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Examining housing insecurity and transportation barriers in pediatric hospital readmissions: insights from structured
Shivani Mehta1, William Brown1,2,3,4,5, Urmimala Sarkar2,6
1Department of Epidemiology and Biostatistics, University of California, San Francisco (UCSF), San Francisco, CA 94158, United States.
Insights
Combining structured and unstructured data significantly improves the identification of social determinants of health (SDOH) in children, revealing a greater impact on hospital readmissions and emergency department visits. This hybrid approach enhances risk assessment for targeted interventions.
Area of Science:
- Pediatric healthcare research
- Health informatics
- Public health
Background:
- Pediatric hospital readmissions are costly and indicate care deficiencies.
- Social determinants of health (SDOH), like housing and transportation insecurity, are critical but understudied in children.
- Identifying SDOH is crucial for improving pediatric health outcomes.
Purpose of the Study:
- To assess the impact of housing and transportation-related SDOH on pediatric readmissions.
- To compare the effectiveness of using structured ICD-10-CM Z-codes versus a hybrid approach (structured data + natural language processing) for SDOH identification.
- To evaluate the association between identified SDOH and readmission risk in pediatric patients.
Main Methods:
- Retrospective cohort study of 8928 pediatric patients (ages 2-17) discharged from January 2018 to January 2023.
- SDOH exposure identified using structured Z-codes and NLP-extracted unstructured data.
- Cox proportional hazards models used to analyze the association between SDOH and 365-day hospital readmission risk.
Main Results:
- The hybrid approach identified 31.7% of patients with SDOH exposure, compared to only 0.8% with structured data alone.
- Patients identified via the hybrid approach showed a higher readmission risk (HR: 2.64) than those identified by structured data alone (HR: 1.99).
- Higher emergency department (ED) utilization was observed in exposed patients, with the hybrid approach showing a stronger association with ED readmissions.
Conclusions:
- Unstructured data analysis significantly enhances SDOH identification in pediatric populations.
- A hybrid data approach reveals stronger associations between SDOH and hospital/ED readmissions.
- Improved risk stratification through hybrid data analysis can guide targeted interventions for pediatric health disparities.
Background:
Pediatric hospital readmissions increase healthcare costs and highlight gaps in care. Social determinants of health (SDOH), such as housing and transportation insecurity, significantly impact outcomes but are underexplored in pediatric populations.
Objectives:
This study evaluates the impact of housing and transportation-related SDOH on pediatric readmissions, comparing structured ICD-10-CM Z-codes alone to a combination of structured and unstructured data extracted via natural language processing (NLP).
Materials And Methods:
We conducted a retrospective cohort study of pediatric patients (ages 2-17) discharged from UCSF Benioff Children's Hospital between January 2018 and January 2023. SDOH exposure was identified using structured Z-codes and NLP-extracted data. The primary outcome was hospital readmission within 365 days. Cox proportional hazards models assessed associations between SDOH and readmission risk.
Results:
Among 8928 patients, only 0.8% were identified as exposed using structured data, compared to 31.7% using combined data. Patients identified through combined data had a higher readmission risk (HR: 2.64, 95% CI: 2.34-2.98) compared to those identified with structured data alone (HR: 1.99, 95% CI: 1.27-3.13). ED utilization was also higher among exposed patients. In the structured-only analysis, exposed patients had a significantly higher hazard of ED readmission (HR: 2.26, 95% CI: 1.65-3.10), whereas the association was slightly attenuated in the combined analysis (HR: 1.49, 95% CI: 1.37-1.62).
Conclusion:
Leveraging unstructured data enhances SDOH identification and reveals stronger associations with hospital and ED readmissions. A hybrid approach enables improved risk stratification and targeted interventions to address pediatric health disparities.
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