Deterioration to decision: a comprehensive literature review of rapid response applications for deteriorating patients in acute care settings

Can an increase in nursing care complexity raise the risk of intra-hospital and intensive care unit transfers in children? A retrospective observational study

INTRODUCTION

Intra-hospital patient transfers (IPTs) and transfers to intensive care units (ICUs) are high-risk events in pediatric care. Nursing care complexity, reflected by nursing diagnoses (NDs) and nursing actions (NAs), may influence the frequency of these transfers. This study explores the association between nursing care complexity and IPTs, including ICU transfers, in hospitalized children.

MATERIALS AND METHODS

A retrospective observational study was conducted at a tertiary care university hospital in Italy. Data from 1013 children aged 2 to 12 years were collected from electronic health records. Sociodemographic, clinical, and nursing data, including NDs and NAs, were analyzed. Latent Class Analysis classified nursing care complexity, while backward elimination regression and binary logistic regression identified predictors of IPTs and ICU transfers.

RESULTS

Significant positive correlations were found between IPTs and both NDs (rs = 0.326, p < 0.001) and NAs (rs = 0.428, p < 0.001). Key predictors of IPTs included Diagnosis Related Groups (DRG) weight, total comorbidities, surgical DRG, the number of medications used, and high nursing care complexity. ICU-transferred patients had significantly higher nursing care complexity (6.54 vs. 3.46 NDs, p < 0.001; 31 vs. 16 NAs, p < 0.001). High nursing care complexity increased the likelihood of ICU transfer by 18 times (OR = 18.413, p < 0.001).

CONCLUSION

Nursing care complexity strongly influences IPTs and ICU transfers. Close monitoring of patients with high nursing care complexity is essential to anticipate transfers and reduce clinical risks.

Using clinical simulation to assess a new paediatric ESCALATION system education package: Empirical research mixed methods

AIM

The aim of the study was to assess the suitability of an online education package to prepare health professionals to use a new paediatric early warning system.

DESIGN

Quasi-experimental mixed methods using co-production.

METHODS

Participants completed the Package and participated in up to four clinical scenarios. Data were collected using self-report surveys, and during clinical scenarios; escalation of care, documentation, family involvement, communication handovers were assessed, and recorded debriefings were thematically analysed. Data were integrated using tabulated joint displays.

RESULTS

Eleven nurses and three doctors were recruited from three mixed adult and paediatric hospitals. Following completion of the Package and clinical scenarios 13/14 (93%) participants agreed preparedness and confidence to use the ESCALATION System had increased. For 53% handovers, the communication framework was followed, for 79% charts, documentation was complete. Participants engaged with the parent (actor) for 97% scenario interactions. The Package was effective and participation in clinical scenarios appeared to enhance learning.

PATIENT OR PUBLIC CONTRIBUTION

Consumers participated in the steering group overseeing the study and in the expert panel who reviewed the education package and clinical scenarios.

ROMI: A Real-Time Optical Digit Recognition Embedded System for Monitoring Patients in Intensive Care Units

With advances in the Internet of Things, patients in intensive care units are constantly monitored to expedite emergencies. Due to the COVID-19 pandemic, non-face-to-face monitoring has been required for the safety of patients and medical staff. A control center monitors the vital signs of patients in ICUs. However, some medical devices, such as ventilators and infusion pumps, operate in a standalone fashion without communication capabilities, requiring medical staff to check them manually. One promising solution is to use a robotic system with a camera. We propose a real-time optical digit recognition embedded system called ROMI. ROMI is a mobile robot that monitors patients by recognizing digits displayed on LCD screens of medical devices in real time. ROMI consists of three main functions for recognizing digits: digit localization, digit classification, and digit annotation. We developed ROMI by using Matlab Simulink, and the maximum digit recognition performance was 0.989 mAP on alexnet. The developed system was deployed on NVIDIA GPU embedded platforms: Jetson Nano, Jetson Xavier NX, and Jetson AGX Xavier. We also created a benchmark by evaluating the runtime performance by considering ten pre-trained CNN models and three NVIDIA GPU platforms. We expect that ROMI will support medical staff with non-face-to-face monitoring in ICUs, enabling more effective and prompt patient care.

Development of an evidence-based ESCALATION system for recognition and response to paediatric clinical deterioration

AIM

The aim of this study was to develop an evidence-based paediatric early warning system for infants and children that takes into consideration a variety of paediatric healthcare contexts and addresses barriers to escalation of care.

METHODS

A three-stage intervention development framework consisted of Stage 1: evidence review, benchmarking, stakeholder (health professionals, decision-makers, and health consumers) engagement, and consultation; Stage 2: planning and coproduction by the researchers and stakeholders using action research cycles; and Stage 3: prototyping and testing.

RESULTS

A prototype evidence-based system incorporated human factor principles, used a structured approach to patient assessment, promoted situational awareness, and included family as well as clinician concern. Family involvement in detecting changes in their child's condition was supported by posters and flyers codesigned with health consumers. Five age-specific observation and response charts included 10 weighted variables and one unweighted variable (temperature) to convey a composite early warning score. The escalation pathway was supported by a targeted communication framework (iSoBAR NOW).

CONCLUSION

The development process resulted in an agreed uniform ESCALATION system incorporating a whole-system approach to promote critical thinking, situational awareness for the early recognition of paediatric clinical deterioration as well as timely and effective escalation of care. Incorporating family involvement was a novel component of the system.

Why do healthcare professionals fail to escalate as per the early warning system (EWS) protocol? A qualitative evidence synthesis of the barriers and facilitators of escalation

Background

Early warning systems (EWSs) are used to assist clinical judgment in the detection of acute deterioration to avoid or reduce adverse events including unanticipated cardiopulmonary arrest, admission to the intensive care unit and death. Sometimes healthcare professionals (HCPs) do not trigger the alarm and escalate for help according to the EWS protocol and it is unclear why this is the case. The aim of this qualitative evidence synthesis was to answer the question ‘why do HCPs fail to escalate care according to EWS protocols?’ The findings will inform the update of the National Clinical Effectiveness Committee (NCEC) National Clinical Guideline No. 1 Irish National Early Warning System (INEWS).

Methods

A systematic search of the published and grey literature was conducted (until February 2018). Data extraction and quality appraisal were conducted by two reviewers independently using standardised data extraction forms and quality appraisal tools. A thematic synthesis was conducted by two reviewers of the qualitative studies included and categorised into the barriers and facilitators of escalation. GRADE CERQual was used to assess the certainty of the evidence.

Results

Eighteen studies incorporating a variety of HCPs across seven countries were included. The barriers and facilitators to the escalation of care according to EWS protocols were developed into five overarching themes: Governance, Rapid Response Team (RRT) Response, Professional Boundaries, Clinical Experience, and EWS parameters. Barriers to escalation included: Lack of Standardisation, Resources, Lack of accountability, RRT behaviours, Fear, Hierarchy, Increased Conflict, Over confidence, Lack of confidence, and Patient variability. Facilitators included: Accountability, Standardisation, Resources, RRT behaviours, Expertise, Additional support, License to escalate, Bridge across boundaries, Clinical confidence, empowerment, Clinical judgment, and a tool for detecting deterioration. These are all individual yet inter-related barriers and facilitators to escalation.

Conclusions

The findings of this qualitative evidence synthesis provide insight into the real world experience of HCPs when using EWSs. This in turn has the potential to inform policy-makers and HCPs as well as hospital management about emergency response system-related issues in practice and the changes needed to address barriers and facilitators and improve patient safety and quality of care.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12873-021-00403-9.