Variations among Electronic Health Record and Physiologic Streaming Vital Signs for Use in Predictive Algorithms in Pediatric Severe Sepsis

Abstract: Objective This study sought to describe the similarities and differences among physiologic streaming vital signs (PSVSs) and electronic health record (EHR)-documented vital signs (EVSs) in pediatric sepsis. Methods In this retrospective cohort study, we identified sepsis patients admitted to the pediatric intensive care unit. We compared PSVS and EVS measures of heart rate (HR), respiratory rate, oxyhemoglobin saturation, and blood pressure (BP) across domains of completeness, concordance, plausibility, and currency. Results We report 1,095 epochs comprising vital sign data from 541 unique patients. While counts of PSVS measurements per epoch were substantially higher, increased missingness was observed compared with EVS. Concordance was highest among HR and lowest among BP measurements, with bias present in all measures. Percent of time above or below defined plausibility cutoffs significantly differed by measure. All EVS measures demonstrated a mean delay from time recorded at the patient to EHR entry. Conclusion We measured differences between vital sign sources across all data domains. Bias direction differed by measure, possibly related to bedside monitor measurement artifact. Plausibility differences may reflect the more granular nature of PSVS which can be critical in illness detection. Delays in EVS measure currency may impact real-time decision support systems. Technical limitations increased missingness in PSVS measures and reflect the importance of systems monitoring for data continuity. Both PSVS and EVS have advantages and disadvantages that must be weighed when making use of vital signs in decision support systems or as covariates in retrospective analyses.

Angaben zum Objekt

• Standort: Deutsche Nationalbibliothek Frankfurt am Main
• Umfang: Online-Ressource
• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Variations among Electronic Health Record and Physiologic Streaming Vital Signs for Use in Predictive Algorithms in Pediatric Severe Sepsis ; volume:06 ; number:02 ; year:2022 ; pages:e76-e84 ; ACI Open ; 06, Heft 02 (2022), e76-e84

Beteiligte, Orts- und Zeitangaben

• Beteiligte Personen und Organisationen: Dziorny, Adam C. ; Lindell, Robert B. ; Fitzgerald, Julie C. ; Bonafide, Christopher P.

Weitere Informationen

• DOI: 10.1055/s-0042-1755373
• URN: urn:nbn:de:101:1-2022112411473569167049
• Rechteinformation: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
• Letzte Aktualisierung: 15.08.2025, 07:36 MESZ