How the Wake Up Safe pediatric anesthesia collaborative increased quality improvement capability and collaboration.

Wake Up Safe is a patient safety organization consisting of 40 institutions with a mission to improve the processes of care and outcomes for newborns, infants, and children having anesthesia for surgery and medical procedures. It was recognized that the level of quality improvement (QI), knowledge, and experience varied greatly between member institutions. In Fiscal Year 2015, the group's leadership created a subcommittee on QI and education in efforts to provide member institutions with the skills and resources to use QI methodology to improve care at their own institution. This subcommittee developed a program to improve members' knowledge in safety analytics and QI science and to help members implement change in their own institutions. This review describes the development and implementation of this initiative. As a result of this initiative, significant progress was made improving the QI capability of the collaborative over a two-year period. This educational and support program included workshops, an online discussion forum, site visits, and project presentations.

Optimizing Pediatric Induction Experiences Using Human-centered Design.

PURPOSE: Anesthesia inhalation induction (falling asleep for a surgery using a medical mask) is often stressful for children. When children become anxious about induction, they may resist wearing the anesthesia mask. High anxiety during induction is associated with poorer outcomes after surgery, such as increased emergence delirium, increased pain and negative behavioral changes after discharge. The purpose of this project was to design an optimal anesthesia induction experience for children, with a focus on decreasing patient anxiety during inhalation induction. DESIGN: Designing for the perioperative environment requires in-depth knowledge of existing processes, needs of key stakeholders, strengths/shortcomings of existing approaches, and iterative testing of design concepts. We used a human centered design model (design research) to approach this challenge. METHODS: Hospital staff partnered with a design team at the Live Well Collaborative. Families and staff were consulted during all phases of the design process. The iterative design research process (research, ideation, refinement) was used to develop product and process concepts for optimizing the induction experience. Requirements for an optimal induction experience were defined during the research phase through reviewing the scientific literature, process mapping and benchmarking with other products. Product and process concepts were developed during the ideation phase. Concepts were tested and refined during the refinement phase. FINDINGS: The research phase provided insights about the current anesthesia induction process and what interventions help engage children in medical care. Key insights included normalizing the anesthesia mask through medical play, providing patients with an increased sense of control preoperatively and during induction, and engaging multiple senses during the process. The ideation phase led to the development of several design concepts, including an app that is activated by breathing into the anesthesia mask. During the refinement phase, concepts were shared and refined with input from families and clinical staff. This phase led to the development of a novel zoo-themed gaming app. CONCLUSIONS: The design research process facilitated the creation of a new anxiety reduction tool for the perioperative environment. The breath-controlled induction app simultaneously employs multiple evidence-based anxiety reduction techniques and is designed to seamlessly integrate into the fast-paced perioperative workflow during key stress points. Testing in the clinical setting is needed to determine the effectiveness of the app for preoperative anxiety reduction.

Validation of a Simple Tool for Electronic Documentation of Behavioral Responses to Anesthesia Induction.

