Enhancing Recovery in Congenital Cardiac Surgery.

BACKGROUND: The benefits of a comprehensive enhanced recovery after surgery (ERAS) program for patients with congenital heart disease are largely unknown. This study evaluated adherence and to outcomes of a recently implemented enhanced recovery program (ERP) in congenital cardiac surgery. METHODS: Patients undergoing elective procedures for simple and moderately complex congenital cardiac surgery have followed institutional ERP guidelines since October 2018. Adherence to guidelines over a 12-month period (P2) was compared with implementation data (P1, 5 months). The association of outcomes with continuous time was estimated using linear regression. RESULTS: Among 559 patients (representing 40% of the cardiac surgical volume) following the ERP over a period of 17 months, no differences in patient characteristics were observed between periods, except a higher incidence of previous operations in P2. Adherence to many aspects of guidelines improved from P1 to P2. The following improvements were notable: operating room extubation, 27% in P2 vs16% in P1 (P = .006); and a decrease in median ventilation time, 6.0 hours (interquartile range [IQR], 0-9.2 hours) in P2 vs 7.6 hours (IQR, 3.8-12.3 hours) in P1 (P = .002). In addition, there was a reduction in opioids, reported as oral morphine equivalents, that was most significant for intraoperative oral morphine equivalents: 5.00 mg/kg (IQR, 3.11-7.60 mg/kg) in P2 vs 6.05 mg/kg (IQR, 3.77-9.78 mg/kg) in P1 (P = .001). There was no difference in overall intensive care unit and postoperative lengths of stay, except in lower-risk surgical procedures. Surgical outcomes were similar in the 2 periods. CONCLUSIONS: An enhanced recovery program reduced the use of opioids, led to more extubation in the operating room, and reduced mechanical ventilation duration in patients undergoing congenital cardiac surgery.

Initial experience introducing an enhanced recovery program in congenital cardiac surgery.

OBJECTIVE: We hypothesized that a new enhanced recovery after surgery (ERAS) program would accelerate functional recovery after congenital heart surgery and reduce length of stay and complications. METHODS: Evidence-based interventions in perioperative care were evaluated for relevance, and components of the ERAS cardiac program were determined. The target patient population included infants to adults with low comorbidities. Major outcomes were compared to a pre-ERAS era cohort using propensity matching. RESULTS: From October 1, 2018, to February 28, 2019, 155 of 448 patients were eligible for the ERAS program. The median age was 3.6 years (interquartile range, 0.5-12.3). Key metrics included early extubation (<8 hours), achieved in 84 patients (54%; median 7.6 hours; interquartile range, 3.8-12.3), and multimodal pain regimen used in all patients (100%) postoperatively, but in only 88 of 155 patients (57%) intraoperatively. Opioid analgesia was highest the night of surgery (oral morphine equivalent: 0.36 mg/kg/12 hours; interquartile range, 0.21-0.57). In matched analysis, raw median mechanical ventilation time was 7.6 hours (interquartile range, 3.8-12.2) in ERAS versus 8.2 (interquartile range, 4.0-17.0) in pre-ERAS era (P = .001 log-hours). Raw median intensive care unit length of stay was shorter with ERAS: 1.12 days (interquartile range, 0.93-2.01) versus 1.28 days (interquartile range, 0.96-2.09) pre-ERAS (P = .046 log-days), but there was no difference in hospital length of stay. There was no increase in Society of Thoracic Surgeons-reported complications, readmissions, and reinterventions. CONCLUSIONS: This represents the initial implementation experience of an enhanced recovery after surgery program after congenital surgery at a large pediatric hospital. Adherence to the program component metrics is not yet optimized, but monthly sharing of quality metrics allows multidisciplinary collaboration, provider engagement, and opportunities for research and process improvement.

Variation in Case-Mix Adjusted Unplanned Pediatric Cardiac ICU Readmission Rates.

