Presenter Status
Fellow
Abstract Type
Research
Primary Mentor
Henry Puls, MD
Start Date
14-5-2025 11:30 AM
End Date
14-5-2025 1:30 PM
Presentation Type
Poster Presentation
Description
Background: Children with medical complexity (CMC) use a greater amount of inpatient resources and stand to benefit from unique care models and coordination. However, hospital resources can be limited, and a better understanding of which CMC are high resource users could improve hospital and staff planning.
Objectives/Goal: To develop a risk score predictive of recurrent high intensity inpatient utilization among CMC.
Methods/Design: We conducted a retrospective cohort study of children <18 years old with ≥3 complex chronic conditions (CCC) discharged from one of 48 children’s hospitals in the Pediatric Health Information System during 2021 and 2022. To reflect CMC typically cared for by a general medical service, children with cardiac procedures, dialysis, oncology, or transplant CCCs, and index hospitalization mortality were excluded. We used multivariable logistic regression to determine factors present on the index hospitalization associated with ≥5 hospitalizations or ≥3 hospitalizations with one lasting ≥25 days within any 365-day period (high inpatient utilization) in 2021-2023. We developed risk scoring system using model coefficients and defined the optimal risk score cutoff to maximize sensitivity and specificity. We then applied the risk score cutoff to children discharged to determine (a) ratio of predicted:actual CMC with recurrent high resource use and (b) the total predicted daily volume on 50th, 75th, and 90th percentile days for each hospital.
Results: Of 44,432 included children, 9,596 (21.6%) had high inpatient utilization (Table). Children under 1 year of age had the highest odds of high inpatient utilization (OR 2.26 [95% CI: 2.16, 2.37]) and all CCC and technology groups (except metabolic) met statistical significance (Figure 1). The optimal risk score cutoff was 29 and predicted 17,411 (39.2%) CMC as high inpatient resource utilizers; the predicted:actual ratio of CMC with high inpatient utilization was 1.81. The mean daily census of the 50th, 75th, and 90th percentiles across hospitals was 28 CMC with recurrent high utilization (± 17), 34 (±18), and 39 (±19; Figure2).
Conclusions: It is feasible to develop a risk score predictive of recurrent high inpatient utilization among CMC. There is substantial variability in volume of CMC with high utilization between pediatric hospitals. The risk score cutoff values can be modified to suit different applications and institution-specific objectives. These applications could include a dedicated service line, staffing, or formal hand off.
Included in
Higher Education and Teaching Commons, Medical Education Commons, Pediatrics Commons, Science and Mathematics Education Commons
A Risk Score to Predict Recurrent High Intensity Inpatient Resource Utilization for Children with Medical Complexity.
Background: Children with medical complexity (CMC) use a greater amount of inpatient resources and stand to benefit from unique care models and coordination. However, hospital resources can be limited, and a better understanding of which CMC are high resource users could improve hospital and staff planning.
Objectives/Goal: To develop a risk score predictive of recurrent high intensity inpatient utilization among CMC.
Methods/Design: We conducted a retrospective cohort study of children <18 years old with>≥3 complex chronic conditions (CCC) discharged from one of 48 children’s hospitals in the Pediatric Health Information System during 2021 and 2022. To reflect CMC typically cared for by a general medical service, children with cardiac procedures, dialysis, oncology, or transplant CCCs, and index hospitalization mortality were excluded. We used multivariable logistic regression to determine factors present on the index hospitalization associated with ≥5 hospitalizations or ≥3 hospitalizations with one lasting ≥25 days within any 365-day period (high inpatient utilization) in 2021-2023. We developed risk scoring system using model coefficients and defined the optimal risk score cutoff to maximize sensitivity and specificity. We then applied the risk score cutoff to children discharged to determine (a) ratio of predicted:actual CMC with recurrent high resource use and (b) the total predicted daily volume on 50th, 75th, and 90th percentile days for each hospital.
Results: Of 44,432 included children, 9,596 (21.6%) had high inpatient utilization (Table). Children under 1 year of age had the highest odds of high inpatient utilization (OR 2.26 [95% CI: 2.16, 2.37]) and all CCC and technology groups (except metabolic) met statistical significance (Figure 1). The optimal risk score cutoff was 29 and predicted 17,411 (39.2%) CMC as high inpatient resource utilizers; the predicted:actual ratio of CMC with high inpatient utilization was 1.81. The mean daily census of the 50th, 75th, and 90th percentiles across hospitals was 28 CMC with recurrent high utilization (± 17), 34 (±18), and 39 (±19; Figure2).
Conclusions: It is feasible to develop a risk score predictive of recurrent high inpatient utilization among CMC. There is substantial variability in volume of CMC with high utilization between pediatric hospitals. The risk score cutoff values can be modified to suit different applications and institution-specific objectives. These applications could include a dedicated service line, staffing, or formal hand off.
