Clinical utility and acceptability of a whole-hospital, pro-active electronic paediatric early warning system (the DETECT study): A prospective e-survey of parents and health professionals

PLoS One. 2022 Sep 15;17(9):e0273666. doi: 10.1371/journal.pone.0273666. eCollection 2022.

Abstract

Background: Paediatric early warning systems (PEWS) are a means of tracking physiological state and alerting healthcare professionals about signs of deterioration, triggering a clinical review and/or escalation of care of children. A proactive end-to-end deterioration solution (the DETECT surveillance system) with an embedded e-PEWS that included sepsis screening was introduced across a tertiary children's hospital. One component of the implementation programme was a sub-study to determine an understanding of the DETECT e-PEWS in terms of its clinical utility and its acceptability.

Aim: This study aimed to examine how parents and health professionals view and engage with the DETECT e-PEWS apps, with a particular focus on its clinical utility and its acceptability.

Method: A prospective, closed (tick box or sliding scale) and open (text based) question, e-survey of parents (n = 137) and health professionals (n = 151) with experience of DETECT e-PEWS. Data were collected between February 2020 and February 2021.

Results: Quantitative data were analysed using descriptive and inferential statistics and qualitative data with generic thematic analysis. Overall, both clinical utility and acceptability (across seven constructs) were high across both stakeholder groups although some challenges to utility (e.g., sensitivity of triggers within specific patient populations) and acceptability (e.g., burden related to having to carry extra technology) were identified.

Conclusion: Despite the multifaceted nature of the intervention and the complexity of implementation across a hospital, the system demonstrated clinical utility and acceptability across two key groups of stakeholders: parents and health professionals.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Child
  • Electronics
  • Health Personnel*
  • Hospitals*
  • Humans
  • Parents
  • Prospective Studies