Implementation of an electroencephalogram-guided propofol anesthesia practice in a large academic pediatric hospital: A quality improvement project.

BACKGROUND: Propofol-based total intravenous anesthesia is gaining popularity in pediatric anesthesia. Electroencephalogram can be used to guide propofol dosing to the individual patient to mitigate against overdosing and adverse events. However, electroencephalogram interpretation and propofol pharmacokinetics are not sufficiently taught in training programs to confidently deploy electroencephalogram-guided total intravenous anesthesia. AIMS: We conducted a quality improvement project with the smart aim of increasing the percentage of electroencephalogram-guided total intravenous anesthesia cases in our main operating room from 0% to 80% over 18 months. Balancing measures were number of total intravenous anesthesia cases, emergence times, and perioperative emergency activations. METHODS: The project key drivers were education, equipment, and electronic health record modifications. Plan-Do-Study-Act cycles included: (1) providing journal articles, didactic lectures, intraoperative training, and teaching documents; (2) scheduling electroencephalogram-guided total intravenous anesthesia teachers to train faculty, staff, and fellows for specific cases and to assess case-based knowledge; (3) adding age-based propofol dosing tables and electroencephalogram parameters to the electronic health record (EPIC co, Verona, WI); (4) procuring electroencephalogram monitors (Sedline, Masimo Inc). Electroencephalogram-guided total intravenous anesthesia cases and balancing measures were identified from the electronic health record. The smart aim was evaluated by statistical process control chart. RESULTS: After the four Plan-Do-Study-Act cycles, electroencephalogram-guided total intravenous anesthesia increased from 5% to 75% and was sustained at 72% 9 months after project completion. Total intravenous anesthesia cases/mo and number of perioperative emergency activations did not change significantly from start to end of the project, while emergence time for electroencephalogram-guided total intravenous anesthesia was greater statistically but not clinically (total intravenous anesthesia without electroencephalogram [16 ± 10 min], total intravenous anesthesia with electroencephalogram [18 ± 9 min], sevoflurane [17 ± 9 min] p < .001). CONCLUSION: Quality improvement methods may be deployed to adopt electroencephalogram-guided total intravenous anesthesia in a large academic pediatric anesthesia practice. Keys to success include education, in operating room case training, scheduling teachers with learners, electronic health record modifications, and electroencephalogram devices and supplies.

Quantitative electroencephalogram in term neonates under different sleep states.

Electroencephalogram (EEG) can be used to assess depth of consciousness, but interpreting EEG can be challenging, especially in neonates whose EEG undergo rapid changes during the perinatal course. EEG can be processed into quantitative EEG (QEEG), but limited data exist on the range of QEEG for normal term neonates during wakefulness and sleep, baseline information that would be useful to determine changes during sedation or anesthesia. We aimed to determine the range of QEEG in neonates during awake, active sleep and quiet sleep states, and identified the ones best at discriminating between the three states. Normal neonatal EEG from 37 to 46 weeks were analyzed and classified as awake, quiet sleep, or active sleep. After processing and artifact removal, total power, power ratio, coherence, entropy, and spectral edge frequency (SEF) 50 and 90 were calculated. Descriptive statistics were used to summarize the QEEG in each of the three states. Receiver operating characteristic (ROC) curves were used to assess discriminatory ability of QEEG. 30 neonates were analyzed. QEEG were different between awake vs asleep states, but similar between active vs quiet sleep states. Entropy beta, delta2 power %, coherence delta2, and SEF50 were best at discriminating awake vs active sleep. Entropy beta had the highest AUC-ROC ≥ 0.84. Entropy beta, entropy delta1, theta power %, and SEF50 were best at discriminating awake vs quiet sleep. All had AUC-ROC ≥ 0.78. In active sleep vs quiet sleep, theta power % had highest AUC-ROC > 0.69, lower than the other comparisons. We determined the QEEG range in healthy neonates in different states of consciousness. Entropy beta and SEF50 were best at discriminating between awake and sleep states. QEEG were not as good at discriminating between quiet and active sleep. In the future, QEEG with high discriminatory power can be combined to further improve ability to differentiate between states of consciousness.

