Implementation of a national system for best practice delivery of paediatric infusions.

BACKGROUND: Standard concentration infusions and 'smart-pumps' are recognised as best practice in the paediatric setting. Implementation rates in European hospitals remain low. Children's Health Ireland (CHI) developed a paediatric 'smart-pump' drug library using standardised concentrations. At time of development, other Irish hospitals continued to use traditional pumps and weight-based paediatric infusions. AIM: To expand best paediatric infusion practices by nationalising use of the CHI drug library. SETTING: Tertiary paediatric, maternity and general acute hospitals, and associated transport services in Ireland. DEVELOPMENT: The CHI drug library was first developed for paediatric intensive care and then adapted over a 10-year period for use in emergency departments, general paediatric wards, neonatal units, adult intensive care and transport services. The original library (42 drug lines, 1 'care-unit') was substantially expanded (223 drug lines, 6 'care-units'). A neonatal sub-library was created. IMPLEMENTATION: Executive support, dedicated resources and governance structures were secured. Implementation and training packages were developed. Implementation has occurred across CHI, in paediatric and neonatal transport services, 58% (n = 11) of neonatal units, and 23% (n = 6) of paediatric sites. EVALUATION: A before and after study demonstrated significant reductions in infusion prescribing errors (29.0% versus 8.4%, p < 0.001). Direct observation of infusions (n = 1023) found high compliance rates (98.9%) and low programming errors (1.6%). 100% of nurses (n = 132) surveyed 9 months after general ward implementation considered the drug library had enhanced patient safety. CONCLUSION: Strategic planning and collaboration can standardise infusion practices. The CHI drug library has been approved as a National Standard of Care, with implementation continuing.

A Systematic Review and Pooled Prevalence of Delirium in Critically Ill Children.

OBJECTIVES: Pediatric delirium is a neuropsychiatric disorder with disrupted cerebral functioning due to underlying disease and/or critical care treatment. Pediatric delirium can be classified as hypoactive, hyperactive, and mixed. This systematic review was conducted to estimate the pooled prevalence of pediatric delirium using validated assessment tools in children (Cornell Assessment of Pediatric Delirium, Pediatric Confusion Assessment Method for the ICU, PreSchool Confusion Assessment Method for the ICU, Pediatric Confusion Assessment Method for the ICU Severity Scale, and Sophia Observation Withdrawal Symptoms Pediatric Delirium scale), identify modifiable and nonmodifiable risk factors, and explore the association of pediatric delirium with clinical outcomes. DATA SOURCES: A systematic search of PubMed, EMBASE, and CINAHL databases was undertaken for full articles pertaining to pediatric delirium prevalence. STUDY SELECTION: No language or date barriers were set. Studies were included where the following eligibility criteria were met: study design aimed to estimate pediatric delirium prevalence arising from treatment in the intensive care setting, using a validated tool. Only randomized controlled trials, cross-sectional studies, or cohort studies allowing an estimate of the prevalence of pediatric delirium were included. DATA EXTRACTION: Data were extracted by the primary researcher (D.S.) and accuracy checked by coauthors. DATA SYNTHESIS: A narrative synthesis and pooled prevalence meta-analysis were undertaken. CONCLUSIONS: Pediatric delirium, as determined by the Cornell Assessment of Pediatric Delirium score, is estimated to occur in 34% of critical care admissions. Eight of 11 studies reporting on subtype identified hypoactive delirium as most prevalent (46-81%) with each of the three remaining reporting either hyperactive (44%), mixed (57%), or equal percentages of hypoactive and mixed delirium (43%) as most prevalent. The development of pediatric delirium is associated with cumulative doses of benzodiazepines, opioids, the number of sedative classes used, deep sedation, and cardiothoracic surgery. Increased time mechanically ventilated, length of stay, mortality, healthcare costs, and associations with decreased quality of life after discharge were also found. Multi-institutional and longitudinal studies are required to better determine the natural history, true prevalence, long-term outcomes, management strategies, and financial implications of pediatric delirium.

Sedation With Midazolam After Cardiac Surgery in Children With and Without Down Syndrome: A Pharmacokinetic-Pharmacodynamic Study.

