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.

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.

Efficacy of α2-Agonists for Sedation in Pediatric Critical Care: A Systematic Review.

OBJECTIVE: Children in PICUs normally require analgesics and sedatives to maintain comfort, safety, and cooperation with interventions. α2-agonists (clonidine and dexmedetomidine) have been described as adjunctive (or alternative) sedative agents alongside opioids and benzodiazepines. This systematic review aimed to determine whether α2-agonists were effective in maintaining patients at a target sedation score over time compared with a comparator group. We also aimed to determine whether concurrent use of α2-agonists provided opioid-sparing effects. DATA SOURCES: A systematic search was performed using the Cochrane Central Register of Controlled Trials, PubMed, EMBASE, CINAHL, and LILACS. STUDY SELECTION: We included randomized controlled trials of children in PICU treated with clonidine or dexmedetomidine for the indication of sedation. DATA EXTRACTION: Two authors independently screened articles for inclusion. DATA SYNTHESIS: Six randomized controlled trials with sufficient data were identified and critically appraised. Three clonidine trials (two vs placebo and one vs midazolam) and three dexmedetomidine trials (two vs fentanyl, one vs midazolam) were included. Due to study heterogeneity it was not possible to pool studies. A narrative synthesis is provided. CONCLUSIONS: Reporting of study results using the outcome "time maintained at target sedation score' for clonidine or dexmedetomidine was poor. Only one trial compared clonidine with midazolam using a sedation score outcome. This study was underpowered to demonstrate equivalence to midazolam as a sedative. The adjunctive use of clonidine demonstrated significant decreases in opioid use in neonates but not in older groups. Clonidine dose was inconsistent between studies. Dexmedetomidine demonstrated an opioid-sparing effect in two small trials. Further studies, including dose-finding studies and studies with sedation score-based outcomes, are needed.

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.

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.

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.