Comparison of Postoperative Respiratory Monitoring by Acoustic and Transthoracic Impedance Technologies in Pediatric Patients at Risk of Respiratory Depression.

BACKGROUND: In children, postoperative respiratory rate (RR) monitoring by transthoracic impedance (TI), capnography, and manual counting has limitations. The rainbow acoustic monitor (RAM) measures continuous RR noninvasively by a different methodology. Our primary aim was to compare the degree of agreement and accuracy of RR measurements as determined by RAM and TI to that of manual counting. Secondary aims include tolerance and analysis of alarm events. METHODS: Sixty-two children (2-16 years old) were admitted after tonsillectomy or receiving postoperative patient/parental-controlled analgesia. RR was measured at regular intervals by RAM, TI, and manual count. Each TI or RAM alarm resulted in a clinical evaluation to categorize as a true or false alarm. To assess accuracy and degree of agreement of RR measured by RAM or TI compared with manual counting, a Bland-Altman analysis was utilized showing the average difference and the limits of agreement. Sensitivity and specificity of RR alarms by TI and RAM are presented. RESULTS: Fifty-eight posttonsillectomy children and 4 patient/parental-controlled analgesia users aged 6.5 ± 3.4 years and weighting 35.3 ± 22.7 kg (body mass index percentile 76.6 ± 30.8) were included. The average monitoring time per patient was 15.9 ± 4.8 hours. RAM was tolerated 87% of the total monitoring time. The manual RR count was significantly different from TI (P = .007) with an average difference ± SD of 1.39 ± 10.6 but were not significantly different from RAM (P = .81) with an average difference ± SD of 0.17 ± 6.8. The proportion of time when RR measurements differed by ≥4 breaths was 22% by TI and was 11% by RAM. Overall, 276 alarms were detected (mean alarms/patient = 4.5). The mean number of alarms per patient were 1.58 ± 2.49 and 2.87 ± 4.32 for RAM and TI, respectively. The mean number of false alarms was 0.18 ± 0.71 for RAM and 1.00 ± 2.78 for TI. The RAM was found to have 46.6% sensitivity (95% confidence interval [CI], 0.29-0.64), 95.9% specificity (95% CI, 0.90-1.00), 88.9% positive predictive value (95% CI, 0.73-1.00), and 72.1% negative predictive value (95% CI, 0.61-0.84), whereas the TI monitor had 68.5% sensitivity (95% CI, 0.53-0.84), 72.0% specificity (95% CI, 0.60-0.84), 59.0% positive (95% CI, 0.44-0.74), and 79.5% negative predictive value (95% CI, 0.69-0.90). CONCLUSIONS: In children at risk of postoperative respiratory depression, RR assessment by RAM was not different to manual counting. RAM was well tolerated, had a lower incidence of false alarms, and had better specificity and positive predictive value than TI. Rigorous evaluation of the negative predictive value is essential to determine the role of postoperative respiratory monitoring with RAM.

Trending and accuracy of noninvasive hemoglobin monitoring in pediatric perioperative patients.

