Mixed-methods process evaluation of a respiratory-culture diagnostic stewardship intervention.

2023

1-9

01/2023

1559-6834

OBJECTIVE: To conduct a process evaluation of a respiratory culture diagnostic stewardship intervention.

DESIGN: Mixed-methods study.

SETTING: Tertiary-care pediatric intensive care unit (PICU).

PARTICIPANTS: Critical care, infectious diseases, and pulmonary attending physicians and fellows; PICU nurse practitioners and hospitalist physicians; pediatric residents; and PICU nurses and respiratory therapists.

METHODS: This mixed-methods study was conducted concurrently with a diagnostic stewardship intervention to reduce the inappropriate collection of respiratory cultures in mechanically ventilated children. We quantified baseline respiratory culture utilization and indications for ordering using quantitative methods. Semistructured interviews informed by these data and the Consolidated Framework for Implementation Research (CFIR) were then performed, recorded, transcribed, and coded to identify salient themes. Finally, themes identified in these interviews were used to create a cross-sectional survey.

RESULTS: The number of cultures collected per day of service varied between attending physicians (range, 2.2-27 cultures per 100 days). In total, 14 interviews were performed, and 87 clinicians completed the survey (response rate, 47%) and 77 nurses or respiratory therapists completed the survey (response rate, 17%). Clinicians varied in their stated practices regarding culture ordering, and these differences both clustered by specialty and were associated with perceived utility of the respiratory culture. Furthermore, group "default" practices, fear, and hierarchy were drivers of culture orders. Barriers to standardization included fear of a missed diagnosis and tension between practice standardization and individual decision making.

CONCLUSIONS: We identified significant variation in utilization and perceptions of respiratory cultures as well as several key barriers to implementation of this diagnostic test stewardship intervention.

10.1017/ice.2022.299

Infect Control Hosp Epidemiol

36594433

Pediatric In-Hospital CPR Quality at Night and on Weekends.

2019

2019 Nov 14

1873-1570

<p><strong>INTRODUCTION: </strong>Survival after in-hospital cardiac arrest (IHCA) has been reported to be worse for arrests at night or during weekends.This study aimed to determine whether measured cardiopulmonary resuscitation (CPR) quality metrics might explain this difference in outcomes.</p>

<p><strong>METHODS: </strong>IHCA data was collected by the Pediatric Resuscitation Quality (pediRES-Q) collaborative for patients &lt;18 years. Metrics of CPR quality [chest compression rate, depth and fraction] were measured using monitordefibrillator pads, and events were compared by time of day and day of week.</p>

<p><strong>RESULTS: </strong>We evaluated 6915 sixty-second epochs of chest compression (CC) data from 239 subjects between October 2015 and March 2019, across 18 hospitals. There was no significant difference in CPR quality metrics during day (07:00-22:59) versus night (23:00-06:59), or weekdays (Monday 07:00 to Friday 22:59) versus weekends (Friday 23:00 to Monday 06:59).There was also no difference in rate of return of circulation. However, survival to hospital discharge was higher for arrests that occurred during the day (39.1%) vs. nights (22.4%, p = 0.015), as well as on weekdays (39.9%) vs. weekends (19.1%, p = 0.003).</p>

<p><strong>CONCLUSIONS: </strong>For pediatric IHCA where CC metrics were obtained, there was no significant difference in CPR quality metrics or rate of return of circulation by time of day or day of week. There was higher survival to hospital discharge when arrests occurred during the day (vs. nights), or on weekdays (vs. weekends), and this difference was not related to disparities in CC quality.</p>

10.1016/j.resuscitation.2019.10.039

Resuscitation

31734222

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

A pragmatic checklist to identify pediatric ICU patients at risk for cardiac arrest or code bell activation.

2016

33-7

2016 Feb

1873-1570

<p><strong>BACKGROUND: </strong>In-hospital cardiac arrest is a rare event associated with significant morbidity and mortality. The ability to identify the ICU patients at risk for cardiac arrest could allow the clinical team to prepare staff and equipment in anticipation.</p>

<p><strong>METHODS: </strong>This pilot study was completed at a large tertiary care pediatric intensive care unit to determine the feasibility of a simple checklist of clinical variables to predict deterioration. The daily checklist assessed patient risk for critical deterioration defined as cardiac arrest or code bell activation within 24h of the checklist screen. The Phase I checklist was developed by expert consensus and evaluated to determine standard diagnostic test performance. A modified Phase II checklist was developed to prospectively test the feasibility and bedside provider "number needed to train".</p>

<p><strong>RESULTS: </strong>For identifying patients requiring code bell activation, both checklists demonstrated a sensitivity of 100% with specificity of 76.0% during Phase I and 97.7% during Phase II. The positive likelihood ratio improved from 4.2 to 43.7. For identifying patients that had a cardiac arrest within 24h, the Phase I and II checklists demonstrated a sensitivity of 100% with specificity again improving from 75.7% to 97.6%. There was an improved positive likelihood ratio from 4.1 in Phase I to 41.9 in Phase II, with improvement of "number needed to train" from 149 to 7.4 providers.</p>

<p><strong>CONCLUSIONS: </strong>A novel high-risk clinical indicators checklist is feasible and provides timely and accurate identification of the ICU patients at risk for cardiac arrest or code bell activation.</p>

10.1016/j.resuscitation.2015.11.017

Resuscitation

26703460