OBJECTIVES: To identify modifiable factors leading to unplanned readmission and characterize differences in adjusted unplanned readmission rates across hospitals. DESIGN: Retrospective cohort study using prospectively collected clinical registry data SETTING:: Pediatric Cardiac Critical Care Consortium clinical registry. PATIENTS: Patients admitted to a pediatric cardiac ICU at Pediatric Cardiac Critical Care Consortium hospitals. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We examined pediatric cardiac ICU encounters in the Pediatric Cardiac Critical Care Consortium registry from October 2013 to March 2016. The primary outcomes were early (< 48 hr from pediatric cardiac ICU transfer) and late (2-7 d) unplanned readmission. Generalized logit models identified independent predictors of unplanned readmission. We then calculated observed-to-expected ratios of unplanned readmission and identified higher-than or lower-than-expected unplanned readmission rates for those with an observed-to-expected ratios greater than or less than 1, respectively, and a 95% CI that did not cross 1. Of 11,301 pediatric cardiac ICU encounters (16 hospitals), 62% were surgical, and 18% were neonates. There were 175 (1.6%) early unplanned readmission, and 300 (2.7%) late unplanned readmission, most commonly for respiratory (31%), or cardiac (28%) indications. In multivariable analysis, unique modifiable factors were associated with unplanned readmission. Although shorter time between discontinuation of vasoactive infusions and pediatric cardiac ICU transfer was associated with early unplanned readmission, nighttime discharge was independently associated with a greater likelihood of late unplanned readmission. Two hospitals had lower-than-expected unplanned readmission in both the early and late categories, whereas two other hospitals were higher-than-expected in both. CONCLUSIONS: This analysis demonstrated time from discontinuation of critical care therapies to pediatric cardiac ICU transfer as a significant, modifiable predictor of unplanned readmission. We identified two hospitals with lower-than-expected adjusted rates of both early and late unplanned readmission, suggesting that their systems are well designed to prevent unplanned readmission. This offers the possibility of disseminating best practices to other hospitals through collaborative learning.

Accurate Prediction of Congenital Heart Surgical Length of Stay Incorporating a Procedure-Based Categorical Variable.

OBJECTIVES: There is increasing demand for the limited resource of Cardiac ICU care. In this setting, there is an expectation to optimize hospital resource use without restricting care delivery. We developed methodology to predict extended cardiac ICU length of stay following surgery for congenital heart disease. DESIGN: Retrospective analysis by multivariable logistic regression of important predictive factors for outcome of postoperative ICU length of stay greater than 7 days. SETTING: Cardiac ICU at Boston Children's Hospital, a large, pediatric cardiac surgical referral center. PATIENTS: All patients undergoing congenital heart surgery at Boston Children's Hospital from January 1, 2010, to December 31, 2015. INTERVENTIONS: No study interventions. MEASUREMENTS AND MAIN RESULTS: The patient population was identified. Clinical variables and Congenital Heart Surgical Stay categories were recorded based on surgical intervention performed. A model was built to predict the outcome postoperative ICU length of stay greater than 7 days at the time of surgical intervention. The development cohort included 4,029 cases categorized into five Congenital Heart Surgical Stay categories with a C statistic of 0.78 for the outcome ICU length of stay greater than 7 days. Explanatory value increased with inclusion of patient preoperative status as determined by age, ventilator dependence, and admission status (C statistic = 0.84). A second model was optimized with inclusion of intraoperative factors available at the time of postoperative ICU admission, including cardiopulmonary bypass time and chest left open (C statistic 0.87). Each model was tested in a validation cohort (n = 1,008) with equivalent C statistics. CONCLUSIONS: Using a model comprised of basic patient characteristics, we developed a robust prediction tool for patients who will remain in the ICU longer than 7 days after cardiac surgery, at the time of postoperative ICU admission. This model may assist in patient counseling, case scheduling, and capacity management. Further examination in external settings is needed to establish generalizability.

Epidemiology of Noninvasive Ventilation in Pediatric Cardiac ICUs.

OBJECTIVE: To describe the epidemiology of noninvasive ventilation therapy for patients admitted to pediatric cardiac ICUs and to assess practice variation across hospitals. DESIGN: Retrospective cohort study using prospectively collected clinical registry data. SETTING: Pediatric Cardiac Critical Care Consortium clinical registry. PATIENTS: Patients admitted to cardiac ICUs at PC4 hospitals. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We analyzed all cardiac ICU encounters that included any respiratory support from October 2013 to December 2015. Noninvasive ventilation therapy included high flow nasal cannula and positive airway pressure support. We compared patient and, when relevant, perioperative characteristics of those receiving noninvasive ventilation to all others. Subgroup analysis was performed on neonates and infants undergoing major cardiovascular surgery. To examine duration of respiratory support, we created a casemix-adjustment model and calculated adjusted mean durations of total respiratory support (mechanical ventilation + noninvasive ventilation), mechanical ventilation, and noninvasive ventilation. We compared adjusted duration of support across hospitals. The cohort included 8,940 encounters from 15 hospitals: 3,950 (44%) received noninvasive ventilation and 72% were neonates and infants. Medical encounters were more likely to include noninvasive ventilation than surgical. In surgical neonates and infants, 2,032 (55%) received postoperative noninvasive ventilation. Neonates, extracardiac anomalies, single ventricle, procedure complexity, preoperative respiratory support, mechanical ventilation duration, and postoperative disease severity were associated with noninvasive ventilation therapy (p < 0.001 for all). Across hospitals, noninvasive ventilation use ranged from 32% to 65%, and adjusted mean noninvasive ventilation duration ranged from 1 to 4 days (3-d observed mean). Duration of total adjusted respiratory support was more strongly correlated with duration of mechanical ventilation compared with noninvasive ventilation (Pearson r = 0.93 vs 0.71, respectively). CONCLUSIONS: Noninvasive ventilation use is common in cardiac ICUs, especially in patients admitted for medical conditions, infants, and those undergoing high complexity surgery. We observed wide variation in noninvasive ventilation use across hospitals, though the primary driver of total respiratory support time seems to be duration of mechanical ventilation.