BACKGROUND: Rainbow Pulse CO-Oximetry technology (Masimo Corporation, Irvine, CA) provides continuous and noninvasive measurement of arterial hemoglobin concentration (SpHb). We assessed the trending and accuracy of SpHb by this innovative monitoring compared with Hb concentration obtained with conventional laboratory techniques (Hb) in children undergoing surgical procedures with potential for substantial blood loss. METHODS: Hb concentrations were recorded from Pulse CO-Oximetry and a conventional hematology analyzer. Regression analysis and 4-quadrant plot were used to evaluate the trending for changes in SpHb and Hb measurements (ΔSpHb and ΔHb). Bias, precision, and limits of agreement of SpHb and of in vivo adjusted SpHb (SpHb - first bias to HB) compared with Hb were calculated. RESULTS: One hundred fifty-eight SpHb-Hb data pairs and 105 delta pairs (ΔSpHb and ΔHb) from 46 patients aged 2 months to 17 years with Hb ranging from 16.7 to 7.9 g/dL were collected. To evaluate trending, the delta pairs (ΔSpHb and ΔHb) were plotted, which revealed a positive correlation (ΔSpHb = 0.022 + 0.76ΔHb) with correlation coefficient r = 0.76, 95% CI [confidence interval] = 0.57-0.86. The bias and precision of SpHb to Hb and in vivo adjusted SpHb were 0.4 ± 1.3 g/dL and 0.1 ± 1.2 g/dL, respectively; the limits of agreement were -2.0 to 3.2 g/dL before in vivo adjustment and -2.4 to 2.2 g/dL after in vivo adjustment (P value = 0.04). The mean percent bias (from the reference Hb concentration) decreased from 4.1% ± 11.9% to 0.7% ± 11.3% (P value = 0.01). No drift in bias over time was observed during the study procedure. Of patient demographic and physiological factors tested for correlation with the SpHb, only perfusion index at sensor site showed a weak correlation. CONCLUSIONS: The accuracy of SpHb in children with normal Hb and mild anemia is similar to that previously reported in adults and is independent of patient demographic and physiological states except for a weak correlation with perfusion index. The trending of SpHb and Hb in children with normal Hb and mild anemia showed a positive correlation. Further studies are necessary in children with moderate and severe anemia.

Quality and safety in pediatric anesthesia: how can guidelines, checklists, and initiatives improve the outcome?

PURPOSE OF REVIEW: Cognitive aids are tangible or intangible instruments that guide users in decision-making and in the completion of a complex series of tasks. Common examples include mnemonics, checklists, and algorithms. Cognitive aids constitute very effective approaches to achieve well tolerated, high quality healthcare because they promote highly reliable processes that reduce the likelihood of failure. This review describes recent advances in quality improvement for pediatric anesthesiology with emphasis on application of cognitive aids to impact patient safety and outcomes. RECENT FINDINGS: Quality improvement encourages the examination of systems to create stable processes and ultimately high-value care. Quality improvement initiatives in pediatric anesthesiology have been shown to improve outcomes and the delivery of efficient and effective care at many institutions. The use of checklists, in particular, improves adherence to evidence-based care in crisis situations, decreases catheter-associated bloodstream infections, reduces blood product utilization, and improves communication during the patient handoff process. Use of this simple tool has been associated with decreased morbidity, fewer medical errors, improved provider satisfaction, and decreased mortality in nonanesthesia disciplines as well. SUMMARY: Successful quality improvement initiatives utilize cognitive aids such as checklists and have been shown to optimize pediatric patient experience and anesthesia outcomes and reduce perioperative complications.

Perspectives on quality and safety in pediatric anesthesia.

Organizational culture underlies every improvement strategy; without a strong culture, a change, even if initially successful, is short lived. Changing culture and improving quality require commitment of leadership, and leaders must play an active and visible role to articulate the vision and create the proper environment. Quality-improvement projects require a consistent framework for outlining a process, identifying problems, and testing, evaluating, and implementing changes. Wake Up Safe is a patient safety organization that strives to use quality improvement to make anesthesia care safer. Root cause analysis is a methodology in safety analytics based on a sequence of events model of safety.

National pediatric anesthesia safety quality improvement program in the United States.

BACKGROUND: As pediatric anesthesia has become safer over the years, it is difficult to quantify these safety advances at any 1 institution. Safety analytics (SA) and quality improvement (QI) are used to study and achieve high levels of safety in nonhealth care industries. We describe the development of a multiinstitutional program in the United States, known as Wake-Up Safe (WUS), to determine the rate of serious adverse events (SAE) in pediatric anesthesia and to apply SA and QI in the pediatric anesthesia departments to decrease the SAE rate. METHODS: QI was used to design and implement WUS in 2008. The key drivers in the design were an organizational structure; an information system for the SAE; SA to characterize the SAE; QI to imbed high-reliability care; communications to disseminate the learnings; and engaged leadership in each department. Interventions for the key drivers, included Participation Agreements, Patient Safety Organization designation, IRB approval, Data Management Co., membership fee, SAE standard templates, SA and QI workshops, and department leadership meetings. RESULTS: WUS has 19 institutions, 39 member anesthesiologists, 734 SAE, and 736,365 anesthetics as of March, 2013. The initial members joined at year 1, and initial SAE were recorded by year 2. The SAE rate is 1.4 per 1000 anesthetics. Of SAE, respiratory was most common, followed by cardiac arrest, care escalation, and cardiovascular, collectively 76% of SAE. In care escalation, medication errors and equipment dysfunction were 89%. Of member anesthesiologists, 70% were trained in SA and QI by March 2013; virtually, none had SA and QI expertise before joining WUS. CONCLUSION: WUS documented the incidence and types of SAE nationally in pediatric anesthesiology. Education and application of QI and SA in anesthesia departments are key strategies to improve perioperative safety by WUS.

