Predictors and Direct Cost Estimation of Long Stays in Pediatric Intensive Care Units in Saudi Arabia: A Mixed Methods Study

Unplanned Readmissions in Children with Medical Complexity in Saudi Arabia: A Large Multicenter Study

Background

Children with medical complexity (CMC) account for a substantial proportion of healthcare spending, and one-third of their expenditures are due to readmissions. However, knowledge regarding the healthcare-resource utilization and characteristics of CMC in Saudi Arabia is limited.

Objectives

To describe hospitalization patterns and characteristics of Saudi CMC with an unplanned 30-day readmission.

Methodology

This retrospective study included Saudi CMC (aged 0-14 years) who had an unplanned 30-day readmission at six tertiary centers in Riyadh, Jeddah, Dammam, Alahsa, and Almadina between January 2016 and December 2020. Hospital-based inclusion criteria focused on CMC with multiple complex chronic conditions (CCCs) and technology assistance (TA) device use. CMC were compared across demographics, clinical characteristics, and hospital-resource utilization.

Results

A total of 9139 pediatric patients had unplanned 30-day readmission during the study period, of which 680 (7.4%) met the inclusion criteria. Genetic conditions were the most predominant primary pathology (66.3%), with one-third of cases (33.7%) involving the neuromuscular system. During the index admission, pneumonia was the most common diagnosis (33.1%). Approximately 35.1% of the readmissions were after 2 weeks. Pneumonia accounted for 32.5% of the readmissions. After readmission, 16.9% of patients were diagnosed with another CCC or received a new TA device, and the in-hospital mortality rate was 6.6%.

Conclusion

The rate of unplanned 30-day readmissions in children with medical complexity in Saudi Arabia is 7.4%, which is lower than those reported from developed countries. Saudi children with CCCs and TA devices were readmitted approximately within similar post-discharge time and showed distinct hospitalization patterns associated with specific diagnoses. To effectively reduce the risk of 30-day readmissions, targeted measures must be introduced both during the hospitalization period and after discharge.

Using technology to reduce critical deterioration (the DETECT study): a cost analysis of care costs at a tertiary children's hospital in the United Kingdom

BACKGROUND

Electronic early warning systems have been used in adults for many years to prevent critical deterioration events (CDEs). However, implementation of similar technologies for monitoring children across the entire hospital poses additional challenges. While the concept of such technologies is promising, their cost-effectiveness is not established for use in children. In this study we investigate the potential for direct cost savings arising from the implementation of the DETECT surveillance system.

METHODS

Data were collected at a tertiary children's hospital in the United Kingdom. We rely on the comparison between patients in the baseline period (March 2018 to February 2019) and patients in the post-intervention period (March 2020 to July 2021). These provided a matched cohort of 19,562 hospital admissions for each group. From these admissions, 324 and 286 CDEs were observed in the baseline and post-intervention period, respectively. Hospital reported costs and Health Related Group (HRG) National Costs were used to estimate overall expenditure associated with CDEs for both groups of patients.

RESULTS

Comparing post-intervention with baseline data we found a reduction in the total number of critical care days, driven by an overall reduction in the number of CDEs, however without statistical significance. Using hospital reported costs adjusted for the Covid-19 impact, we estimate a non-significant reduction of total expenditure from £16.0 million to £14.3 million (corresponding to £1.7 million of savings - 11%). Additionally, using HRG average costs, we estimated a non-significant reduction of total expenditure from £8.2 million to £ 7.2 million (corresponding to £1.1 million of savings - 13%).

DISCUSSION AND CONCLUSION

Unplanned critical care admissions for children not only impose a substantial burden on patients and families but are also costly for hospitals. Interventions aimed at reducing emergency critical care admissions can be crucial to contribute to the reduction of these episodes' costs. Even though cost reductions were identified in our sample, our results do not support the hypothesis that reducing CDEs using technology leads to a significant reduction on hospital costs.

TRIAL REGISTRATION

Current Controlled Trials ISRCTN61279068, date of registration 07/06/2019, retrospectively registered.

Enhancing Expert Panel Discussions in Pediatric Palliative Care: Innovative Scenario Development and Summarization With ChatGPT-4

This study presents a novel approach to enhance expert panel discussions in a medical conference through the use of ChatGPT-4 (Generative Pre-trained Transformer version 4), a recently launched powerful artificial intelligence (AI) language model. We report on ChatGPT-4's ability to optimize and summarize the medical conference panel recommendations of the first Pan-Arab Pediatric Palliative Critical Care Hybrid Conference, held in Riyadh, Saudi Arabia. ChatGPT-4 was incorporated into the discussions in two sequential phases: first, scenarios were optimized by the AI model to stimulate in-depth conversations; second, the model identified, summarized, and contrasted key themes from the panel and audience discussions. The results suggest that ChatGPT-4 effectively facilitated complex do-not-resuscitate (DNR) conflict resolution by summarizing key themes such as effective communication, collaboration, patient and family-centered care, trust, and ethical considerations. The inclusion of ChatGPT-4 in pediatric palliative care panel discussions demonstrated potential benefits for enhancing critical thinking among medical professionals. Further research is warranted to validate and broaden these insights across various settings and cultures.

Factors influencing the length of stay among patients admitted to a tertiary pediatric intensive care unit in Saudi Arabia

This study aimed to assess the variables contributing to the length of stay in the pediatric intensive care unit. This study utilized a retrospective design by analyzing data from the Virtual Pediatric Systems web-based database. The study was conducted in a tertiary hospital-King Fahad Medical City in Riyadh, Saudi Arabia-from January 1, 2014 to December 31, 2019. The patients were admitted to intensive care with complex medical and surgical diseases. The variables were divided into quantitative and qualitative parameters, including patient data, Pediatric Risk of Mortality III score, and complications. Data from 3,396 admissions were analyzed. In this cohort, the median and mean length of stay were 2.8 (interquartile range, 1.08-7.04) and 7.43 (standard deviation, 14.34) days, respectively. The majority of long-stay patients-defined as those staying longer than 30 days-were less than 12 months of age (44.79%), had lower growth parameters (p < 0.001), and had a history of admission to pediatric intensive care units. Moreover, the majority of long-stay patients primarily suffered from respiratory diseases (51.53%) and had comorbidities and complications during their stay (p < 0.001). Multivariate analysis of all variables revealed that central line-associated bloodstream infections (p < 0.001), external ventricular drain insertion (p < 0.005), tracheostomy (p < 0.001), and use of mechanical ventilation (p < 0.001) had the most significant associations with a longer stay in the pediatric intensive care unit. The factors associated with longer stays included the admission source, central nervous system disease comorbidity, and procedures performed during the stay. Factors such as respiratory support were also associated with prolonged intensive care unit stays.