OBJECTIVES: To compare the pharmacokinetics and pharmacodynamics of IV midazolam after cardiac surgery between children with and without Down syndrome. DESIGN: Prospective, single-center observational trial. SETTING: PICU in a university-affiliated pediatric teaching hospital. PATIENTS: Twenty-one children with Down syndrome and 17 without, 3-36 months, scheduled for cardiac surgery with cardiopulmonary bypass. INTERVENTIONS: Postoperatively, nurses regularly assessed the children's pain and discomfort with the validated COMFORT-Behavioral scale and Numeric Rating Scale for pain. A loading dose of morphine (100 µg/kg) was administered after coming off bypass; thereafter, morphine infusion was commenced at 40 µg/kg/hr. Midazolam was started if COMFORT-Behavioral scale score of greater than 16 and Numeric Rating Scale score of less than 4 (suggestive of undersedation). Plasma midazolam and metabolite concentrations were measured for population pharmacokinetic- and pharmacodynamic analysis using nonlinear mixed effects modeling (NONMEM) (Version VI; GloboMax LLC, Hanover, MD) software. MEASUREMENTS AND MAIN RESULTS: Twenty-six children (72%) required midazolam postoperatively (15 with Down syndrome and 11 without; p = 1.00). Neither the cumulative midazolam dose (p = 0.61) nor the time elapsed before additional sedation was initiated (p = 0.71), statistically significantly differed between children with and without Down syndrome. Population pharmacokinetic and pharmacodynamics analysis revealed no statistically significant differences between the children with and without Down syndrome. Bodyweight was a significant covariate for the clearance of 1-OH-midazolam to 1-OH-glucuronide (p = 0.003). Pharmacodynamic analysis revealed a marginal effect of the midazolam concentration on the COMFORT-Behavioral score. CONCLUSIONS: The majority of children with and without Down syndrome required additional sedation after cardiac surgery. This pharmacokinetic and pharmacodynamic analysis does not provide evidence for different dosing of midazolam in children with Down syndrome after cardiac surgery.

Direct Observational Study of Interfaced Smart-Pumps in Pediatric Intensive Care.

BACKGROUND: Processes for delivery of high-risk infusions in pediatric intensive care units (PICUs) are complex. Standard concentration infusions (SCIs), smart-pumps, and electronic prescribing are recommended medication error reduction strategies. Implementation rates in Europe lag behind those in the United States. Since 2012, the PICU of an Irish tertiary pediatric hospital has been using a smart-pump SCI library, interfaced with electronic infusion orders (Philips ICCA). The incidence of infusion errors is unknown. OBJECTIVES: To determine the frequency, severity, and distribution of smart-pump infusion errors in PICUs. METHODS: Programmed infusions were directly observed at the bedside. Parameters were compared against medication orders and autodocumented infusion data. Identified deviations were categorized as medication errors or discrepancies. Error rates (%) were calculated as infusions with errors and errors per opportunities for error (OEs). Predefined definitions, multidisciplinary consensus and grading processes were employed. RESULTS: A total of 1,023 infusions for 175 patients were directly observed over 27 days between February and September 2017. The drug library accommodated 96.5% of infusions. Compliance with the drug library was 98.9%. A total of 133 infusions had ≥1 error (13.0%); a further 58 (5.7%) had ≥1 discrepancy. From a total of 4,997 OEs, 153 errors (3.1%) and 107 discrepancies (2.1%) were observed. Undocumented bolus doses were most commonly identified (n = 81); this was the only deviation in 36.1% (n = 69) of infusions. Programming errors were rare (0.32% OE). Errors were minor, with just one requiring minimal intervention to prevent harm. CONCLUSION: The error rates identified are low compared with similar studies, highlighting the benefits of smart-pumps and autodocumented infusion data in PICUs. A range of quality improvement opportunities has been identified.

Exploring the Relationship Between Morphine Concentration and Oversedation in Children After Cardiac Surgery.

Titrating analgesic and sedative drugs in pediatric intensive care remains a challenge for caregivers due to the lack of pharmacodynamic knowledge in this population. The aim of the current study is to explore the concentration-effect relationship for morphine-associated oversedation after cardiac surgery in children aged 3 months to 3 years. Data on morphine dosing, as well as morphine plasma concentrations, were available from a previous study on the pharmacokinetics of morphine after cardiac surgery in children. Oversedation was defined as scores below 11 on the validated COMFORT-behavioral scale. Population pharmacokinetic-pharmacodynamic modeling was performed in NONMEM 7.3. The probability of oversedation as a function of morphine concentration was best described using a step function in which the EC50 was 46.3 ng/mL. At morphine concentrations below the EC50 , the probability of oversedation was 2.9% (0.4& to 18%), whereas above the EC50 percentages were 13% (1.9% to 52%) (median value [95% prediction interval from interindividual variability]). Additionally, the risk of oversedation was found to be increased during the first hours after surgery (P < .001) and was significantly lower during mechanical ventilation (P < .005). We conclude that morphine concentrations above approximately 45 ng/mL may increase the probability of oversedation in children after cardiac surgery. The clinician must evaluate, on a case-by-case basis, whether the analgesic benefits arising from dosing regimen associated with such concentrations outweigh the risks.

The Impact of Technology on Prescribing Errors in Pediatric Intensive Care: A Before and After Study.