BACKGROUND: Anxiety and distress behaviors during anesthesia induction are associated with negative postoperative outcomes for pediatric patients. Documenting behavioral responses to induction is useful to evaluate induction quality at hospitals and to optimize future anesthetics for returning patients, but we lack a simple tool for clinical documentation. The Induction Compliance Checklist is a tool for grading induction behaviors that is well validated for research purposes, but it is not practical for routine documentation in busy clinical practice settings. The Child Induction Behavioral Assessment tool was developed to provide a simple and easy to use electronic tool for clinical documentation of induction behaviors. The aim of this study was to test the Child Induction Behavioral Assessment tool's concurrent validity with the Induction Compliance Checklist and the interrater reliability. METHODS: This prospective, observational study included 384 pediatric patients undergoing anesthesia inhalation induction. Concurrent validity with the Induction Compliance Checklist and interrater reliability of the Child Induction Behavioral Assessment were evaluated. Two researchers alternated scoring the Induction Compliance Checklist. The 2 researchers independently scored the Child Induction Behavioral Assessment. The anesthesia clinician caring for the patient also independently scored the Child Induction Behavioral Assessment by completing their routine documentation in the patient's medical record. Two age groups were evaluated (ages 1-3 and 4-12 years old). RESULTS: Clinicians' and researchers' Child Induction Behavioral Assessment scores demonstrated a strong correlation with the Induction Compliance Checklist (P < .0001). There was an excellent agreement between the 2 researchers' Child Induction Behavioral Assessment scores for the younger and older age groups, respectively (Kappa [95% CI] = 0.97 (0.94-0.99); K = 0.94 (0.89-0.99)]. The agreement between the researchers and the 117 clinicians who documented Child Induction Behavioral Assessment assessments in the medical record was good overall (intraclass correlation coefficient = 0.70), with fair agreement with the 1- to 3-year-old patients (intraclass correlation coefficient = 0.56) and good agreement for the 4- to 12-year-old patients (intraclass correlation coefficient = 0.74). CONCLUSIONS: The Child Induction Behavioral Assessment scale is a simple and practical electronic tool used to document pediatric behavioral responses to anesthesia inductions. This study provides evidence of the tool's validity and reliability for inhalation inductions. Future research is needed at other hospitals to confirm validity.

A quality improvement project to reduce postoperative adverse respiratory events and increase safety in the postanesthesia care unit of a pediatric institution.

BACKGROUND: Quality improvement methods can identify solutions and make dramatic improvements in patient safety during daily clinical care. The science of quality improvement in healthcare is still a very new concept in developing countries like China. AIMS: We initiated a quality improvement project to minimize adverse respiratory events in our postanesthesia care unit with the guidance of an experienced quality improvement expert from Cincinnati Children's Hospital Medical Center. METHODS: We set up a quality improvement team that included anesthesia safety team members at Shanghai Children's Medical Center, and a quality improvement expert in pediatric anesthesia from Cincinnati Children's Hospital Medical Center. Data from the previous year were reviewed. After using Failure Mode and Effect Analysis to access risks associated with the current process, a Key Driver Diagram and a Smart Aim were developed. Key drivers included establishing a safety culture, resource allocation to meet needs, education and training, standardization of care, improved communication and handoff, and enhanced detection, recognition, and response to adverse events. Using Plan-Do-Study-Act cycles of the improvement model, interventions were conducted to improve the process. The primary outcome was the percentage of postoperative respiratory adverse events in the postanesthesia care unit, and we calculated the average recovery time as a balancing measure. Data were collected and analyzed using a run chart and control chart. RESULTS: The median percentage of respiratory adverse events in postanesthesia care unit decreased from 2.8% to 1.4%. Respiratory adverse events were reduced by over 30% compared to the previous period with no significant change in mean recovery time. CONCLUSION: Using quality improvement methods, we successfully reduced the percentage of respiratory adverse events in the postanesthesia care unit. This helped to establish a safety culture among the anesthesia staff. Quality and safety improvement can be successfully implemented in developing countries like China with collaboration with quality improvement experts from more experienced institutions.

Increasing compliance of safe medication administration in pediatric anesthesia by use of a standardized checklist.