Cardiothoracic Critical Care.

High-value CCC is rapidly evolving to meet the demands of increased patient acuity and to incorporate advances in technology. The high-performing CCC system and culture should aim to learn quickly and continuously improve. CCC demands a proactive, interactive, precise, an expert team, and continuity.

Targeted interventions improve shared agreement of daily goals in the pediatric intensive care unit.

OBJECTIVE: To improve communication during daily rounds using sequential interventions. DESIGN: Prospective cohort study. SETTING: Multidisciplinary pediatric intensive care unit in a university hospital. SUBJECTS: The multidisciplinary rounding team in the pediatric intensive care unit, including attending physicians, physician trainees, and nurses. INTERVENTIONS: Daily rounds on 736 patients were observed over a 9-month period. Sequential interventions were timed 8-12 wks apart: 1) implementing a new resident daily progress note format; 2) creating a performance improvement "dashboard"; and 3) documenting patients' daily goals on bedside whiteboards. MEASUREMENTS AND MAIN RESULTS: After all interventions, team agreement with the attending physician's stated daily goals increased from 56.9% to 82.7% (p < .0001). Mean agreement increased for each provider category: 65.2% to 88.8% for fellows (p < .0001), 55.0% to 83.8% for residents (p < .0001), and 54.1% to 77.4% for nurses (p < .0001). In addition, significant improvements were noted in provider behaviors after interventions. Barriers to communication (bedside nurse multitasking during rounds, interruptions during patient presentations, and group disassociation) were reduced, and the use of communication facilitators (review of the prior day's goals, inclusion of bedside nurse input, and order read-back) increased. The percentage of providers reporting being "very satisfied" or "satisfied" with rounds increased from 42.6% to 78.3% (p < .0001). CONCLUSIONS: Shared agreement of patients' daily goals among key healthcare providers can be increased through process-oriented interventions. Improved agreement will potentially lead to improved quality of patient care and reduced medical errors.

Adaptation of a postoperative handoff communication process for children with heart disease: a quantitative study.

Handoff communication is a point of vulnerability when valuable patient information can be inaccurate or omitted. An institutional protocol was implemented in 2005 to improve the handoff from the operating room to the intensive care unit after pediatric cardiac surgery. A cross-sectional study of the present process was performed to understand how users adapt a communication intervention over time. Twenty-nine handoff events were observed. Individuals required for the handoff were present at 97% of the events. Content items averaged a 53% reporting rate. Some clinical information not specified in the protocol demonstrated a higher reporting rate, such as echocardiogram results (68%) and vascular access (79%). A mean of 2.3 environmental distractions per minute of communication were noted. Participant-directed adjustments in content reporting suggest that a facilitator in process improvement is user-centered innovation. Future handoff communication interventions should reduce nonessential distractions and incorporate a discussion of the anticipated patient course.

Determining pediatric intensive care unit quality indicators for measuring pediatric intensive care unit safety.

INTRODUCTION: The measurement of quality and patient safety continues to gain increasing importance, as these measures are used for both healthcare improvement and accountability. Pediatric care, particularly that provided in pediatric intensive care units, is sufficiently different from adult care that specific metrics are required. BODY: Pediatric critical care requires specific measures for both quality and safety. Factors that may affect measures are identified, including data sources, risk adjustment, intended use, reliability, validity, and the usability of measures. The 18-month process to develop seven pediatric critical care measures proposed for national use is described. Specific patient safety metrics that can be applied to pediatric intensive care units include error-, injury-, and risk-based approaches. CONCLUSION: Measurement of pediatric critical care quality and safety will likely continue to evolve. Opportunities exist for intensivists to contribute and lead in the development and refinement of measures.