Citations

OBJECTIVES: With increasing complexity of critical care medicine comes an increasing need for multidisciplinary involvement in care. In many institutions, pharmacists are an integral part of this team, but long-term data on the interventions performed by pharmacists and their effects on patient care and outcomes are limited. We aimed to describe the role of pediatric clinical pharmacists in pediatric intensive care unit (PICU) practice. METHODS: We retrospectively reviewed the records of pharmacy interventions in the PICU at the Mayo Clinic in Rochester, Minnesota, from 2003-2013, with a distinct period of increased pharmacist presence in the PICU from 2008 onward. We compared demographic and outcome data on patients who did and who did not have pharmacy interventions during 2 periods (2003–2007 and 2008–2013). RESULTS: We identified 27,773 total interventions by pharmacists during the 11-year period, of which 79.8% were accepted by the clinical team. These interventions were made on 10,963 unique PICU admissions and prevented 5867 order entry errors. Pharmacists' interventions increased year over year, including a significant change in 2008. Patients who required pharmacy involvement were younger, sicker, and had longer intensive care unit, hospital, and ventilator duration. Average central line infections and central line entry rates decreased significantly over the study period. CONCLUSIONS: Increased pharmacist presence in the PICU is associated with increased interventions and prevention of adverse drug events. Pharmacist participation during rounds and order entry substantially improved the care of critically sick children and should be encouraged.

ABSTRACT Background Implementation of checklists has been shown to be effective in improving patient safety. This study aims to evaluate the effectiveness of implementation of a checklist for daily care processes into clinical practice of pediatric intensive care units (PICUs) with limited resources. Methods Prospective before–after study in eight PICUs from China, Congo, Croatia, Fiji, and India after implementation of a daily checklist into the ICU rounds. Results Seven hundred and thirty-five patients from eight centers were enrolled between 2015 and 2017. Baseline stage had 292 patients and post-implementation 443. The ICU length of stay post-implementation decreased significantly [9.4 (4–15.5) vs. 7.3 (3.4–13.4) days, p = 0.01], with a nominal improvement in the hospital length of stay [15.4 (8.4–25) vs. 12.6 (7.5–24.4) days, p = 0.055]. The hospital mortality and ICU mortality between baseline group and post-implementation group did not show a significant difference, 14.4% vs. 11.3%; p = 0.22 for each. There was a variable impact of checklist implementation on adherence to various processes of care recommendations. A decreased exposure in days was noticed for; mechanical ventilation from 42.6% to 33.8%, p < 0.01; central line from 31.3% to 25.3%, p < 0.01; and urinary catheter from 30.6% to 24.4%, p < 0.01. Although there was an increased utilization of antimicrobials (89.9–93.2%, p < 0.01). Conclusions Checklists for the treatment of acute illness and injury in the PICU setting marginally impacted the outcome and processes of care. The intervention led to increasing adherence with guidelines in multiple ICU processes and led to decreased length of stay.

BACKGROUNDDelirium is associated with poor outcomes in adults but is less extensively studied in children.OBJECTIVESTo describe a quality improvement initiative to implement delirium assessment in a pediatric intensive care unit and to identify barriers to delirium screening completion.METHODSA survey identified perceived barriers to delirium assessment. Failure modes and effects analysis characterized factors likely to impede assessment. A randomized case-control study evaluated factors affecting assessment by comparing patients always assessed with patients never assessed.RESULTSDelirium assessment was completed in 57% of opportunities over 1 year, with 2% positive screen results. Education improved screening completion by 20%. Barriers to assessment identified by survey (n = 25) included remembering to complete assessments, documentation outside workflow, and “busy patient.” Factors with high risk prediction numbers were lack of time and paper charting. Patients always assessed had more severe illness (median Pediatric Index of Mortality 2 score, 0.90 vs 0.36; P < .001), more developmental disabilities (moderate to severe pediatric cerebral performance category score, 54% vs 32%; P = .007), and admission during lower pediatric intensive care unit census (median [interquartile range], 10 [9–12] vs 12 [10–13]; P < .001) than did those never assessed (each group, n = 80). Patients receiving mechanical ventilation were less likely to be assessed (41.0% vs 51.2%, P < .001).CONCLUSIONSSuccessful implementation of pediatric delirium screening may be associated with early use of quality improvement tools to identify assessment barriers, comprehensive education, monitoring system with feedback, multidisciplinary team involvement, and incorporation into nursing workflow models.