Accuracy of acoustic respiration rate monitoring in pediatric patients.

BACKGROUND: Rainbow acoustic monitoring (RRa) utilizes acoustic technology to continuously and noninvasively determine respiratory rate from an adhesive sensor located on the neck. OBJECTIVE: We sought to validate the accuracy of RRa, by comparing it to capnography, impedance pneumography, and to a reference method of counting breaths in postsurgical children. METHODS: Continuous respiration rate data were recorded from RRa and capnography. In a subset of patients, intermittent respiration rate from thoracic impedance pneumography was also recorded. The reference method, counted respiratory rate by the retrospective analysis of the RRa, and capnographic waveforms while listening to recorded breath sounds were used to compare respiration rate of both capnography and RRa. Bias, precision, and limits of agreement of RRa compared with capnography and RRa and capnography compared with the reference method were calculated. Tolerance and reliability to the acoustic sensor and nasal cannula were also assessed. RESULTS: Thirty-nine of 40 patients (97.5%) demonstrated good tolerance of the acoustic sensor, whereas 25 of 40 patients (62.5%) demonstrated good tolerance of the nasal cannula. Intermittent thoracic impedance produced erroneous respiratory rates (>50 b·min(-1) from the other methods) on 47% of occasions. The bias ± SD and limits of agreement were -0.30 ± 3.5 b·min(-1) and -7.3 to 6.6 b·min(-1) for RRa compared with capnography; -0.1 ± 2.5 b·min(-1) and -5.0 to 5.0 b·min(-1) for RRa compared with the reference method; and 0.2 ± 3.4 b·min(-1) and -6.8 to 6.7 b·min(-1) for capnography compared with the reference method. CONCLUSIONS: When compared to nasal capnography, RRa showed good agreement and similar accuracy and precision but was better tolerated in postsurgical pediatric patients.

Improving on-time start of day and end of day for a pediatric surgical service.

BACKGROUND AND OBJECTIVE: In multicase pediatric ear, nose, and throat operating rooms (ORs), brief delays in early case start times often produce a cascading effect of lengthy delays by the end of the day and can often lead to patient, family, and staff dissatisfaction and increased labor costs due to unplanned overtime. We sought to improve actual end of day relative to scheduled end of day from 40% to 60%. METHODS: Key drivers of the process included case scheduling, ordering of sedative medications, and nurse availability in the post anesthesia care unit to receive the patient from the anesthesia provider. A multidisciplinary team conducted a series of tests of change addressing the various key drivers. Data were collected by using an independent, impartial data collector as well as being extracted from the hospital information technology system. Data were analyzed by using control charts and statistical process control methods. RESULTS: The percentage of ORs ending on time increased from 40% to 60%. Appropriate scheduling of complex cases increased from 10% to 87%, and accurate scheduling of case duration improved from 21% to 48%. Timely premedication increased from 55% to 90% and immediate availability of a nurse in the postanesthesia care unit from 68% to.90%. CONCLUSIONS: By applying quality-improvement methods, significant improvements were made in a multicase pediatric ear, nose, and throat OR. The impact can be significant by reducing wait times for patients, as well as staff overtime for the institution.

Getting started with the model for improvement: psychology and leadership in quality improvement.

Although the case for quality in hospitals is compelling, doctors are often uncertain how to achieve it. This article forms the third and final part of a series providing practical guidance on getting started with a first quality improvement project. Introduction.

Evaluation of pediatric near-infrared cerebral oximeter for cardiac disease.

