Clinical Decision Support in the PICU: Implications for Design and Evaluation*

Dziorny, Adam; Heneghan, Julia A.; Bhat, Moodakare A.; Karavite, Dean; Sanchez-Pinto, L. Nelson; McArthur, Jennifer; Muthu, Naveen

doi:10.1097/pcc.0000000000002973

Cited by 11 publications

(17 citation statements)

References 18 publications

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“…When a clinical problem is insufficiently defined or the research priorities have not been fully considered and debated, scoping reviews and consensus conferences can aid in lending clarity to what is known and what future research priorities should be. In the last 3 years, PALISI has focused on aspects of hemopoietic stem-cell transplantation (HCT) (16)(17)(18), transfusion and bleeding (19,20), measuring outcomes (21)(22)(23), and clinical decision support (24). Table 2 shows other examples of consensus conferences and their links to prior or future PALISI Network studies.…”

Section: Scoping Reviews and Consensus Meetingsmentioning

confidence: 99%

Pediatric Acute Lung Injury and Sepsis Investigators (PALISI): Evolution of an Investigator-Initiated Research Network

Randolph

Bembea

Cheifetz

et al. 2022

Pediatric Critical Care Medicine

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The Pediatric Acute Lung Injury and Sepsis Investigators (PALISI) Network originated over 20 years ago to foster research to optimize the care of critically ill infants and children. Over this period, PALISI has seen two major evolutions: formalization of our network infrastructure and a broadening of our clinical research focus. First, the network is unique in that its activities and meetings are funded by subscriptions from members who now comprise a multidisciplinary group of investigators from over 90 PICUs all over the United States (US) and Canada, with collaborations across the globe. In 2020, the network converted into a standalone, nonprofit organizational structure (501c3), making the PALISI Network formally independent of academic and clinical institutions or professional societies. Such an approach allows us to invest in infrastructure and future initiatives with broader opportunities for fund raising. Second, our research investigations have expanded beyond the original focus on sepsis and acute lung injury, to incorporate the whole field of pediatric critical care, for example, efficient liberation from mechanical ventilator support, prudent use of blood products, improved safety of intubation practices, optimal sedation practices and glucose control, and pandemic research on influenza and COVID-19. Our network approach in each field follows, where necessary, the full spectrum of clinical and translational research, including: immunobiology studies for understanding basic pathologic mechanisms; surveys to explore contemporary clinical practice; consensus conferences to establish agreement about literature evidence; observational prevalence and incidence studies to measure scale of a clinical issue or question; case control studies as preliminary best evidence for design of definitive prospective studies; and, randomized controlled trials for informing clinical care. As a research network, PALISI and its related subgroups have published over 350 peer-reviewed publications from 2002 through September 2022.

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Section: Scoping Reviews and Consensus Meetingsmentioning

confidence: 99%

Pediatric Acute Lung Injury and Sepsis Investigators (PALISI): Evolution of an Investigator-Initiated Research Network

Randolph

Bembea

Cheifetz

et al. 2022

Pediatric Critical Care Medicine

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“…These limitations were highlighted in a recent study in which most pediatric critical care providers were neutral or disagreed that current predictive algorithms provided useful information. 96 Providers agreed that important goals included evidence-based CDSS with a proven impact on patient safety, that were well-placed and delivered at the right time. 96 Providers expressed concern about the accuracy of CDSS, the effect on practitioners' critical reasoning, and the burden of increased time spent on the computer.…”

Section: Clinical Decision Supportmentioning

confidence: 99%

“…96 Providers agreed that important goals included evidence-based CDSS with a proven impact on patient safety, that were well-placed and delivered at the right time. 96 Providers expressed concern about the accuracy of CDSS, the effect on practitioners' critical reasoning, and the burden of increased time spent on the computer. 96…”

Section: Clinical Decision Supportmentioning

confidence: 99%

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The use of machine learning and artificial intelligence within pediatric critical care

et al. 2022

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The field of pediatric critical care has been hampered in the era of precision medicine by our inability to accurately define and subclassify disease phenotypes. This has been caused by heterogeneity across age groups that further challenges the ability to perform randomized controlled trials in pediatrics. One approach to overcome these inherent challenges include the use of machine learning algorithms that can assist in generating more meaningful interpretations from clinical data. This review summarizes machine learning and artificial intelligence techniques that are currently in use for clinical data modeling with relevance to pediatric critical care. Focus has been placed on the differences between techniques and the role of each in the clinical arena. The various forms of clinical decision support that utilize machine learning are also described. We review the applications and limitations of machine learning techniques to empower clinicians to make informed decisions at the bedside.

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“…Some of these barriers may include alert fatigue, inappropriate alerting, disrupted workflows, and perceived threats to autonomy. 2,4 In a survey of 45 institutions, Dziorny et al 5 found that pediatric intensive care practitioners viewed CDS tools as intrusive with concerns for diminished critical thinking. Williams et al 3 acknowledge these barriers as a potential explanation for the modest impact on improving their outcome of interest.…”

mentioning

confidence: 99%

Making tools that work for us: Improving clinical decision support

Liang

Molloy

2023

Journal of Hospital Medicine

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Hospitalists encounter clinical decision support (CDS) tools hourly in their daily clinical practice. This support can come in the form of clinical algorithms, abnormal lab result alerts, order sets, medication dosage errors, and more. 1 CDS tools are implemented with the goal of increasing evidence-based practice and improving patient outcomes, but evidence from clinical trials on the impact of these tools is mixed, with the greatest improvement seen in process measures rather than outcomes. 1,2 CDS tools are often implemented as part of operational or quality improvement work without rigorous testing or postimplementation evaluation. Yet, like any other tool utilized in clinical

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Clinical Decision Support in the PICU: Implications for Design and Evaluation*

Abstract: To assess the current landscape of clinical decision support (CDS) tools in PICUs in order to identify priority areas of focus in this field.

Cited by 11 publications

References 18 publications

Pediatric Acute Lung Injury and Sepsis Investigators (PALISI): Evolution of an Investigator-Initiated Research Network

Pediatric Acute Lung Injury and Sepsis Investigators (PALISI): Evolution of an Investigator-Initiated Research Network

The use of machine learning and artificial intelligence within pediatric critical care

Making tools that work for us: Improving clinical decision support

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