BACKGROUND: Medication errors pose a significant risk perioperatively. In the perioperative environment, common medication administration processes are not typically performed. Given the common administration of potentially harmful medications and the potential for medication errors, patient risk is substantial. Specifically, intravenous acetaminophen has been used more frequently in the perioperative period which yielded an increase in medication administration errors reported. AIMS: This project was initiated by Cincinnati Children's Hospital after an increase in perioperative acetaminophen dosing errors was reported. After mapping the administration process of perioperative acetaminophen, we sought to reduce medication errors by the use of a safety checklist. Acetaminophen was used as a surrogate for other perioperative medications in this quality improvement project. METHODS: Use of a failure mode effects analysis assisted the team in understanding the failures of the process of safe medication administration. Subsequently, key drivers of this process were designed to include accurate understanding and documentation of medication history, consistent communication between perioperative caregivers, and an efficient checklist process. A multidisciplinary team conducted a series of tests to modify key drivers. Data were collected by utilizing data from a paper checklist, prior to the electronic medical record change that was prompted by this study. A total of 633 checklists and electronic medical records were analyzed during a 6-month period; data were analyzed using control charts and statistical process control methods. RESULTS/ANALYSIS: The percentage of compliance with the safe administration checklist for acetaminophen in the preoperative period increased to 97%. Use of the paper checklist likely prompted the appropriate increase in compliance with safe administration. Additionally, provider-specific feedback produced a significant increase in compliance with the use of the checklist. CONCLUSION: Application of quality improvement methods, specifically a safety checklist, were utilized to improve the safe administration of acetaminophen during the perioperative period. Increasing reliability of accurate delivery and administration of medication to patients are crucial in optimizing patient safety. Use of a medication safety checklist may be beneficial in reducing potential administration errors, specifically for high-risk medications.

The Child Induction Behavioral Assessment Tool: A Tool to Facilitate the Electronic Documentation of Behavioral Responses to Anesthesia Inductions.

PURPOSE: The purpose of this study was to develop and implement an electronic tool for documenting pediatric patients' behavioral responses to anesthesia induction. DESIGN: Quality improvement methodology was used in the tool development and implementation. METHODS: The Child Induction Behavioral Assessment (CIBA) tool was developed based upon existing validated tools and through discussions with content experts and key stakeholders. Staff usage of the tool was monitored and the clinical utility of the tool was assessed. FINDINGS: The CIBA tool facilitated frequent documentation of behavioral responses to inductions. The majority of clinicians reported that they found the prior CIBA ratings useful when developing induction plans for returning patients. CONCLUSIONS: Electronic documentation using the CIBA tool may provide useful information for optimizing induction plans for returning patients. Future research is needed to directly test the CIBA tool's validity.

Perioperative Respiratory Adverse Events in Pediatric Ambulatory Anesthesia: Development and Validation of a Risk Prediction Tool.

BACKGROUND: Perioperative respiratory adverse events (PRAEs) are the most common cause of serious adverse events in children receiving anesthesia. Our primary aim of this study was to develop and validate a risk prediction tool for the occurrence of PRAE from the onset of anesthesia induction until discharge from the postanesthesia care unit in children younger than 18 years undergoing elective ambulatory anesthesia for surgery and radiology. The incidence of PRAE was studied. METHODS: We analyzed data from 19,059 patients from our department's quality improvement database. The predictor variables were age, sex, ASA physical status, morbid obesity, preexisting pulmonary disorder, preexisting neurologic disorder, and location of ambulatory anesthesia (surgery or radiology). Composite PRAE was defined as the presence of any 1 of the following events: intraoperative bronchospasm, intraoperative laryngospasm, postoperative apnea, postoperative laryngospasm, postoperative bronchospasm, or postoperative prolonged oxygen requirement. Development and validation of the risk prediction tool for PRAE were performed using a split sampling technique to split the database into 2 independent cohorts based on the year when the patient received ambulatory anesthesia for surgery and radiology using logistic regression. A risk score was developed based on the regression coefficients from the validation tool. The performance of the risk prediction tool was assessed by using tests of discrimination and calibration. RESULTS: The overall incidence of composite PRAE was 2.8%. The derivation cohort included 8904 patients, and the validation cohort included 10,155 patients. The risk of PRAE was 3.9% in the development cohort and 1.8% in the validation cohort. Age ≤ 3 years (versus >3 years), ASA physical status II or III (versus ASA physical status I), morbid obesity, preexisting pulmonary disorder, and surgery (versus radiology) significantly predicted the occurrence of PRAE in a multivariable logistic regression model. A risk score in the range of 0 to 3 was assigned to each significant variable in the logistic regression model, and final score for all risk factors ranged from 0 to 11. A cutoff score of 4 was derived from a receiver operating characteristic curve to determine the high-risk category. The model C-statistic and the corresponding SE for the derivation and validation cohort was 0.64 ± 0.01 and 0.63 ± 0.02, respectively. Sensitivity and SE of the risk prediction tool to identify children at risk for PRAE was 77.6 ± 0.02 in the derivation cohort and 76.2 ± 0.03 in the validation cohort. CONCLUSIONS: The risk tool developed and validated from our study cohort identified 5 risk factors: age ≤ 3 years (versus >3 years), ASA physical status II and III (versus ASA physical status I), morbid obesity, preexisting pulmonary disorder, and surgery (versus radiology) for PRAE. This tool can be used to provide an individual risk score for each patient to predict the risk of PRAE in the preoperative period.

