Airway Impedance: A Novel Diagnostic Tool to Predict Extraesophageal Airway Inflammation.

OBJECTIVE: To validate a novel biomarker, airway impedance for extraesophageal disease. STUDY DESIGN: We prospectively recruited patients with respiratory symptoms undergoing combined endoscopy and direct laryngoscopy for the evaluation of symptoms. The direct laryngoscopy was performed and videotaped for blinded scoring by 3 otolaryngologists and an impedance catheter was placed onto the posterior larynx to obtain measurements. Following this, an endoscopy was performed and impedance measurements and biopsies were taken at 3 esophageal heights. Impedance values were compared within and between patients. RESULTS: Eighty-eight patients were recruited, of which 73 had complete airway and endoscopic exams. There was no significant correlation between airway impedance values and mean reflux finding scores (r2 = 0.45, P = .07). There was no significant positive correlation between airway impedance and esophageal impedance values (r2 = 0.097-0.138, P > .2). Patients taking proton pump inhibitors had significantly lower mean airway impedance values (706 ± 450 Ω) than patients not taking them (1069 ± 809 Ω, P = .06). Patients who had evidence of aspiration on video fluoroscopic swallow studies had lower airway impedance (871 ± 615 Ω) than patients without aspiration (1247 ± 360 Ω, P = .008). Inhaled steroids did not impact airway impedance levels (P = .7). CONCLUSIONS: Airway impedance may be an important diagnostic tool to diagnose gastroesophageal reflux or aspiration, eliminating the subjectivity of airway appearance alone.

Assessing the Utility of a Machine-Learning Model to Assist With the Assignment of the American Society of Anesthesiology Physical Status Classification in Pediatric Patients.

BACKGROUND: The American Society of Anesthesiologists Physical Status Classification System (ASA-PS) is used to classify patients' health before delivering an anesthetic. Assigning an ASA-PS Classification score to pediatric patients can be challenging due to the vast array of chronic conditions present in the pediatric population. The specific aims of this study were to (1) suggest an ASA-PS score for pediatric patients undergoing elective surgical procedures using machine-learning (ML) methods; and (2) assess the impact of presenting the suggested ASA-PS score to clinicians when making their final ASA-PS assignment. The intent was not to create a new ASA-PS score but to use ML methods to generate a suggested score, along with information on how the score was generated (ie, historical information on patient comorbidities) to assist clinicians when assigning their final ASA-PS score. METHODS: A retrospective analysis of 146,784 pediatric surgical encounters from January 1, 2016, to December 31, 2019, using eXtreme Gradient Boosting (XGBoost) methods to predict ASA-PS scores using patients' age, weight, and chronic conditions. SHapley Additive exPlanations (SHAP) were used to assess patient characteristics that contributed most to the predicted ASA-PS scores. The predicted ASA-PS model was presented to a prospective cohort study of 28,677 surgical encounters from December 1, 2021, to October 31, 2022. The predicted ASA-PS score was presented to the anesthesiology provider for review before entering the final ASA-PS score. The study focused on summarizing the available information for the anesthesiologist by using ML methods. The goal was to explore the potential for ML to provide assistance to anesthesiologists by highlighting potential areas of discordance between the variables that generated a given ML prediction and the physician's mental model of the patient's medical comorbidities. RESULTS: For the retrospective analysis, the distribution of predicted ASA-PS scores was 22.7% ASA-PS I, 48.5% II, 23.6% III, 5.1% IV, and 0.04% V. The distribution of clinician-assigned ASA-PS scores was 24.3% for ASA-PS I, 44.5% for ASA-PS II, 24.9% for ASA III, 6.1% for ASA-PS IV, and 0.2% for ASA-V. In the prospective analysis, the final ASA-PS score matched the initial ASA-PS 90.7% of the time and 9.3% were revised after viewing the predicted ASA-PS score. When the initial ASA-PS score and the ML ASA-PS score were discrepant, 19.5% of the cases have a final ASA-PS score which is different from the initial clinician ASA-PS score. The prevalence of multiple chronic conditions increased with ASA-PS score: 34.9% ASA-PS I, 73.2% II, 92.3% III, and 94.4% IV. CONCLUSIONS: ML derivation of predicted pediatric ASA-PS scores was successful, with a strong agreement between predicted and clinician-entered ASA-PS scores. Presentation of predicted ASA-PS scores was associated with revision in final scoring for 1-in-10 pediatric patients.