BACKGROUND: Cerebral hypoxia-ischemia remains a complication in children with congenital heart disease. Near-infrared spectroscopy can be utilized at the bedside to detect cerebral hypoxia-ischemia. This study aimed to calibrate and validate an advanced technology near-infrared cerebral oximeter for use in children with congenital heart disease. METHODS: After institutional review board approval and parental consent, 100 children less than 12 years and less than 40 kg were enrolled. Phase I (calibration) measured arterial and jugular venous saturation (SaO(2), SjO(2)) by co-oximetry simultaneously with device signals to calibrate an algorithm to determine regional cerebral saturation against a weighted average cerebral saturation (0.7 SjO(2) + 0.3 SaO(2)). Phase II (validation) evaluated regional cerebral saturation from the algorithm against the weighted average cerebral saturation by correlation, bias, precision, and A(Root Mean Square) assessed by linear regression and Bland-Altman analysis. RESULTS: Of 100 patients, 86 were evaluable consisting of 7 neonates, 44 infants, and 35 children of whom 55% were female, 79% Caucasian, and 41% with cyanotic disease. The SaO(2) and regional cerebral saturation ranged from 34% to 100% and 34% to 91%, respectively. There were no significant differences in subject characteristics between phases. For the entire cohort, A(RMS), bias, precision, and correlation coefficient were 5.4%, 0.5%, 5.39%, and 0.88, respectively. Age, skin color, and hematocrit did not affect these values. CONCLUSIONS: This cerebral oximeter accurately measures the absolute value of cerebral saturation in children over a wide range of oxygenation and subject characteristics, offering advantages in assessment of cerebral hypoxia-ischemia in congenital heart disease.

Quantification of serum fentanyl concentrations from umbilical cord blood during ex utero intrapartum therapy.

Fetal IM injection of fentanyl is frequently performed during ex utero intrapartum therapy (EXIT procedure). We quantified the concentration of fentanyl in umbilical vein blood. Thirteen samples from 13 subjects were analyzed. Medians and ranges are reported as follows. Weight of the newborn at delivery was 3000 g (2020-3715 g). The dose of fentanyl was 60 µg (45-65 µg). The time between IM administration of fentanyl and collection of the sample was 37 minutes (5-86 minutes). Fentanyl was detected in all of the samples, with a median serum concentration of 14.0 ng/mL (4.3-64.0 ng/mL).

Cerebral oxygen saturation-time threshold for hypoxic-ischemic injury in piglets.

BACKGROUND: Detection of cerebral hypoxia-ischemia (H-I) and prevention of brain injury remains problematic in critically ill neonates. Near-infrared spectroscopy (NIRS), a noninvasive bedside technology could fill this role, although NIRS cerebral O(2) saturation (Sc(O2)) viability-time thresholds for brain injury have not been determined. We investigated the relationship between H-I duration at Sc(O2) 35%, a viability threshold which causes neurophysiological impairment, to neurological outcome. METHODS: Forty-six fentanyl-midazolam anesthetized piglets were equipped with NIRS and cerebral function monitor (CFM) to record Sc(O2) and electrocortical activity (ECA). After carotid occlusion, inspired O(2) was adjusted to produce H-I (Sc(O2) 35% with decreased ECA) for 1, 2, 3, 4, 6 or 8 h in different groups, followed by survival to assess neurological outcome by behavioral and histological examination. RESULTS: For H-I lasting 1 or 2 h, ECA and Sc(O2) during reperfusion rapidly returned to normal and neurological outcomes were normal. For H-I more than 2-3 h, ECA was significantly decreased and Sc(O2) was significantly increased during reperfusion, suggesting continued depression of tissue O(2) metabolism. As H-I increased beyond 2 h, the incidence of neurological injury increased linearly, approximately 15% per h. CONCLUSION: A viability-time threshold for H-I injury is Sc(O2) of 35% for 2-3 h, heralded by abnormalities in NIRS and CFM during reperfusion. These findings suggest that NIRS and CFM might be used together to predict neurological outcome, and illustrate that there is a several hour window of opportunity during H-I to prevent neurological injury.