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.

Emoticon use Increases Plain Milk and Vegetable Purchase in a School Cafeteria without Adversely Affecting Total Milk Purchase.

PURPOSE: Choosing poor-quality foods in school cafeterias is a risk factor for childhood obesity. Given the option, children often select chocolate milk over plain white milk. Efforts to increase plain white milk selection, such as banning chocolate milk in school cafeterias, increases plain white fat-free milk (PWFFM) purchase but decreases the overall milk purchase. The purpose of this study was to determine whether emoticon placement next to healthful foods would increase healthful purchases, particularly PWFFM. METHODS: In an inner city elementary school with 297 children, "Green Smiley Face" emoticons were placed to encourage the purchase of healthful foods including an entrée with whole grains, fruits, vegetables, and PWFFM. Purchase data were obtained from cash register receipts. Differences were analyzed by χ(2) Care and Statistical Process Control (SPC) and Graphical Methods. RESULTS: Only 7.4% of students selected white milk at baseline compared with 17.9% after the emoticons were placed (P < 0.0001). There was a decrease in chocolate milk purchase from 86.5% to 77.1% with the addition of the emoticons (P < 0.001). There was no significant difference in total milk purchase: 93.4% before the emoticons compared with 94.9% after. There was no significant change in the purchase of entrée or fruits. However, there was, a significant increase in vegetable purchase from 0.70 vegetables purchased per student per day to 0.90 by SPC (>8 points above the mean). IMPLICATIONS: The addition of emoticons increases the purchase of PWFFM and vegetables in a school cafeteria setting without adversely affecting total milk sales. Emoticons offer a practical, low-cost means to improve food selection by children.

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.

Redesigning intensive care unit flow using variability management to improve access and safety.

BACKGROUND: Poor flow of patients into and out of the ICU can result in gridlock and bottlenecks that disrupt care and have a detrimental effect on patient safety and satisfaction, hospital efficiency, staff stress and morale, and revenue. Beginning in 2006, Cincinnati Children's Hospital Medical Center implemented a series of interventions to "smooth" patient flow through the system. METHODS: Key activities included patient flow models based on surgical providers' predicted need for intensive care and predicted length of stay; scheduling the case and an ICU bed at the same time; capping and simulation models to identify the appropriate number of elective surgical cases to maximize occupancy without cancelling elective cases; and a morning huddle by the chief of staff, manager of patient services, and representatives from the operating room, pediatric ICUS, and anesthesia to confirm that day's plan and anticipate the next day's needs. RESULTS: New elective surgical admissions to the pediatric ICU were restricted to a maximum of five cases per day. Diversion of patients to the cardiac ICU, keeping patients in the postanesthesia care unit longer than expected, and delaying or canceling cases are now rare events. Since implementation of the operations management interventions, there have been no cases when beds in the pediatric ICU were not available when needed for urgent medical or surgical use. DISCUSSION: A system for smoothing flow, based on an advanced predictive model for need, occupancy, and length of stay, coupled with an active daily strategy for demand/capacity matching of resources and needs, allowed much better early planning, predictions, and capacity management, thereby ensuring that all patients are in suitable ICU environments.

Improving access to pediatric subspecialty care: initial failures and lessons learned.

OBJECTIVES: We originally examined the effectiveness of strategies, proven successful in improving appointment availability in primary care, at a large tertiary-care academic medical center. We then sought to describe the reasons for the initial failure of these strategies. METHODS: Clinics participating in an access improvement initiative were matched to control clinics. Intervention clinics used a variety of techniques to improve access. Run charts were used to determine the impact of the interventions on appointment availability. Linear models, control charts, and other graphic displays were used to understand the relationship among supply, demand, and appointment availability. RESULTS: Access did not improve in intervention clinics. Neither a linear models approach nor the use of control charts resulted in a simple tool to help clinics better understand the relationship among supply, demand, and days to third next available appointment. However, the development of a single clinic chart that incorporated supply and demand, plus estimates of future supply and demand, made it clear that current supply would not be able to meet demand. This helped teams focus their efforts on improving supply. CONCLUSIONS: Use of detailed data-based tools to guide choices of interventions, coupled with new and explicit institutional expectations for physician attendance at clinics, appears to be a promising strategy for enhancing access.