The Pediatric-Specific American Society of Anesthesiologists Physical Status Score: A Multicenter Study.

BACKGROUND: When applied to the pediatric population, the American Society of Anesthesiologists physical status (ASA-PS) classification has exhibited poor reliability due to its subjective and adult-focused definitions. This study was done to measure interrater agreement of a pediatric-adapted ASA-PS classification and to solicit multicenter perspectives to optimize the pediatric ASA-PS classification. METHODS: A prospective, mixed-methods study of 197 pediatric anesthesiologists from 13 academic pediatric hospitals in the United States, Europe, and Australia surveyed in May and July 2019. Participants assigned ASA-PS scores (I to V) for 15 pediatric cases with a heterogeneous mix of acute and chronic health conditions undergoing a variety of surgical and related procedures. Pediatric-adapted definitions of ASA-PS were provided. The intraclass correlation coefficient (ICC) was used to assess interrater reliability of ASA-PS scores. The ICC was estimated using 2-way mixed-effects modeling, accounting for multiple raters assigning scores for the same set of cases. Qualitative feedback on the pediatric-adapted ASA-PS classification was analyzed with line-by-line coding. RESULTS: The survey response rate was 83.8% (165 of 197). The ICC agreement among participants on ASA-PS scoring across all 15 clinical cases was 0.58 (95% confidence interval [CI], 0.42-0.77). ICC did not vary significantly by years of anesthesiology practice. ICC varied across hospitals (range: 0.34; 95% CI, 0.12-0.63 to 0.79; 95% CI, 0.66-0.91). The highest level of agreement occurred with cases most often scored as ASA-PS I, IV, and V; the lowest agreement occurred with cases most often scored ASA-PS II and III. Clarification of how well a chronic condition was controlled and presence of an acute illness were 2 common themes suggested to optimize the validity of the pediatric-adapted ASA-PS definitions. CONCLUSIONS: The pediatric-adapted ASA-PS classification had moderate interrater reliability among pediatric anesthesiologists. The lower reliability of scoring for ASA-PS II and III cases, in particular, supports the need for further ASA-PS definition refinement for pediatric populations.

Hospital Volumes of Inpatient Pediatric Surgery in the United States.

BACKGROUND: Perioperative outcomes of children depend on the skill and expertise in managing pediatric patients, as well as integration of surgical, anesthesiology, and medical teams. We compared the types of pediatric patients and inpatient surgical procedures performed in low- versus higher-volume hospitals throughout the United States. METHODS: Retrospective analysis of 323,258 hospitalizations with an operation for children age 0 to 17 years in 2857 hospitals included in the Agency for Healthcare Research and Quality (AHRQ) Kids' Inpatient Database (KID) 2016. Hospitals were categorized by their volume of annual inpatient surgical procedures. Specific surgeries were distinguished with the AHRQ Clinical Classification System. We assessed complex chronic conditions (CCCs) using Feudtner and Colleagues' system. RESULTS: The median annual volume of pediatric inpatient surgeries across US hospitals was 8 (interquartile range [IQR], 3-29). The median volume of inpatient surgeries for children with a CCC was 4 (IQR, 1-13). Low-volume hospitals performed significantly fewer types of surgeries (median 2 vs 131 types of surgeries in hospitals with 1-24 vs ≥2000 volumes). Appendectomy and fixation of bone fracture were among the most common surgeries in low-volume hospitals. As the volume of surgical procedures increased from 1 to 24 to ≥2000, the percentage of older children ages 11 to 17 years decreased (70.9%-32.0% [P < .001]) and the percentage of children with a CCC increased (11.2%-60.0% [P < .001]). CONCLUSIONS: Thousands of US hospitals performed inpatient surgeries on few pediatric patients, including those with CCCs who have the highest risk of perioperative morbidity and mortality. Evaluation of perioperative decision making, workflows, and pediatric clinicians in low- and higher-volume hospitals is warranted.