BACKGROUND: Increased use of health information technology (HIT) has been advocated as a medication error reduction strategy. Evidence of its benefits in the pediatric setting remains limited. In 2012, electronic prescribing (ICCA, Philips, United Kingdom) and standard concentration infusions (SCIs)-facilitated by smart-pump technology-were introduced into the pediatric intensive care unit (PICU) of an Irish tertiary-care pediatric hospital. OBJECTIVE: The aim of this study is to assess the impact of the new technology on the rate and severity of PICU prescribing errors and identify technology-generated errors. METHODS: A retrospective, before and after study design, was employed. Medication orders were reviewed over 24 weeks distributed across four time periods: preimplementation (Epoch 1); postimplementation of SCIs (Epoch 2); immediate postimplementation of electronic prescribing (Epoch 3); and 1 year postimplementation (Epoch 4). Only orders reviewed by a clinical pharmacist were included. Prespecified definitions, multidisciplinary consensus and validated grading methods were utilized. RESULTS: A total of 3,356 medication orders for 288 patients were included. Overall error rates were similar in Epoch 1 and 4 (10.2 vs. 9.8%; p = 0.8), but error types differed (p < 0.001). Incomplete and wrong unit errors were eradicated; duplicate orders increased. Dosing errors remained most common. A total of 27% of postimplementation errors were technology-generated. Implementation of SCIs alone was associated with significant reductions in infusion-related prescribing errors (29.0% [Epoch 1] to 14.6% [Epoch 2]; p < 0.001). Further reductions (8.4% [Epoch 4]) were identified after implementation of electronically generated infusion orders. Non-infusion error severity was unchanged (p = 0.13); fewer infusion errors reached the patient (p < 0.01). No errors causing harm were identified. CONCLUSION: The limitations of electronic prescribing in reducing overall prescribing errors in PICU have been demonstrated. The replacement of weight-based infusions with SCIs was associated with significant reductions in infusion prescribing errors. Technology-generated errors were common, highlighting the need for on-going research on HIT implementation in pediatric settings.

Optimizing clonidine dosage for sedation in mechanically ventilated children: A pharmacokinetic simulation study.

BACKGROUND: Clonidine is in widespread off-label use as a sedative in mechanically ventilated children, despite limited evidence of efficacy. A variety of dosage regimens have been utilized in clinical practice and in research studies. Within these studies, clonidine has inconsistently shown useful sedation properties. One of the reasons attributed to the inconsistent signs of efficacy is suboptimal clonidine dosing. AIMS: This study aims to propose a target plasma concentration and simulate clonidine pharmacokinetics (PK) in a cohort of mechanically ventilated children to evaluate the adequacy of clonidine dosage regimens used in clinical practice and research studies. METHODS: A literature search was undertaken to identify a clonidine pharmaockinetic-pharmacodynamics (PKPD) model, from which a target concentration for sedation was defined. Using a previously published PK model, the projected plasma concentrations of 692 mechanically ventilated children (demographics taken from a recent study) were generated. Doses from recently published clinical studies were investigated. Adequacy of each regimen to attain therapeutic clonidine plasma concentrations was assessed. RESULTS: A target plasma concentration of above 2 µg/L was proposed. Nine dosage regimens (four intravenous boluses, four intravenous infusions, and one nasogastric route boluses) were evaluated ranging from 1 µg/kg eight hourly intravenous boluses to a regimen up to 3 µg/kg/hr continuous intravenous infusion. Regimens with a loading dose of 2 µg/kg followed by variable continuous infusion of up to 2 µg/kg/hr titrated according to sedation score appear most suitable. Doses should be halved in neonates. CONCLUSION: The variety of dosage regimens in the previous studies of clonidine along with difficulties in the conduct of interventional studies may have contributed to the lack of efficacy data to support its use. Simulations of clonidine plasma concentrations based on known population pharmacokinetic parameters suggest a loading dose followed by higher than current practice maintenance dose infusion is required to achieve adequate steady-state concentrations early in treatment. Further PKPD studies will aid in the determination of the optimal clonidine dosage regimen.

The Effectiveness of α2 Agonists As Sedatives in Pediatric Critical Care: A Propensity Score-Matched Cohort Study.

