The Utility of Paired Upper and Lower COVID-19 Sampling in Patients with Artificial Airways.

2021

1-8

2021 May 10

1559-6834

<p>Early in the COVID-19 pandemic, CDC recommended collection of a lower respiratory tract (LRT) specimen for SARS-CoV-2 testing in addition to the routinely recommended upper respiratory tract (URT) testing in mechanically ventilated patients. Significant operational challenges were noted at our institution using this approach. In this report, we describe our experience with routine collection of paired URT and LRT sample testing. Our results revealed a high concordance between the two sources, and that all children tested for SARS-CoV-2 were appropriately diagnosed with URT testing alone. There was no added benefit to LRT testing. Based on these findings, our institutional approach was therefore adjusted to sample the URT alone for most patients, with LRT sampling reserved for patients with ongoing clinical suspicion for SARS-CoV-2 after a negative URT test.</p>

10.1017/ice.2021.222

Infect Control Hosp Epidemiol

33966664

Development and Implementation of a Bedside Peripherally Inserted Central Catheter Service in a PICU.

2019

71-78

2019 01

1529-7535

<p><strong>OBJECTIVES: </strong>To create a bedside peripherally inserted central catheter service to increase placement of bedside peripherally inserted central catheter in PICU patients.</p>

<p><strong>DESIGN: </strong>Two-phase observational, pre-post design.</p>

<p><strong>SETTING: </strong>Single-center quaternary noncardiac PICU.</p>

<p><strong>PATIENTS: </strong>All patients admitted to the PICU.</p>

<p><strong>INTERVENTIONS: </strong>From June 1, 2015, to May 31, 2017, a bedside peripherally inserted central catheter service team was created (phase I) and expanded (phase II) as part of a quality improvement initiative. A multidisciplinary team developed a PICU peripherally inserted central catheter evaluation tool to identify amenable patients and to suggest location and provider for procedure performance. Outcome, process, and balancing metrics were evaluated.</p>

<p><strong>MEASUREMENTS AND MAIN RESULTS: </strong>Bedside peripherally inserted central catheter service placed 130 of 493 peripherally inserted central catheter (26%) resulting in 2,447 hospital central catheter days. A shift in bedside peripherally inserted central catheter centerline proportion occurred during both phases. Median time from order to catheter placement was reduced for peripherally inserted central catheters placed by bedside peripherally inserted central catheter service compared with placement in interventional radiology (6 hr [interquartile range, 2-23 hr] vs 34 hr [interquartile range, 19-61 hr]; p &lt; 0.001). Successful access was achieved by bedside peripherally inserted central catheter service providers in 96% of patients with central tip position in 97%. Bedside peripherally inserted central catheter service central line-associated bloodstream infection and venous thromboembolism rates were similar to rates for peripherally inserted central catheters placed in interventional radiology (all central line-associated bloodstream infection, 1.23 vs 2.18; p = 0.37 and venous thromboembolism, 1.63 vs 1.57; p = 0.91). Peripherally inserted central catheters in PICU patients had reduced in-hospital venous thromboembolism rate compared with PICU temporary catheter in PICU rate (1.59 vs 5.36; p &lt; 0.001).</p>

<p><strong>CONCLUSIONS: </strong>Bedside peripherally inserted central catheter service implementation increased bedside peripherally inserted central catheter placement and employed a patient-centered and timely process. Balancing metrics including central line-associated bloodstream infection and venous thromboembolism rates were not significantly different between peripherally inserted central catheters placed by bedside peripherally inserted central catheter service and those placed in interventional radiology.</p>

10.1097/PCC.0000000000001739

Pediatr Crit Care Med

30234675

Design and Implementation of a Pediatric ICU Acuity Scoring Tool as Clinical Decision Support.

2018

576-587

2018 07

1869-0327

<p><strong>BACKGROUND AND OBJECTIVE: </strong>Pediatric in-hospital cardiac arrest most commonly occurs in the pediatric intensive care unit (PICU) and is frequently preceded by early warning signs of clinical deterioration. In this study, we describe the implementation and evaluation of criteria to identify high-risk patients from a paper-based checklist into a clinical decision support (CDS) tool in the electronic health record (EHR).</p>

<p><strong>MATERIALS AND METHODS: </strong>The validated paper-based tool was first adapted by PICU clinicians and clinical informaticians and then integrated into clinical workflow following best practices for CDS design. A vendor-based rule engine was utilized. Littenberg's assessment framework helped guide the overall evaluation. Preliminary testing took place in EHR development environments with more rigorous evaluation, testing, and feedback completed in the live production environment. To verify data quality of the CDS rule engine, a retrospective Structured Query Language (SQL) data query was also created. As a process metric, preparedness was measured in pre- and postimplementation surveys.</p>

<p><strong>RESULTS: </strong>The system was deployed, evaluating approximately 340 unique patients monthly across 4 clinical teams. The verification against retrospective SQL of 15-minute intervals over a 30-day period revealed no missing triggered intervals and demonstrated 99.3% concordance of positive triggers. Preparedness showed improvements across multiple domains to our a priori goal of 90%.</p>

<p><strong>CONCLUSION: </strong>We describe the successful adaptation and implementation of a real-time CDS tool to identify PICU patients at risk of deterioration. Prospective multicenter evaluation of the tool's effectiveness on clinical outcomes is necessary before broader implementation can be recommended.</p>

10.1055/s-0038-1667122

Appl Clin Inform

30068013

Performance of a Clinical Decision Support Tool to Identify PICU Patients at High Risk for Clinical Deterioration.

2019

2019 Oct 02

1529-7535

<p><strong>OBJECTIVES: </strong>To evaluate the translation of a paper high-risk checklist for PICU patients at risk of clinical deterioration to an automated clinical decision support tool.</p>

<p><strong>DESIGN: </strong>Retrospective, observational cohort study of an automated clinical decision support tool, the PICU Warning Tool, adapted from a paper checklist to predict clinical deterioration events in PICU patients within 24 hours.</p>

<p><strong>SETTING: </strong>Two quaternary care medical-surgical PICUs-The Children's Hospital of Philadelphia and Cincinnati Children's Hospital Medical Center.</p>

<p><strong>PATIENTS: </strong>The study included all patients admitted from July 1, 2014, to June 30, 2015, the year prior to the initiation of any focused situational awareness work at either institution.</p>

<p><strong>INTERVENTIONS: </strong>We replicated the predictions of the real-time PICU Warning Tool by retrospectively querying the institutional data warehouse to identify all patients that would have flagged as high-risk by the PICU Warning Tool for their index deterioration.</p>

<p><strong>MEASUREMENTS AND MAIN RESULTS: </strong>The primary exposure of interest was determination of high-risk status during PICU admission via the PICU Warning Tool. The primary outcome of interest was clinical deterioration event within 24 hours of a positive screen. The date and time of the deterioration event was used as the index time point. We evaluated the sensitivity, specificity, positive predictive value, and negative predictive value of the performance of the PICU Warning Tool. There were 6,233 patients evaluated with 233 clinical deterioration events experienced by 154 individual patients. The positive predictive value of the PICU Warning Tool was 7.1% with a number needed to screen of 14 patients for each index clinical deterioration event. The most predictive of the individual criteria were elevated lactic acidosis, high mean airway pressure, and profound acidosis.</p>

<p><strong>CONCLUSIONS: </strong>Performance of a clinical decision support translation of a paper-based tool showed inferior test characteristics. Improved feasibility of identification of high-risk patients using automated tools must be balanced with performance.</p>

10.1097/PCC.0000000000002106

Pediatr Crit Care Med

31577691