The virtual pediatric perioperative home, experience at a major metropolitan safety net hospital.

INTRODUCTION: Successes from anesthesiologist-led perioperative surgical homes in the adult patient population have inspired similar initiatives by pediatric hospitals. Typically the care coordination for these perioperative homes is run through hospital-funded, on-site, preanesthesia clinics. Preliminary data from pediatric perioperative homes have shown promising results in improved patient outcomes and decreased length of hospital stay. The majority of pediatric surgeries within the country are performed in nonpediatric hospitals. Such centers may not have the infrastructure or financial resources for a freestanding pediatric preanesthesia clinic. Faced with this situation at the largest safety net hospital in New England, the authors present their experience designing and implementing a "Virtual Pediatric Perioperative Home," a telemedicine-based triage and preanesthetic optimization for pediatric patients at Boston Medical Center, Boston, MA. METHODS: A retrospective chart review of all pediatric anesthesia cases at Boston Medical Center from February 1, 2019, to January 31, 2020, as well as the number of pediatric cases canceled or postponed on the day of surgery for any reason during the same time period was conducted. RESULTS: From February 1, 2019, to January 31, 2020, 1546 anesthetics were performed in children 18 years and under. Of those, 63 were designated as emergent and hence excluded from our analysis. 153 of the total 1483 (9.4%) of nonemergent bookings were canceled or postponed on the day of surgery. This represented a marked decline from our previous year's 13.7% same-day cancellation rate for pediatric patients. The most common reason for case cancellations (41.8%) was acute illness. Cancellation rates varied from month to month, with the highest cancellation rate of the year in September 2019 (18.8%). The departments of Podiatry and Gastroenterology represented the highest cancellation rates as a denominator of their case volumes, 15.4% and 15.2%, respectively. Younger children had 2.4 times the odds (95% CI: 1.720, 3.4) of cancellation compared to older children. DISCUSSION: The virtual pediatric perioperative home (VPPH) may benefit quality of care while decreasing costs to pediatric patients, families, and hospital systems. While direct financial gains may be difficult to demonstrate, the VPPH has the potential to reduce OR delays and same day cancellations related to questions of medical optimization. In the context of a socioeconomically disadvantaged patient population, our VPPH's team of subspecialists created inroads for at risk children to establish or reestablish care for their comorbidities, while collaboration with the Department of Children and Families further streamlined communication and consent for pediatric patients in foster care. CONCLUSIONS: The authors describe the design and successful implementation of a telemedicine-based pediatric preanesthesia triage and medical optimization service at a large safety net hospital. By creating a communication network of pediatric subspecialists, the anesthesiologists were able to, at minimal institutional cost, coordinate care for children with a variety of comorbidities leading up to the day of surgery. This yielded a 9.4% same day cancellation rate in a complex, socioeconomically disadvantaged pediatric patient population at a general hospital.

One Size Does Not Fit All: A Perspective on the American Society of Anesthesiologists Physical Status Classification for Pediatric Patients.

