Predictors and direct cost estimation of long stays in pediatric intensive care units in saudi arabia: A mixed methods study

Abstract

Background: Several factors influence patients’ length of stay (LOS) in pediatric intensive care units (PICUs). This study explored the factors and cost associated with long LOS among pediatric patient population across various PICUs and pediatric surgical cardiac intensive care units (SCICUs). Methods: This is a multi-center concurrent mixed-methods study that was conducted in different PICUs and SCICUs in Riyadh, Saudi Arabia. The units’ leaders were qualitatively interviewed to explore the potential factors contributing to long LOSs in PICUs and SCICUs, and deductive content analysis was used. Microcosting was utilized to estimate the inpatient costs for a sample of long-stay patients (LSPs) and the potential cost savings if those patients were transferred to step-down care units (SDUs) for those who stayed ≥60 days. Results: Ten (90%) leaders of PICUs and SCICUs who were invited had participated. Changing the admission criteria, patient transfer to SDUs, family engagement in the decision-making process, and adopting a national do-not-resuscitate (DNR) policy were factors contributing to short LOSs. On the other hand, administrative constraints, staff avoidance of code status decisions, lack of palliative care resources, and complex patient characteristics were factors associated with long LOSs. The mean inpatient cost per patient was SAR 3.63 million (USD 0.97 million), and the total cost for the 48 patients was SAR 172.95 million (USD 46.12 million). Conclusion: If the recommendation to transfer LSPs after a 60-day PICU stay to SDUs is taken, the estimated cost savings among this sample of patients alone can be as high as SAR 109.47 million (USD 29.19 million). Therefore, future studies should examine the factors contributing to long LOSs in PICUs and SCICUs as well as the effectiveness of different policies aimed at improving the resource allocation and management using more robust study designs and diverse patient population.