Interventions designed using quality improvement methods reduce the incidence of serious airway events and airway cardiac arrests during pediatric anesthesia.

BACKGROUND: Although serious complications during pediatric anesthesia are less common than they were 20 years ago, serious airway events continue to occur. Based on Quality Improvement (QI) data from our institution, a QI project was designed to reduce the incidence of serious airway events and airway cardiac arrests. METHODS: A quality improvement team consisting of members of the Department of Anesthesia was formed and QI data from previous years were analyzed. The QI team developed a Smart Aim, Key Driver Diagram, and specific Interventions that focused on the accessibility of emergency drugs, the use of nondepolarizing muscle relaxants for endotracheal intubation in children 2 years and younger, and the presence of anesthesia providers until emergence from anesthesia in high-risk patients. RESULTS: The percentage of cases where muscle relaxants were utilized in children 2 years and younger for endotracheal intubation and where atropine and succinylcholine were readily available increased at both our base and outpatient facilities. Over the 2.5-year study period, the incidence of serious airway events and airway cardiac arrests was reduced by 44% and 59%, respectively compared to the previous 2-year period. CONCLUSION: We utilized QI methodology to design and implement a project which led to greater standardization of clinical practice within a large pediatric anesthesia group. Based on an understanding of system issues impacting our clinical practice, we designed and tested interventions that led to a significant reduction in the incidence of serious airway events and airway cardiac arrests.

Case report of transfusion-related acute lung injury in a pediatric spine surgery patient transfused leukoreduced red blood cells.

Despite leukoreduced red blood cells (LR-RBCs) reducing the risk of transfusion-related acute lung injury (TRALI), we present a case of a 16-year-old female with kyphosis who received a transfusion of one unit of LR-RBCs, which lead to life-threatening, intraoperative TRALI. The clinical presentation included pulmonary edema, severe postoperative lactic acidosis, left ventricular dysfunction, increased creatine phosphokinase, fatty infiltration of the liver, and hemodynamic instability requiring inotropic support. This presentation is not the classic description of TRALI. Our patient improved with supportive treatment and was successfully extubated on postoperative day 4. TRALI work-up revealed antibody formation to HLA A2, A68, B44, and DQA 5 for the LR-RBCs unit administered.

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.

Quality and safety in pediatric anesthesia.

Health care quality and value are leading issues in medicine today for patients, health care professionals, and policy makers. Outcome, safety, and service-the components of quality-have been used to define value when placed in the context of cost. Health care organizations and professionals are faced with the challenge of improving quality while reducing health care related costs to improve value. Measurement of quality is essential for assessing what is effective and what is not when working toward improving quality and value. However, there are few tools currently for assessing quality of care, and clinicians often lack the resources and skills required to conduct quality improvement work. In this article, we provide a brief review of quality improvement as a discipline and describe these efforts within pediatric anesthesiology.

Using quality improvement methods to optimize resources and maximize productivity in an anesthesia screening and consultation clinic.