BACKGROUND: The American Society of Anesthesiologists physical status (ASA-PS) classification system is used worldwide to classify patients based on comorbid conditions before general anesthesia. Despite its popularity, the ASA-PS classification system has been shown to have poor interrater reliability due to its subjective definitions, especially when applied to the pediatric population. We hypothesized that the clarification of ASA-PS definitions to better reflect pediatric conditions would improve the accuracy of ASA-PS applied to this population. METHODS: A stratified, randomized sample of 120 pediatric surgical cases was collected from a tertiary-care pediatric hospital. A team of senior anesthesiologists reclassified ASA-PS within this patient sample using the suggested pediatric-specific ASA-PS definitions. Interrater reliability was measured using intraclass correlation (ICC) and Fleiss κ statistic. In addition, a qualitative study component using small focus groups of senior anesthesiologists identified areas of ambiguity within the ASA-PS system. RESULTS: Among the 90 reclassifications within each ASA-PS group, 42.2% (n = 38) of ASA-PS I were upgraded to ASA-PS II, and 36.7% (n = 33) of ASA-PS II were upgraded to ASA-PS III. In addition, 28.9% (n = 26) of ASA-PS III were upgraded to ASA-PS IV, and 24.4% (n = 22) of ASA-PS IV were downgraded to III. ICC across the reclassified ASA-PS categories was 0.77 (95% confidence interval [CI], 0.71-0.83; P < .001) demonstrating strong overall agreement. Fleiss κ statistic was lowest in ASA-PS II and III patients (κ = 0.41 and κ = 0.30, respectively) indicating lower agreement beyond chance within these subgroups. Focus groups revealed common themes such as active sequelae of disease, active versus well-controlled presence of comorbidities, and the possible inclusion of functional limitations as important considerations. CONCLUSIONS: The ASA-PS classification system has several benefits including ease-of-use, simplicity, and flexibility. However, revising the ASA-PS system to provide better guidance for pediatric patients could be valuable. While this study demonstrates good interrater reliability with the included ASA-PS pediatric definitions, further work is needed to clarify accurate assignment of ASA-PS within the midrange of the scale (ASA-PS II and III) and explore its implementation in other institutions.

Comprehensive Risk Assessment of Morbidity in Pediatric Patients Undergoing Noncardiac Surgery: An Institutional Experience.

BACKGROUND: Utilizing the intrinsic surgical risk (ISR) and the patient's chronic and acute conditions, this study aims to develop and validate a comprehensive predictive model of perioperative morbidity in children undergoing noncardiac surgery. METHODS: Following institutional review board (IRB) approval at a tertiary care children's hospital, data for all noncardiac surgical encounters for a derivation dataset from July 2017 to December 2018 including 16,724 cases and for a validation dataset from January 2019 to December 2019 including 9043 cases were collected retrospectively. The primary outcome was a composite morbidity score defined by unplanned transfer to an intensive care unit (ICU), acute respiratory failure requiring intubation, postoperative need for noninvasive or invasive positive pressure ventilation, or cardiac arrest. Internal model validation was performed using 1000 bootstrap resamples, and external validation was performed using the 2019 validation cohort. RESULTS: A total of 1519 surgical cases (9.1%) experienced the defined composite morbidity. Using multivariable logistic regression, the Risk Assessment of Morbidity in Pediatric Surgery (RAMPS) score was developed with very good predictive ability in the derivation cohort (area under the curve [AUC] = 0.805; 95% confidence interval [CI], 0.795-0.816), very good internal validity using 1000 bootstrap resamples (bias-corrected Nagelkerke R = 0.21 and Brier score = 0.07), and good external validity (AUC = 0.783; 95% CI, 0.770-0.797). The included variables are age <5 years, critically ill, chronic condition indicator (CCI) ≥3, significant CCI ≥2, and ISR quartile ≥3. The RAMPS score ranges from 0 to 10, with the risk of composite morbidity ranging from 1.8% to 42.7%. CONCLUSIONS: The RAMPS score provides the ability to identify a high-risk cohort of pediatric patients using a 5-component tool, and it demonstrated good internal and external validity and generalizability. It also provides an opportunity to improve perioperative planning with the intent of improving both individual-patient outcomes and the appropriate allocation of health care resources.

Implementing a Pediatric Perioperative Surgical Home Integrated Care Coordination Pathway for Laryngeal Cleft Repair.

