Predicting Healthcare Workload in Pediatric Home Hospitalization: The Role of Patient Complexity and Family Participation.

Background: Hospital-at-home (HAH) programs deliver hospital-level care in patients' homes, improving satisfaction and optimizing resource use. While widely adopted in adults, pediatric HAH remains limited. At Sant Joan de Déu Hospital (Barcelona, Spain), the pediatric HAH program for acutely ill children has expanded to include more clinically complex cases. Family involvement is essential, as caregivers are trained to administer treatments, monitor clinical status, and support telematic follow-ups, supporting the healthcare team's workload. Objective: To identify patient characteristics influencing healthcare workload and develop a predictive model to enhance resource allocation. Methods: This single-center, prospective cohort study included all patients admitted to the pediatric HAH program for one year. Primary variables were caregiver training time, home visiting time, patient age, type of care provided, and clinical complexity. Secondary variables included referral specialty and team composition. Data were collected using digital time-tracking, manual records, and clinical databases. Analyses included Kruskal-Wallis and Dunn's multiple comparison tests. Results: All variables showed significant differences in training and visiting times. Training time ranged from 19 to 157 min; visiting time from 6.2 to 157 min. A predictive model using five key variables estimated visiting time, and another model based on care type estimated training time were created. Conclusions: Patient characteristics and caregiver involvement significantly affect direct care workload. These findings can inform strategies to optimize staffing and scale pediatric HAH programs effectively.