Understanding Pediatric Surgery Cancellation: Geospatial Analysis.

BACKGROUND: Day-of-surgery cancellation (DoSC) represents a substantial wastage of hospital resources and can cause significant inconvenience to patients and families. Cancellation is reported to impact between 2% and 20% of the 50 million procedures performed annually in American hospitals. Up to 85% of cancellations may be amenable to the modification of patients' and families' behaviors. However, the factors underlying DoSC and the barriers experienced by families are not well understood. OBJECTIVE: This study aims to conduct a geospatial analysis of patient-specific variables from electronic health records (EHRs) of Cincinnati Children's Hospital Medical Center (CCHMC) and of Texas Children's Hospital (TCH), as well as linked socioeconomic factors measured at the census tract level, to understand potential underlying contributors to disparities in DoSC rates across neighborhoods. METHODS: The study population included pediatric patients who underwent scheduled surgeries at CCHMC and TCH. A 5-year data set was extracted from the CCHMC EHR, and addresses were geocoded. An equivalent set of data >5.7 years was extracted from the TCH EHR. Case-based data related to patients' health care use were aggregated at the census tract level. Community-level variables were extracted from the American Community Survey as surrogates for patients' socioeconomic and minority status as well as markers of the surrounding context. Leveraging the selected variables, we built spatial models to understand the variation in DoSC rates across census tracts. The findings were compared to those of the nonspatial regression and deep learning models. Model performance was evaluated from the root mean squared error (RMSE) using nested 10-fold cross-validation. Feature importance was evaluated by computing the increment of the RMSE when a single variable was shuffled within the data set. RESULTS: Data collection yielded sets of 463 census tracts at CCHMC (DoSC rates 1.2%-12.5%) and 1024 census tracts at TCH (DoSC rates 3%-12.2%). For CCHMC, an L2-normalized generalized linear regression model achieved the best performance in predicting all-cause DoSC rate (RMSE 1.299%, 95% CI 1.21%-1.387%); however, its improvement over others was marginal. For TCH, an L2-normalized generalized linear regression model also performed best (RMSE 1.305%, 95% CI 1.257%-1.352%). All-cause DoSC rate at CCHMC was predicted most strongly by previous no show. As for community-level data, the proportion of African American inhabitants per census tract was consistently an important predictor. In the Texas area, the proportion of overcrowded households was salient to DoSC rate. CONCLUSIONS: Our findings suggest that geospatial analysis offers potential for use in targeting interventions for census tracts at a higher risk of cancellation. Our study also demonstrates the importance of home location, socioeconomic disadvantage, and racial minority status on the DoSC of children's surgery. The success of future efforts to reduce cancellation may benefit from taking social, economic, and cultural issues into account.

Surgical and anesthetic management for hepatectomy in two pediatric patients with trisomy 18, pulmonary hypertension, and hepatoblastoma.

Children with trisomy 18 are surviving longer and undergoing more aggressive life-sustaining therapy. This report describes two patients with trisomy 18 and hepatoblastoma (HB) successfully resected in the setting of significant pulmonary hypertension. Forty-four previously published cases of the association between HB and trisomy 18 are reviewed. With careful multidisciplinary preoperative planning, successful resection of HB in children with trisomy 18 who have significant pulmonary hypertension is feasible. Because HB and trisomy 18 are increasing in prevalence, the need for timely liver tumor resection in the setting of pulmonary hypertension will be more common.

Reducing Exposure to Opioid and Benzodiazepine Medications for Pediatric Cardiac Intensive Care Patients: A Quality Improvement Project.

OBJECTIVES: To evaluate the effect of implementation of a comfort algorithm on infusion rates of opioids and benzodiazepines in postneonatal postoperative pediatric cardiac surgery patients. DESIGN: A quality improvement project, using statistical process control methodology. SETTING: Twenty-five-bed tertiary care pediatric cardiac ICU in an urban academic Children's hospital. PATIENTS: Postoperative pediatric cardiac surgery patients. INTERVENTIONS: Implementation of a guided comfort medication algorithm which consisted of key components; a low dose opioid continuous infusion, judicious use of frequent as needed opioids, initiation of dexmedetomidine infusion postoperatively, and minimal use of benzodiazepines. MEASUREMENTS AND MAIN RESULTS: Among the baseline group admitted over the 18 month period prior to comfort algorithm implementation, 58 of 116 intubated patients (50%) received a continuous opioid infusion, compared with 30 of 41 (73%) for the implementation group over the 9-month period following implementation. Following algorithm implementation, opioid infusion rates were decreased and benzodiazepine infusions were nearly eliminated. Dexmedetomidine use and infusion rates did not change. Although mean duration of sedative drug infusions did not change with implementation, the frequency of high outliers was diminished. Duration of mechanical ventilation, length of ICU stay (outcome measures), and the frequency of unplanned extubation (balancing measure) were not affected by implementation. CONCLUSIONS: Implementation of a pediatric comfort algorithm reduced opioid and benzodiazepine dosing, without compromising safety for postoperative pediatric cardiac surgical patients.

Early Perioperative Management After Pediatric Cardiac Surgery: Review at PCICS 2014.

The sessions of the symposium held in December 2014 allow us to capitalize on the shared knowledge and experience that arise from both cardiac anesthesia and cardiac intensive care. During this session, topics that crossed traditional boundaries of pediatric cardiac intensive care and pediatric cardiac anesthesia were presented and discussed. This article summarizes the five topics presented at the symposium.

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.

Three-year prospective validation of a pre-endoscopic risk stratification in patients with acute upper-gastrointestinal haemorrhage.

OBJECTIVE: To assess the accuracy of a risk stratification that is used at initial assessment to identify groups with increased risk of mortality and requirement for urgent treatment intervention. DESIGN: Prospective assessment of risk stratification in consecutive patients with acute upper-gastrointestinal haemorrhage. METHODS: Over a 3-year period, 1349 consecutive patients with acute upper-gastrointestinal haemorrhage presenting to a single teaching hospital were prospectively risk stratified before endoscopy and followed up for outcome. MAIN OUTCOME MEASURES: Two-week, all-cause mortality, re-bleeding, and need for urgent treatment intervention. RESULTS: Stratification within the high-risk group predicted a significant increased risk of 2-week, all-cause mortality (P < 0.001) when compared with intermediate- and low-risk patients (11.8%, 3% and 0%, respectively), re-bleeding (P < 0.001) (44.1%, 2.3% and 0%, respectively), and need for urgent treatment intervention (P < 0.001) (71%, 40.6% and 2.6%, respectively). CONCLUSIONS: Over a 3-year period, medical staff at this institution have routinely used this risk stratification, which identifies groups of patients at high and low risk of mortality, re-bleeding and need for urgent treatment intervention following acute upper-gastrointestinal haemorrhage. Use of this risk stratification should allow targeting of more intensive treatment where it might be of most benefit. Those patients at lowest risk from outpatient management are also identified.