BACKGROUND: The Pediatric Perioperative Surgical Home (PPSH) model is an integrative care model designed to provide better patient care and value by shifting focus from the patient encounter level to the overarching surgical episode of care. So far, no PPSH model has targeted a complex airway disorder. It was hypothesized that the development of a PPSH for laryngeal cleft repair would reduce the high rates of postoperative resource utilization observed in this population. METHODS: Institutional review board approval was obtained for the purpose of data collection and analysis. A multidisciplinary team of anesthesiologists, surgeons, nursing staff, information technology specialists, and finance administrators was gathered during the PPSH development phase. Standardized perioperative (preoperative, intraoperative, and postoperative) protocols were developed, with a focus on preoperative risk stratification. Patients presenting before surgery with ≥1 predefined medical comorbidity were triaged to the intensive care unit (ICU) postoperatively, while patients without severe systemic disease were triaged to a lower-acuity floor for overnight observation. The success of the PPSH protocol was defined by quality outcome and value measurements. RESULTS: The PPSH initiative included 120 patients, and the pre-PPSH period included 115 patients who underwent laryngeal cleft repair before implementation of the new process. Patients in the pre-PPSH period were reviewed and classified as ICU candidates or lower acuity floor candidates had they presented in the post-PPSH period. Among the 79 patients in the pre-PPSH period who were identified as candidates for the lower-acuity floor transfer, 70 patients (89%) were transferred to the ICU (P < .001). Retrospective analysis concluded that 143 ICU bedded days could have been avoided in the pre-PPSH group by using PPSH risk stratification. Surgery duration (P = .034) and hospital length of stay (P = .015) were found to be slightly longer in the group of pre-PPSH observation unit candidates. Rates of 30-day unplanned readmissions to the hospital were not associated with the new PPSH initiative (P = .093). No patients in either group experienced emergent postoperative intubation or other expected complications. Total hospital costs were not lower for PPSH observation unit patients as compared to pre-PPSH observation unit candidates (difference = 8%; 95% confidence interval, -7% to 23%). CONCLUSIONS: A well-defined preoperative screening protocol for patients undergoing laryngeal cleft repair can reduce postoperative ICU utilization without affecting patient safety. Further research is needed to see if these findings are applicable to other complex airway surgeries.

Making the pediatric perioperative surgical home come to life by leveraging existing health information technology.

PURPOSE OF REVIEW: To design a patient data dashboard for the Department of Anesthesiology, Perioperative and Pain Medicine at Boston Children's Hospital that supports care integration across the healthcare system as described by the pediatric perioperative surgical home (PPSH) initiative. RECENT FINDINGS: By using 360 Technology, patient data was automatically pulled from all available Electronic Health Record sources from 2005 to the present. The PPSH dashboard described in this report provides a guide for implementation of PPSH Clinical Care Pathways. The dashboard integrates several databases to allow for visual longitudinal tracking of patient care, outcomes, and cost. The integration of electronic information provided the ability to display, compare, and analyze selected PPSH metrics in real time. By utilizing the PPSH dashboard format the use of an automated, integrated clinical, and financial health data profile for a specific patient population may improve clinicians' ability to have a comprehensive assessment of all care elements. This more global clinical thinking has the potential to produce bottom-up, evidence-based healthcare reform. SUMMARY: The experience with the PPSH dashboard provides solid evidence for the use of integrated Electronic Health Record to improve patient outcomes and decrease cost.

The nature and sources of variability in pediatric surgical case duration.

