraoperative glucose level by 10 mg/dL was associated with an increase in postoperative glucose levels by 4.7 mg/dL (confidence interval [CI], 4.1-5.3; P < 0.001) for the first postoperative glucose measurement, 2.6 mg/dL (CI, 2.1-3.1; P < 0.001) for the mean first 12-hour postoperative glucose, and 2.4 mg/dL (CI, 2.0-2.9; P < 0.001) for the mean first 24-hour postoperative glucose levels (univariate analysis). Multivariate analysis showed that these effects depended on (interacted with) body mass index and diabetes status of the patient. Both diabetes status (regression coefficient = 12.2; P < 0.001) and intraoperative steroid use (regression coefficient = 10.2; P < 0.001) had a positive effect on elevated postoperative glucose levels. Intraoperative hyperglycemia (>180 mg/dL) was associated with postoperative hyperglycemia during the first 12 hours and the first 24 hours. However, interaction with procedure duration meant that this association was stronger for shorter surgeries. When compared with starting insulin for an intraoperative glucose threshold of 140 mg/dL thus avoiding hyperglycemia, initiation of insulin for a hyperglycemia threshold of 180 mg/dL was associated with an increase in postoperative glucose level (7 mg/dL; P < 0.001) and postoperative hyperglycemia incidence (odds ratio = 1.53; P = 0.01). CONCLUSIONS: A higher intraoperative glucose level is associated with a higher postoperative glucose level. Intraoperative hyperglycemia increases the odds for postoperative hyperglycemia. Adequate intraoperative glucose management by initiating insulin infusion when glucose level exceeds 140 mg/dL to prevent hyperglycemia is associated with lower postoperative glucose levels and fewer incidences of postoperative hyperglycemia. However, patient- and procedure-specific variable interactions make the relationship between intraoperative and postoperative glucose levels complicated.

Intraoperative blood glucose management: impact of a real-time decision support system on adherence to institutional protocol.

Poor perioperative glycemic management can lead to negative surgical outcome. Improved compliance to glucose control protocol could lead to better glucose management. An Anesthesia Information Management System based decision support system-Smart Anesthesia Manager™ (SAM) was used to generate real-time reminders to the anesthesia providers to closely adhere to our institutional glucose management protocol. Compliance to hourly glucose measurements and correct insulin dose adjustments was compared for the baseline period (12 months) without SAM and the intervention period (12 months) with SAM decision support. Additionally, glucose management parameters were compared for the baseline and intervention periods. A total of 1587 cases during baseline and 1997 cases during intervention met the criteria for glucose management (diabetic patients or non-diabetic patients with glucose level >140 mg/dL). Among the intervention cases anesthesia providers chose to use SAM reminders 48.7 % of the time primarily for patients who had diabetes, higher HbA1C or body mass index, while disabling the system for the remaining cases. Compliance to hourly glucose measurement and correct insulin doses increased significantly during the intervention period when compared with the baseline (from 52.6 to 71.2 % and from 13.5 to 24.4 %, respectively). In spite of improved compliance to institutional protocol, the mean glucose levels and other glycemic management parameters did not show significant improvement with SAM reminders. Real-time electronic reminders improved intraoperative compliance to institutional glucose management protocol though glycemic parameters did not improve even when there was greater compliance to the protocol.

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.

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

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.

Smart Anesthesia Manager™ (SAM)--a real-time decision support system for anesthesia care during surgery.

Anesthesia information management systems (AIMS) are being increasingly used in the operating room to document anesthesia care. We developed a system, Smart Anesthesia Manager™ (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 $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 $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: 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.

Automated electronic reminders to improve redosing of antibiotics during surgical cases: comparison of two approaches.

BACKGROUND: Timely re-dosing of antibiotic for prolonged surgical cases is an important measure in reducing the risk of surgical site infections. For the anesthesia team, which generally administers the antibiotic re-doses, it is difficult to keep track of and remember the exact timing requirements. We explored the efficacy of two types of electronic reminders to aid the anesthesia team in performing timely antibiotic re-doses. METHODS: The first electronic reminder was a timer-triggered "blinking button" feature in the Anesthesia Information Management System (AIMS). The second was generated with a real-time decision support system, the Smart Anesthesia Messenger (SAM). The AIMS reminder was applied for the first five months of the study, whereas the SAM reminder was applied for the second five months. A retrospective analysis was performed to evaluate the efficacy of the reminder messages in improving the antibiotic re-dose success rate. RESULTS: In a total of 940 cases, the anesthesia team was reminded of the need for antibiotic re-dosing with AIMS, whereas in 922 cases, the SAM system gave the reminder. The AIMS reminders achieved a timely re-dose success rate of 62.5% ± 1.6%, whereas the SAM reminders achieved a significantly higher success rate: 83.9% ± 3.4% (p < 0.001). CONCLUSIONS: Compared with the simple reminders generated with AIMS, the relevant, informative messages generated with SAM were more effective in improving compliance with timely antibiotic re-doses.

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.