OBJECTIVES: There is limited evidence supporting the widespread use of α2 agonists (clonidine and dexmedetomidine) in pediatric critical care sedation. This study sought to test the association between the use of α2 agonists and enhanced sedation. DESIGN: A retrospective observational cohort study was conducted. Noninferiority of time adequately sedated (COMFORT Behavior Score 11-16) while mechanically ventilated was assessed. Secondarily, dosing of opioids and benzodiazepines was examined. SETTING: Two tertiary PICUs. PATIENTS: Children were classified into an exposed group, who received an α2 agonist as part of their sedation regimen, and an unexposed group. Groups were matched using propensity score analysis. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: One-thousand eighty-five patients were included. The exposed group were adequately sedated 74% (95% CI, 72-75%) of the study time compared with the unexposed group at 70% (95% CI, 67-72%) giving a ratio of 1.06 (95% CI, 1.02-1.10) and a noninferior time adequately sedated. A decrease in time oversedated was observed with 8.1% (95% CI, 4.3-11.9%) less time classified as oversedated in the exposed group. Reduction in morphine use of 0.25 µg/kg/hr (95% CI, -0.68 to 1.18 µg/kg/hr) was not statistically significant. Midazolam use did not decrease and was statistically higher. CONCLUSIONS: Use of α2 agonists was associated with similar time adequately sedated as a matched unexposed group although no reduction in morphine or benzodiazepine coadministration was observed. There was a shift toward lighter sedation with α2 agonist use.

Defining electronic-prescribing and infusion-related medication errors in paediatric intensive care - a Delphi study.

BACKGROUND: The use of health information technology (HIT) to improve patient safety is widely advocated by governmental and safety agencies. Electronic-prescribing and smart-pump technology are examples of HIT medication error reduction strategies. The introduction of new errors on HIT implementation is, however, also recognised. To determine the impact of HIT interventions, clear medication error definitions are required. This study aims to achieve consensus on defining as medication errors a range of either technology-generated, or previously unaddressed infusion-related scenarios, common in the paediatric intensive care setting. METHODS: This study was conducted in a 23-bed paediatric intensive care unit (PICU) of an Irish tertiary paediatric hospital. A modified Delphi technique was employed: previously undefined medication-incidents were identified by retrospective review of voluntary incident reports and clinical pharmacist interventions; a multidisciplinary expert panel scored each incident using a 9-point Likert scale over a number of iterative rounds; levels of agreement were assessed to produce a list of medication errors. Differences in scoring between healthcare professionals were assessed. RESULTS: Seventeen potential errors or 'scenarios' requiring consensus were identified, 13 of which related to technology recently implemented into the PICU. These were presented to a panel of 37 participants, comprising of doctors, nurses and pharmacists. Consensus was reached to define as errors all reported smart-pump scenarios (n = 6) and those pertaining to the pre-electronic process of prescribing weight-based paediatric infusions (n = 4). Of 7 electronic-prescribing scenarios, 4 were defined as errors, 2 were deemed not to be and consensus could not be achieved for the last. Some differences in scoring between healthcare professionals were found, but were only significant (p < 0.05) for two and three scenarios in consensus rounds 1 and 2 respectively. CONCLUSION: The list of medication errors produced using the Delphi technique highlights the diversity of previously undefined medication errors in PICU. The increased complexity of electronic-prescribing processes is evident from the difficulty in achieving consensus on those scenarios. Reducing ambiguity in defining medication errors should assist future research on the impact of HIT medication safety initiatives in critical care. The increasing use of HIT and associated new errors will necessitate further similar studies.

Pharmacodynamics and Pharmacokinetics of Morphine After Cardiac Surgery in Children With and Without Down Syndrome.

OBJECTIVE: To compare the pharmacodynamics and pharmacokinetics of IV morphine after cardiac surgery in two groups of children-those with and without Down syndrome. DESIGN: Prospective, single-center observational trial. SETTING: PICU in a university-affiliated pediatric teaching hospital. PATIENTS: Twenty-one children with Down syndrome and 17 without, 3-36 months old, scheduled for cardiac surgery with cardiopulmonary bypass. INTERVENTIONS: A loading dose of morphine (100 µg/kg) was administered after coming off bypass; thereafter, morphine infusion was commenced at 40 µg/kg/hr. During intensive care, nurses regularly assessed pain and discomfort with validated observational instruments (COMFORT-Behavior scale and Numeric Rating Scale-for pain). These scores guided analgesic and sedative treatment. Plasma samples were obtained for pharmacokinetic analysis. MEASUREMENTS AND MAIN RESULTS: Median COMFORT-Behavior and Numeric Rating Scale scores were not statistically significantly different between the two groups. The median morphine infusion rate during the first 24 hours after surgery was 31.3 µg/kg/hr (interquartile range, 23.4-36.4) in the Down syndrome group versus 31.7 µg/kg/hr (interquartile range, 25.1-36.1) in the control group (p = 1.00). Population pharmacokinetic analysis revealed no statistically significant differences in any of the pharmacokinetic variables of morphine between the children with and without Down syndrome. CONCLUSIONS: This prospective trial showed that there are no differences in pharmacokinetics or pharmacodynamics between children with and without Down syndrome if pain and distress management is titrated to effect based on outcomes of validated assessment instruments. We have no evidence to adjust morphine dosing after cardiac surgery in children with Down syndrome.