A Pediatric Critical Care Practice Group: Use of Expertise and Evidence-Based Practice in Identifying and Establishing “Best” Practice

Lincoln, Patricia; Manning, Mary-Jeanne; Hamilton, Susan; Labreque, Michelle; Casey, Denise; Kennedy, Heather; Penny, Katherine C; Curley, Martha A. Q.

doi:10.4037/ccn2013740

Cited by 4 publications

(2 citation statements)

References 8 publications

(5 reference statements)

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“…However, the necessary combined, implicit knowledge is often only represented in individual persons and not permanently accessible to less experienced persons. Risks for medical errors are omnipresent due to high dynamics, uncertainties, immediate decision-making needs and large data volumes 1 2…”

Section: Introductionmentioning

confidence: 99%

Prediction models for SIRS, sepsis and associated organ dysfunctions in paediatric intensive care: study protocol for a diagnostic test accuracy study

Böhnke

Rübsamen²,

Mast³

et al. 2022

bmjpo

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IntroductionSystemic inflammatory response syndrome (SIRS), sepsis and associated organ dysfunctions are life-threating conditions occurring at paediatric intensive care units (PICUs). Early recognition and treatment within the first hours of onset are critical. However, time pressure, lack of personnel resources, and the need for complex age-dependent diagnoses impede an accurate and timely diagnosis by PICU physicians. Data-driven prediction models integrated in clinical decision support systems (CDSS) could facilitate early recognition of disease onset.ObjectivesTo estimate the sensitivity and specificity of previously developed prediction models (index tests) for the detection of SIRS, sepsis and associated organ dysfunctions in critically ill children up to 12 hours before reference standard diagnosis is possible.Methods and analysisWe conduct a monocentre, prospective diagnostic test accuracy study. Clinicians in the PICU of the tertiary care centre Hannover Medical School, Germany, continuously screen and recruit patients until the adaptive sample size (originally intended sample size of 500 patients) is enrolled. Eligible are children (0–17 years, all sexes) who stay in the PICU for ≥12 hours and for whom an informed consent is given. All eligible patients are independently assessed for SIRS, sepsis and organ dysfunctions using corresponding predictive and knowledge-based CDSS models. The knowledge-based CDSS models serve as imperfect reference standards. The assessments are used to estimate the sensitivities and specificities of each predictive model using a clustered nonparametric approach (main analysis). Subgroup analyses (‘age groups’, ‘sex’ and ‘age groups by sex’) are predefined.Ethics and disseminationThis study obtained ethics approval from the Hannover Medical School Ethics Committee (No. 10188_BO_SK_2022). Results will be disseminated as peer-reviewed publications, at scientific conferences, and to patients in an appropriate dissemination approach.Trial registration numberThis study was registered with the German Clinical Trial Register (DRKS00029071) on 2022-05-23.Protocol version10188_BO_SK_2022_V.2.0–20220330_4_Studienprotokoll.

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Section: Introductionmentioning

confidence: 99%

Prediction models for SIRS, sepsis and associated organ dysfunctions in paediatric intensive care: study protocol for a diagnostic test accuracy study

Böhnke

Rübsamen²,

Mast³

et al. 2022

bmjpo

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“…This is particularly true for paediatric intensive care units (PICU), in which clinicians work under challenging conditions characterised by a high degree of dynamics, uncertainty and risk, time pressure and a vast amount of data. Altogether, these factors carry risk for medical errors and adverse effects on patient safety 13–15…”

Section: Introductionmentioning

confidence: 99%

CADDIE2—evaluation of a clinical decision-support system for early detection of systemic inflammatory response syndrome in paediatric intensive care: study protocol for a diagnostic study

et al. 2019

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IntroductionSystemic inflammatory response syndrome (SIRS) is one of the most critical indicators determining the clinical outcome of paediatric intensive care patients. Clinical decision support systems (CDSS) can be designed to support clinicians in detection and treatment. However, the use of such systems is highly discussed as they are often associated with accuracy problems and ‘alert fatigue’. We designed a CDSS for detection of paediatric SIRS and hypothesise that a high diagnostic accuracy together with an adequate alerting will accelerate the use. Our study will (1) determine the diagnostic accuracy of the CDSS compared with gold standard decisions created by two blinded, experienced paediatricians, and (2) compare the system’s diagnostic accuracy with that of routine clinical care decisions compared with the same gold standard.Methods and analysisCADDIE2 is a prospective diagnostic accuracy study taking place at the Department of Pediatric Cardiology and Intensive Care Medicine at the Hannover Medical School; it represents the second step towards our vision of cross-institutional and data-driven decision-support for intensive care environments (CADDIE). The study comprises (1) recruitment of up to 300 patients (start date 1 August 2018), (2) creation of gold standard decisions (start date 1 May 2019), (3) routine SIRS assessments by physicians (starts with recruitment), (4) SIRS assessments by a CDSS (start date 1 May 2019), and (5) statistical analysis with a modified approach for determining sensitivity and specificity and comparing the accuracy results of the different diagnostic approaches (planned start date 1 July 2019).Ethics and disseminationEthics approval was obtained at the study centre (Ethics Committee of Hannover Medical School). Results of the main study will be communicated via publication in a peer-reviewed journal.Trial registration numberClinicalTrials.govNCT03661450; Pre-results.

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Evidence-based Practice in Action: Ensuring Quality of Pediatric Assessment Frequency

McDonald

Eckhardt

2017

Journal of Pediatric Nursing

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A Pediatric Critical Care Practice Group: Use of Expertise and Evidence-Based Practice in Identifying and Establishing “Best” Practice

Cited by 4 publications

References 8 publications

Prediction models for SIRS, sepsis and associated organ dysfunctions in paediatric intensive care: study protocol for a diagnostic test accuracy study

Prediction models for SIRS, sepsis and associated organ dysfunctions in paediatric intensive care: study protocol for a diagnostic test accuracy study

CADDIE2—evaluation of a clinical decision-support system for early detection of systemic inflammatory response syndrome in paediatric intensive care: study protocol for a diagnostic study

Evidence-based Practice in Action: Ensuring Quality of Pediatric Assessment Frequency

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