OBJECTIVES: The anesthesia preoperative screening and evaluation of a patient prior to surgery is a critical element in the safe and effective delivery of anesthesia care. In this era of increased focus on cost containment, many anesthesia practices are looking for ways to maximize productivity while maintaining the quality of the preoperative evaluation process by harnessing and optimizing all available resources. We sought to develop a Nurse Practitioner-assisted Preoperative Anesthesia Screening process using quality improvement methods with the goal of maintaining the quality of the screening process, while at the same time redirecting anesthesiologists time for the provision of nonoperating room (OR) anesthesia. The Nurse practitioner (NP) time (approximately 10 h per week) directed to this project was gained as a result of an earlier resource utilization improvement project within the Department of Anesthesia. The goal of this improvement project was to increase the proportion of patient anesthesia screens conducted by NPs to 50% within 6 months. METHODS: After discussion with key stakeholders of the process, a multidisciplinary improvement team identified a set of operational factors (key drivers) believed to be important to the success of the preoperative anesthesia screening process. These included the development of dedicated NP time for daily screening, NP competency and confidence with the screening process, effective mentoring by anesthesiologists, standardization of screening process, and communication with stakeholders of the process, that is, surgeons. These key drivers focused on the development of several interventions such as (i) NP education in the preoperative anesthesia screening for consultation process by a series of didactic lectures conducted by anesthesiologists, and NP's shadowing an anesthesiologist during the screening process, (ii) Anesthesiologist mentoring and assessment of NP screenings using the dual screening process whereby both anesthesiologists and NP conducted the screening process independently and results were compared and discussed, (iii) Examination and re-adjustment of NP schedules to provide time for daily screening while preserving other responsibilities, and (iv) Standardization through the development of guidelines for the preoperative screening process. Measures recorded included the percentage of patient anesthesia screens conducted by NP, the percentage of dual screens with MD and NP agreement regarding the screening decision, and the average times taken for the anesthesiologist and NP screening process. RESULTS: After implementation of these interventions, the percentage of successful NP-assisted anesthesia consultation screenings increased from 0% to 65% over a period of 6 months. The Anesthesiologists' time redirected to non-OR anesthesia averaged at least 8 h a week. The percentage of dual screens with agreement on the screening decision was 96% (goal >95%). The overall average time taken for a NP screen was 8.2 min vs 4.5 min for an anesthesiologist screen. The overall average operating room delays and cancelations for cases on the day of surgery remained the same. CONCLUSIONS: By applying quality improvement methods, we identified key drivers for the institution of an NP-assisted preoperative screening process and successfully implemented this process while redirecting anesthesiologists' time for the provision of non-OR anesthesia. This project was instrumental in improving the matching of provider skills with clinical need while maintaining superior outcomes at the lowest possible cost.

Improving on-time starts for patients scheduled with general anesthesia in a MRI suite.

OBJECTIVE: We applied quality improvement methodology to identify unnecessary, redundant parts of processes that can lead to delayed on-time starts for patients scheduled with general anesthesia (GA) in the radiology department. AIM: To address the issue of delayed on-time starts by improving work flow for the first patient scheduled with GA. BACKGROUND: Unplanned imaging in a high-volume MRI suite can result in a significant ripple effect throughout the day. Delayed on-time starts can lead to patient, family, and staff dissatisfaction due to significant wait times. MATERIALS AND METHODS: The team conducted a 5 month improvement project. Baseline data were obtained from pilot time studies allowed the team to identify reasons why the first case was not starting on time and to identify several key drivers to improve the process. Using the framework of small tests of change or the Plan-Do-Study-Act model, our key interventions primarily focused on standardizing the processes for completing the preimaging evaluation and for anesthesia induction. The primary objective measure of successful on-time start was defined as obtaining the first MRI image within 10 min of the scheduled start time, for the first patients of the day scheduled with GA. The secondary outcome measure was the extent of the delay quantified in minutes. RESULTS: Prior to the initiation of the project, only 36% of the first patients scheduled with GA each day met the primary objective measure. At the conclusion of the project 84% started on time. The secondary measure also showed significant improvement. CONCLUSIONS: Process improvement projects in anesthesia can yield positive results, using small incremental standardized changes. We used a quality improvement methods to successfully improve on-time start for patients scheduled with GA in high-volume MRI suite.

