Clinical audit of a Paediatric Emergency Warning Score (PEWS) in the paediatric oncology unit of a newly established tertiary cancer institute

Predicting Clinical Deterioration and Mortality at Differing Stages During Hospitalization: A Systematic Review of Risk Prediction Models in Children in Low- and Middle-Income Countries

OBJECTIVE

To determine which risk prediction model best predicts clinical deterioration in children at different stages of hospital admission in low- and middle-income countries.

METHODS

For this systematic review, Embase and MEDLINE databases were searched, and Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed. The key search terms were "development or validation study with risk-prediction model" AND "deterioration or mortality" AND "age 0-18 years" AND "hospital-setting: emergency department (ED), pediatric ward (PW), or pediatric intensive care unit (PICU)" AND "low- and middle-income countries." The Prediction Model Risk of Bias Assessment Tool was used by two independent authors. Forest plots were used to plot area under the curve according to hospital setting. Risk prediction models used in two or more studies were included in a meta-analysis.

RESULTS

We screened 9486 articles and selected 78 publications, including 67 unique predictive models comprising 1.5 million children. The best performing models individually were signs of inflammation in children that can kill (SICK) (ED), pediatric early warning signs resource limited settings (PEWS-RL) (PW), and Pediatric Index of Mortality (PIM) 3 as well as pediatric sequential organ failure assessment (pSOFA) (PICU). Best performing models after meta-analysis were SICK (ED), pSOFA and Pediatric Early Death Index for Africa (PEDIA)-immediate score (PW), and pediatric logistic organ dysfunction (PELOD) (PICU). There was a high risk of bias in all studies.

CONCLUSIONS

We identified risk prediction models that best estimate deterioration, although these risk prediction models are not routinely used in low- and middle-income countries. Future studies should focus on large scale external validation with strict methodological criteria of multiple risk prediction models as well as study the barriers in the way of implementation.

TRIAL REGISTRATION

PROSPERO International Prospective Register of Systematic Reviews: Prospero ID: CRD42021210489.

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

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.

Health professionals' initial experiences and perceptions of the acceptability of a whole-hospital, pro-active electronic paediatric early warning system (the DETECT study): a qualitative interview study

Background

Paediatric early warning systems (PEWS) alert health professionals to signs of a child’s deterioration with the intention of triggering an urgent review and escalating care. They can reduce unplanned critical care transfer, cardiac arrest, and death. Electronic systems may be superior to paper-based systems. The objective of the study was to critically explore the initial experiences and perceptions of health professionals about the acceptability of DETECT e-PEWS, and what factors influence its acceptability.

Methods

A descriptive qualitative study (part of The DETECT study) was undertaken February 2020–2021. Single, semi-structured telephone interviews were used. The setting was a tertiary children’s hospital, UK. The participants were health professionals working in study setting and using DETECT e-PEWS. Sampling was undertaken using a mix of convenience and snowballing techniques. Participants represented two user-groups: ‘documenting vital signs’ (D-VS) and ‘responding to vital signs’ (R-VS). Perceptions of clinical utility and acceptability of DETECT e-PEWS were derived from thematic analysis of transcripts.

Results

Fourteen HPs (12 nurses, 2 doctors) participated; seven in D-VS and seven in the R-VS group. Three main themes were identified: complying with DETECT e-PEWS, circumventing DETECT e-PEWS, and disregarding DETECT e-PEWS. Overall clinical utility and acceptability were deemed good for HPs in the D-VS group but there was diversity in perception in the R-VS group (nurses found it more acceptable than doctors). Compliance was better in the D-VS group where use of DETECT e-PEWS was mandated and used more consistently. Some health professionals circumvented DETECT e-PEWS and fell back into old habits. Doctors (R-VS) did not consistently engage with DETECT e-PEWS, which reduced the acceptability of the system, even in those who thought the system brought benefits.

Conclusions

Speed and accuracy of real-time data, automation of triggering alerts and improved situational awareness were key factors that contributed to the acceptability of DETECT e-PEWS. Mandating use of both recording and responding aspects of DETECT e-PEWS is needed to ensure full implementation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12887-022-03411-1.