Objective: No risk prediction model is currently available to measure patient’s probability for readmission to the pediatric intensive care unit (PICU). This retrospective case–control study was designed to assess the applicability of an adult risk prediction score (Stability and Workload Index for Transfer [SWIFT]) and to create a pediatric version (PRediction Of PICU Early Readmissions [PROPER]). Design: Eighty-six unplanned early (<48 hours) PICU readmissions from January 07, 2007, to June 30, 2014, were compared with 170 random controls. Patient- and disease-specific data and PICU workload factors were compared across the 2 groups. Factors statistically significant on multivariate analysis were included in the creation of the risk prediction model. The SWIFT scores were calculated for cases and controls and compared for validation. Results: Readmitted patients were younger, weighed less, and were more likely to be admitted from the emergency department. There were no differences in gender, race, or admission Pediatric Index of Mortality scores. A higher proportion of patients in the readmission group had a Pediatric Cerebral Performance Category in the moderate to severe disability category. Cases and controls did not differ with respect to staff workload at discharge or discharge day of the week; there was a much higher proportion of patients on supplemental oxygen in the readmission group. Only 2 of 5 categories in the SWIFT model were significantly different, and although the median SWIFT score was significantly higher in the readmissions group, the model discriminated poorly between cases and controls (area under the curve: 0.613). A 7-category PROPER score was created based on a multiple logistic regression model. Sensitivity of this model (score ≥12) for the detection of readmission was 81% with a positive predictive value of 0.50. Conclusion: We have created a preliminary model for predicting patients at risk of early readmissions to the PICU from the hospital floor. The SWIFT score is not applicable for predicting the risk for pediatric population.

BACKGROUND AND OBJECTIVES: Ineffective and inefficient patient transfer processes can increase the chance of medical errors. Improvements in such processes are high-priority local institutional and national patient safety goals. At our institution, nonintubated postoperative pediatric patients are first admitted to the postanesthesia care unit before transfer to the PICU. This quality improvement project was designed to improve the patient transfer process from the operating room (OR) to the PICU. METHODS: After direct observation of the baseline process, we introduced a structured, direct OR-PICU transfer process for orthopedic spinal fusion patients. We performed value stream mapping of the process to determine error-prone and inefficient areas. We evaluated primary outcome measures of handoff error reduction and the overall efficiency of patient transfer process time. Staff satisfaction was evaluated as a counterbalance measure. RESULTS: With the introduction of the new direct OR-PICU patient transfer process, the handoff communication error rate improved from 1.9 to 0.3 errors per patient handoff (P = .002). Inefficiency (patient wait time and non–value-creating activity) was reduced from 90 to 32 minutes. Handoff content was improved with fewer information omissions (P &lt; .001). Staff satisfaction significantly improved among nearly all PICU providers. CONCLUSIONS: By using quality improvement methodology to design and implement a new direct OR-PICU transfer process with a structured multidisciplinary verbal handoff, we achieved sustained improvements in patient safety and efficiency. Handoff communication was enhanced, with fewer errors and content omissions. The new process improved efficiency, with high staff satisfaction.

BACKGROUND: Although under-reported and understudied, unplanned extubations carry a significant risk of patient harm and even death. They are an important yardstick of quality control of care of intubated patients in the ICU. A unit-based risk assessment and multidisciplinary approach is required to decrease the incidence of unplanned extubations. METHODS: As part of a quality-improvement initiative of Children's Hospital at Montefiore, all planned and unplanned extubations in a multidisciplinary 20-bed pediatric ICU were evaluated over a 12-month period (January to December 2010). At the end of 6 months, an interim analysis was performed, and high-risk patient groups and patient care factors were identified. These factors were targeted in the second phase of the project. RESULTS: Over this period, there were a total of 267 extubations, of which 231 (87%) were planned extubations and 36 (13%) were unplanned. A patient care policy targeting the risk factors was instituted, along with extensive nursing and other personnel education in the second phase. As a result of this intervention, the unplanned extubation rate in the pediatric ICU decreased from 3.55 to 2.59/100 intubation days. All subjects who had an unplanned extubation during nursing procedures or transport required re-intubation, whereas none of the unplanned extubations during ventilator weaning required re-intubation. CONCLUSIONS: A targeted approach based on unit-specific risk factors is most effective in quality-improvement projects. A specific policy for sedation and weaning can be very helpful in managing intubated patients and preventing unintended harm.