BACKGROUND: Case time variability confounds surgical scheduling and decreases access to limited operating room resources. Variability arises from many sources and can differ among institutions serving different populations. A rich literature has developed around case time variability in adults, but little in pediatrics. OBJECTIVE: We studied the effect of commonly used patient and procedure factors in driving case time variability in a large, free-standing, academic pediatric hospital. METHODS: We analyzed over 40 000 scheduled surgeries performed over 3 years. Using bootstrapping, we computed descriptive statistics for 249 procedures and reported variability statistics. We then used conditional inference regression trees to identify procedure and patient factors associated with pediatric case time and evaluated their predictive power by comparing prediction errors against current practice. Patient and procedure factors included patient's age and weight, medical status, surgeon identity, and ICU request indicator. RESULTS: Overall variability in pediatric case time, as reflected by standard deviation, was 30% (25.8, 34.7) of the median case time. Relative variability (coefficient of variation), was largest among short cases. For a few procedure types, the regression tree can improve prediction accuracy if extreme behavior cases are preemptively identified. However, for most procedure types, no useful predictive factors were identified and, most notably, surgeon identity was unimportant. CONCLUSIONS: Pediatric case time variability, unlike adult cases, is poorly explained by surgeon effect or other characteristics that are commonly abstracted from electronic records. This largely relates to the 'long-tailed' distribution of pediatric cases and unpredictably long cases. Surgeon-specific scheduling is therefore unnecessary and similar cases may be pooled across surgeons. Future scheduling efforts in pediatrics should focus on prospective identification of patient and procedural specifics that are associated with and predictive of long cases. Until such predictors are identified, daily management of pediatric operating rooms will require compensatory overtime, capacity buffers, schedule flexibility, and cost.

Preoperative electrocardiograms for nonsyndromic children with hand syndactyly.

PURPOSE: To examine the efficacy of preoperative electrocardiogram (EKG) screening for Timothy syndrome, a rare and fatal condition characterized by prolonged QT, in children referred for syndactyly release. METHODS: We reviewed the records of nonsyndromic syndactyly patients seen by a hand surgeon at our institution between 2007 and 2013. All underwent a preoperative screening EKG for Timothy syndrome. We reviewed the medical records for demographics, presentation, EKG results, and operative findings, and calculated median age at the time of EKG and surgery and frequency distributions for sex, side affected, EKG result, and clinical finding. The mean patient charge for EKG and interpretation was calculated. RESULTS: We identified 128 syndactyly patients, 72% of which were boys. Median age at the time of EKG testing and syndactyly release was 1 year. A total of 92% of patients had normal EKG results; one patient exhibited a prolonged QT. Ten patients (8%) had further cardiac evaluation because of the EKG result and were found to be normal on repeat testing. No patient met QT threshold for Timothy syndrome and all patients were cleared for surgery. The minimum patient charge for EKG testing was $183. CONCLUSIONS: To improve patient safety, some have advocated preoperative EKG testing for all children undergoing syndactyly release to rule out Timothy syndrome. Analysis of our experience failed to yield an instance of Timothy syndrome over a 7-year period. Although EKG charges were relatively low, costs resulting from additional testing, cardiology consultation, and provider and parent time should be considered. Our study does not support routine EKG testing for children referred for syndactyly release, and we have abandoned this practice. TYPE OF STUDY/LEVEL OF EVIDENCE: Prognostic IV.

Factors Affecting Length of Stay for Children Hospitalized After Pediatric Surgical Procedures.

BACKGROUND: Understanding the postoperative length of stay (LOS) by surgical procedure is important for hospital medicine clinicians involved in surgical co-management. We assessed variation in postoperative LOS for children after elective surgical procedures and risk factors for prolonged LOS. METHODS: This study is a retrospective analysis of pediatric patients undergoing elective surgical procedures between January 1, 2018 and October 1, 2021 with postoperative hospitalization for recovery at a freestanding children's hospital. The postoperative LOS (number of days) was compared across types of surgery and by the number of chronic conditions (assessed with the Agency for Healthcare Research and Quality Condition Indicator system) using multivariable quantile regression. RESULTS: The median (interquartile range) LOS across all 347 types of surgical procedures combined was 2 (interquartile range 1-4). Surgical procedures (n = 85) with a median LOS between 3.0 and <5.0 days (eg, spinal fusion, Chiari decompression) accounted for 20.9% of all hospitalizations (N = 12 139) and 23.1% of all postoperative bed days. Procedures (n = 46) with a median LOS of ≥5.0 days (eg, femoral osteotomy, bladder reconstruction) accounted for 15.0% and 46.8% of all hospitalizations and bed days, respectively. After controlling for the type of procedure, having ≥4 (versus none) chronic conditions was significantly associated with experiencing a prolonged LOS (90th percentile: 5.2 days); patients with 4 to 6, versus no, chronic conditions stayed a median of 1.4 (95% confidence interval [CI] 0.7-2.2) days longer, those with 7 to 9 chronic conditions stayed a median of 1.9 (95% CI 1.0-2.7) days longer, and those with ≥10 chronic conditions stayed a median of 4.0 (95% CI 3.3-4.7) days longer. CONCLUSIONS: Hospital medicine clinicians can use the type of surgery in combination with the number of chronic conditions to estimate postoperative LOS after elective surgical procedures in children.

