Using the Electronic Medical Record to Create a Pediatric Sepsis Alert

Coffman, Zachary J; Smith, Janine; Hubbard, Cheryl; Chen, Emily; McDaniel, Lynn

doi:10.1542/peds.141.1_meetingabstract.444

Cited by 1 publication

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“…Of the 13 studies, 11 (85%) were conducted in the United States, whereas the remaining 2 (15%) studies did not specify in which country they were conducted [ 64 , 73 ] ( Multimedia Appendix 6 ). Of the 13 studies, 12 (92%) were conducted in children’s hospitals, whereas the remaining study [ 58 ] was conducted at a general hospital. All studies used quantitative methods, with the principal study design split between single cohort and before-after studies ( Table 1 ).…”

Section: Resultsmentioning

confidence: 99%

“…The most common outcomes investigated were patient outcomes and sepsis treatment and management outcomes ( Figure 3 ). Only 1 (8%) conference abstract [ 58 ] investigated an outcome related to the CCDS system usability, and none of the studies investigated pediatric CCDS-related cost outcomes ( Figure 3 ). The most commonly investigated patient outcome was sepsis identification (9/13, 69%; Table 1 ).…”

Section: Resultsmentioning

confidence: 99%

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Computerized Clinical Decision Support Systems for the Early Detection of Sepsis Among Pediatric, Neonatal, and Maternal Inpatients: Scoping Review

Ackermann¹,

Baker²,

Festa³

et al. 2022

JMIR Med Inform

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Background Sepsis is a severe condition associated with extensive morbidity and mortality worldwide. Pediatric, neonatal, and maternal patients represent a considerable proportion of the sepsis burden. Identifying sepsis cases as early as possible is a key pillar of sepsis management and has prompted the development of sepsis identification rules and algorithms that are embedded in computerized clinical decision support (CCDS) systems. Objective This scoping review aimed to systematically describe studies reporting on the use and evaluation of CCDS systems for the early detection of pediatric, neonatal, and maternal inpatients at risk of sepsis. Methods MEDLINE, Embase, CINAHL, Cochrane, Latin American and Caribbean Health Sciences Literature (LILACS), Scopus, Web of Science, OpenGrey, ClinicalTrials.gov, and ProQuest Dissertations and Theses Global (PQDT) were searched by using a search strategy that incorporated terms for sepsis, clinical decision support, and early detection. Title, abstract, and full-text screening was performed by 2 independent reviewers, who consulted a third reviewer as needed. One reviewer performed data charting with a sample of data. This was checked by a second reviewer and via discussions with the review team, as necessary. Results A total of 33 studies were included in this review—13 (39%) pediatric studies, 18 (55%) neonatal studies, and 2 (6%) maternal studies. All studies were published after 2011, and 27 (82%) were published from 2017 onward. The most common outcome investigated in pediatric studies was the accuracy of sepsis identification (9/13, 69%). Pediatric CCDS systems used different combinations of 18 diverse clinical criteria to detect sepsis across the 13 identified studies. In neonatal studies, 78% (14/18) of the studies investigated the Kaiser Permanente early-onset sepsis risk calculator. All studies investigated sepsis treatment and management outcomes, with 83% (15/18) reporting on antibiotics-related outcomes. Usability and cost-related outcomes were each reported in only 2 (6%) of the 31 pediatric or neonatal studies. Both studies on maternal populations were short abstracts. Conclusions This review found limited research investigating CCDS systems to support the early detection of sepsis among pediatric, neonatal, and maternal patients, despite the high burden of sepsis in these vulnerable populations. We have highlighted the need for a consensus definition for pediatric and neonatal sepsis and the study of usability and cost-related outcomes as critical areas for future research. International Registered Report Identifier (IRRID) RR2-10.2196/24899

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%