A comparison of inhalational inductions for children in the operating room vs the induction room.

BACKGROUND: There has been debate about the use of an induction room (IR) compared with an operating room (OR) for inhalational induction in children. The quality of the anesthesia induction between these two physical environments has not been studied previously. We sought to compare child distress, OR utilization and efficiency, and parental satisfaction and safety, between an IR and an OR. METHODS: In a prospective observational study, we studied 501 developmentally appropriate children ages 1-14 years, American Society of Anesthesiologists (ASA) physical status I-III, presenting for the inhalational induction of anesthesia, undergoing outpatient or outpatient-admit ENT surgery. Inductions were performed in an IR (IR group) or OR (OR group) with parent(s) present. Child behavioral compliance was assessed using the Induction Compliance Checklist (ICC), a validated observational scale from 0 to 10 consisting of 10 behaviors; an ICC score ≥4 was considered poor behavioral compliance. Times for transport, anesthesia start, ready for surgery, surgery finish, out of OR, and total case process times were recorded. OR utilization and OR efficiency was derived using these times. Data on number and experience of clinical providers were also collected. Parent satisfaction with the induction was measured using a satisfaction survey. Safety was measured by recording respiratory complications during induction. The chi-squared test was conducted to determine whether induction location was associated with level of behavioral compliance. A multivariable proportional odds model was used to control for risk factors. OR utilization and efficiency were analyzed using the Wilcoxon-Mann-Whitney test. RESULTS: There were no significant differences in ICC scores between the groups (P-value = 0.12). Anesthesia, nonoperative, and transport time were statistically less in the OR group when compared with the IR group, although total case process times were similar in both groups. While OR efficiency was significantly higher for the OR group (P-value = 0.0096), OR utilization did not differ between groups (P-value = 0.288). The OR group had a significantly higher number of anesthesia providers and a more experienced surgical team. Parents in the two groups were equally satisfied with their experience during induction, and none of the subjects had respiratory complications during the anesthesia induction. CONCLUSIONS: We found no differences in child distress, parent satisfaction, and respiratory complications between inductions conducted in the IR vs the OR. Differences in utilization, efficiency, and turnover were minimal and not operationally significant. Capital equipment, space, and staffing strategies should be key drivers in considerations for the use of IRs, and in the design of ORs with IRs.

Adaptive Care for Perioperative Patients With Developmental Disabilities: An Exploration of Interventions and Family Experience.

INTRODUCTION: Patients with developmental disabilities commonly experience psychological distress during health care visits. There is limited research describing which individualized interventions are being implemented to promote optimal care in the perioperative area. METHOD: In this prospective observational study of 60 patients with developmental diagnoses, aged 3-21 years, we recorded adaptive care plan (ACP) interventions and assessed family experience. RESULTS: Patients receiving ACPs had diverse diagnoses, including autism spectrum and 10 other unique syndromes. Most patients received previsit planning (90%), adaptations to standard protocols (60%), child life specialist preparation (67%), procedural support (90%), and were given fast-acting anxiolytics before anesthesia induction (68%). Families reported that ACPs were important for managing a child's stress (94%) and promoting safety (92%). DISCUSSION: ACPs promote safe, productive health care encounters for patients with various diagnoses, ages, and coping abilities. Families find ACPs important for stress management and promoting safety.

Quality of recovery from two types of general anesthesia for ambulatory dental surgery in children: a double-blind, randomized trial.