Child Opportunity Index Disparities in Pediatric Surgical Encounters During the Coronavirus 2019 Pandemic.

OBJECTIVE: Surgical encounters decreased during the coronavirus disease (COVID-19) pandemic and may have been deferred more in children with impeded health care access related to social/community risk factors. We compared surgery trends before and during the pandemic by Child Opportunity Index (COI). METHODS: Retrospective analysis of 321,998 elective surgical encounters of children ages 0-to-18 years in 44 US children's hospitals from January 1, 2017 to December 31, 2021. We used auto-regression to compare observed versus predicted encounters by month in 2020-21, modeled from 2017 to 2019 trends. Encounters were compared by COI score (very low, low, moderate, high, very high) based on education, health/environment, and social/economic attributes of the zip code from the children's home residence. RESULTS: Most surgeries were on the musculoskeletal (28.1%), ear/nose/pharynx (17.1%), cardiovascular (15.1%), and digestive (9.1%) systems; 20.6% of encounters were for children with very low COI, 20.8% low COI, 19.8% moderate COI, 18.6% high COI, and 20.1% very high COI. Reductions in observed volume of 2020-21 surgeries compared with predicted varied significantly by COI, ranging from -11.3% (95% confidence interval [CI] -14.1%, -8.7%) for very low COI to -2.6% (95%CI -3.9%, 0.7%) for high COI. Variation by COI emerged in June 2020, as the volume of elective surgery encounters neared baseline. For 12 of the next 18 months, the reduction in volume of elective surgery encounters was the greatest in children with very low COI. CONCLUSIONS: Children from very low COI zip codes experienced the greatest reduction in elective surgery encounters during early COVID-19 without a subsequent increase in encounters over time to counterbalance the reduction.

Laryngeal cleft repair: the anesthetic perspective.

INTRODUCTION: Laryngeal cleft is a rare congenital malformation that is being reported with increasing frequency. Diagnosis requires suspension microlaryngoscopy under general anesthesia during spontaneous respiration. Repair may be attempted by a minimally invasive endoscopic approach or open surgical repair. The authors report on their experience with total intravenous anesthesia (TIVA) and spontaneous ventilation without an endotracheal tube during suspension laryngoscopy and CO2 laser application for this specific surgical procedure. Of particular interest were the rate at which this technique failed and rescue techniques were employed and the ability to predict patients in whom this might occur. METHODS: Between July 2004 and September 2012, 110 endoscopic laryngeal cleft repairs were completed under TIVA with spontaneous ventilation without an endotracheal tube. Anesthetic induction was achieved by inhalation of sevoflurane and oxygen by mask or infusion of propofol at 300 mcg kg(-1) min(-1) and remifentanil at 0.05-1.0 mcg kg(-1)  min. The vocal cords and surgical site were sprayed with up to 2 mg kg(-1) of 4% lidocaine. If the oxygen saturation decreased during the procedure or the patient became apneic, a rescue process utilizing jet ventilation or intermittent intubation was instituted. RESULTS: Ten (9.1%) of the 110 cases required rescue (95% confidence interval [CI]: 5.0-15.8%). The most prevalent comorbidities included reactive airway disease, chronic lung disease, failure to thrive, developmental delay, and an unrelated syndrome. Thirty-nine patients (36%) had reactive airway disease and twelve (11%) had chronic lung disease. Intraoperative complications included six cases requiring a brief, temporary period of intubation (5.5%) and four cases requiring a brief period of jet ventilation (3.6%). CONCLUSION: The technique of TIVA with spontaneous respirations without an endotracheal tube is a safe and effective technique for laryngeal cleft repair. Although the potential for intraoperative adverse events may be high, the actual rate was very low. The need to convert to other techniques is not significant although the children who did require brief periods of jet ventilation or intubation tended to have reactive airway disease or chronic lung disease.

Variability in Resource Utilization in the Evaluation and Management of Simple Febrile Seizures Inpatients in US Children's Hospitals.

OBJECTIVE: To characterize resource utilization in the evaluation and treatment of hospitalized simple febrile seizure (SFS) patients in US tertiary pediatric hospitals. METHODS: This is a retrospective cohort study using the Pediatric Health Information System from 2010 to 2015. Children 6 months to 5 years of age who were inpatients with a diagnosis of SFS. Children who had brain magnetic resonance imaging (MRI), electroencephalography (EEG), or received anticonvulsants were compared with those who did not have testing or anticonvulsant treatment. Hospital-level variation in the utilization rates of MRI, EEG, or treatment with anticonvulsants was also evaluated. RESULTS: In Pediatric Health Information System-participating institutions, 8.4% (n=3640) of children presenting to the emergency department with SFS were hospitalized. Among these SFS inpatients, 57.8% (n= 2104) did not receive further evaluation with MRI/EEG or treatment with anticonvulsants. There was evidence of wide inter-hospital variation in resource utilization rates. The median (interquartile range) utilization rate was 6.2% (3.0 to 11.0%) for MRI, 28.5% (16.0 to 46.3%) for EEG and 17.1% (10.9 to 22.3%) for treatment with anticonvulsants. CONCLUSION: No specific hospital-level factors were identified that contributed to the variation in resource utilization in the evaluation and management of hospitalized SFS patients.

Criteria for assessing operating room utilization in a free-standing children's hospital.

BACKGROUND: The staffed hours of operation in any surgical facility are a valuable institutional resource. The realistic target for the utilization of this resource is dependent on many factors including scheduling, efficiency, and culture of the facility. There is no previously reported measure for the actual utilization of staffed regular operating room (OR) hours in an academic pediatric institution. The leadership of the perioperative services at Children's Hospital Boston (CHB) sought to define the utilization of surgical suite staffed block time hours at that institution and in addition determine whether changes in workflow could increase the measured utilization. METHODS: Operating room efficiency in fiscal year 2009 was measured using two variables: utilization and turnover measured in hours for each month in fiscal year 2009, recorded in hours expressed as ratios (observed/expected) and as differences (observed - expected). A total of 27,851 cases from October 1, 2008, through September 30, 2009, were analyzed. All elective cases were scheduled electronically following institutional guidelines; urgent or emergent procedures were scheduled into vacant time slots on the day of the procedure. Time series analysis based on a generalized autoregressive moving average process was used to compare expected with observed utilization and to evaluate changes in utilization and turnover ratios. RESULTS: Efficiency as measured by capped utilization divided by total available time in the OR averaged 79%. Utilization ratios ranged from a low of 73% in February 2009 to a high of 87% in July 2009. An improvement in on-time first-case starts may have contributed to the increase in the utilization of staffed block time. Turnover time as defined by turnover ratio decreased significantly over time, indicating an improved efficiency in the OR starting in April 2009. CONCLUSIONS: Adhering to the specific guidelines that are followed at CHB, the mean utilization of scheduled block time was 79%. This was achieved by maximizing workflow in the surgical, anesthesia, and nursing disciplines to shorten turnover time, fill gaps in the elective schedule with emergency procedures, and provide staffing to accommodate cases that extend beyond the scheduled staffed time prior to the reporting period. Simulated models from other pediatric institutions suggest that the optimal utilization of designated time periods in a surgical facility may range from 85% to 90%.