BACKGROUND: Pediatric dental procedures are increasingly performed under general anesthesia because of the inability to cooperate, situational anxiety, or other behavioral problems. Volatile anesthetics have been associated with emergence delirium in children, whereas the use of propofol for anesthetic maintenance has been shown to reduce the incidence of emergence delirium after other types of surgeries. The aim of this study is to compare a sevoflurane-based anesthetic with a propofol-based technique as it relates to the incidence of emergence delirium and the quality of recovery after pediatric dental surgery, in patients who present with risk factors for perioperative behavioral issues. METHODS: We prospectively collected data of 179 pediatric patients scheduled for ambulatory dental surgery using a double-blind and randomized trial design. Subjects were anesthetized following standardized protocols for either a sevoflurane- or a propofol-based technique. The incidence of emergency delirium, as measured by the Pediatric Anesthesia Emergence Delirium score, was the primary outcome. Secondary outcomes included the incidence of postoperative nausea and vomiting (PONV), number of nursing interventions in the recovery room, time to discharge readiness, and parental satisfaction. RESULTS: We found no difference in the incidence of emergence delirium after both types of anesthesia. However, use of sevoflurane significantly increased both the risk of PONV and the number of postoperative nursing interventions. Discharge criteria were met about 10 min earlier in patients anesthetized with sevoflurane. Parental satisfaction was equally high with both anesthesia regimens. CONCLUSIONS: A propofol-based anesthetic technique did not lead to a lower incidence of emergence delirium after dental surgery in children but did result in significantly less PONV and fewer postoperative nursing interventions.

Quality Initiative Using Theory of Change and Visual Analytics to Improve Controlled Substance Documentation Discrepancies in the Operating Room.

BACKGROUND: Discrepancies in controlled substance documentation are common and can lead to legal and regulatory repercussions. We introduced a visual analytics dashboard to assist in a quality improvement project to reduce the discrepancies in controlled substance documentation in the operating room (OR) of our free-standing pediatric hospital. METHODS: Visual analytics were applied to collected documentation discrepancy audit data and were used to track progress of the project, to motivate the OR team, and in analyzing where further improvements could be made. This was part of a seven-step improvement plan based on the Theory of Change with a logic model framework approach. RESULTS: The introduction of the visual analytics dashboard contributed a 24% improvement in controlled substance documentation discrepancy. The project overall reduced documentation errors by 71% over the studied period. CONCLUSION: We used visual analytics to simultaneously analyze, monitor, and interpret vast amounts of data and present them in an appealing format. In conjunction with quality-improvement principles, this led to a significant improvement in controlled substance documentation discrepancies.

Factors predictive of poor behavioral compliance during inhaled induction in children.

BACKGROUND: Preoperative identification of children at risk of emotional distress and poor behavioral compliance during inhaled induction of anesthesia allows targeted interventions to reduce distress, thereby enhancing the quality of the anesthetic experience. We sought to identify patient, procedural, and health care system factors predictive of poor behavioral compliance during induction. METHODS: We studied 861 developmentally appropriate children ages 1-13 yr, The American Society of Anesthesiologists physical status I to III, presenting for inhaled induction of anesthesia. All inductions were performed in an induction room with parent(s) present. Behavioral compliance was assessed using the Induction Compliance Checklist (ICC), an observational scale consisting of 10 behaviors scored as the number of behaviors observed during induction; ICC > or =4 was considered poor behavioral compliance. A multivariable ordinal logistic regression model for behavioral compliance was generated and the performance of the multivariable model was evaluated by the c statistic. RESULTS: Twenty-one percent of children exhibited poor behavioral compliance on induction. Factors increasing the odds of poor behavioral compliance were younger age (< 4 yr, P < 0.0001), shorter preoperative preparation time (P = 0.004), and high anxiety levels in the preoperative clinic (modified-Yale preoperative anxiety scale > 40; P = 0.016). Previous anesthesia experience increased the odds in school-age children (P = 0.046); this effect was ameliorated in children attending the preoperative tour (P = 0.018). The model using these factors demonstrated moderate discrimination between children with poor compliance and those with perfect compliance (ICC = 0) (c statistic = 0.75). CONCLUSIONS: Factors predictive of poor behavioral compliance were age, previous anesthesia, preoperative tour attendance, preoperative preparation time and anxiety levels in the preoperative clinic. These factors, bundled into a predictive algorithm, may help identify children who could benefit from behavioral or pharmacological interventions and avoid use of interventions to those at low risk.