Association of Socioeconomic Area Deprivation Index with Hospital Readmissions After Colon and Rectal Surgery

• Published in: Journal of gastrointestinal surgery 2021-03, Vol.25 (3), p.795-808
• Main Authors: Ghirimoldi, Federico M., Schmidt, Susanne, Simon, Richard C., Wang, Chen-Pin, Wang, Zhu, Brimhall, Bradley B., Damien, Paul, Moffett, Eric E., Manuel, Laura S., Sarwar, Zaheer U., Shireman, Paula K.
• Format: Article
• Language: English
• Subjects: Colon; Colorectal surgery; Electronic health records; Ethnicity; Female; Fines & penalties; Gastroenterology; Hospitals; Humans; Male; Medicaid; Medicare; Medicine; Medicine & Public Health; Neighborhoods; Operations management; Original Article; Ostomy; Patient Readmission; Patients; Quality control; Residence Characteristics; Retrospective Studies; Risk Factors; Socioeconomic Factors; Surgery; Variables
• ISSN: 1091-255X; 1873-4626
• DOI: 10.1007/s11605-020-04754-9

Background Risk adjustment for reimbursement and quality measures omits social risk factors despite adversely affecting health outcomes. Social risk factors are not usually available in electronic health records (EHR) or administrative data. Socioeconomic status can be assessed by using US Census data. Distressed Communities Index (DCI) is based upon zip codes, and the Area Deprivation Index (ADI) provides more granular estimates at the block group level. We examined the association of neighborhood disadvantage using the ADI, DCI, and patient-level insurance status on 30-day readmission risk after colorectal surgery. Methods Our 677 patient cohort was derived from the 2013–2017 National Surgical Quality Improvement Program at a safety net hospital augmented with EHR data to determine insurance status and 30-day readmissions. Patients’ home addresses were linked to the ADI and DCI. Results Our cohort consisted of 53.9% males and 63.8% Hispanics with a 22.9% 30-day readmission rate from the date of discharge; > 50% lived in highly deprived neighborhoods. Controlling for medical comorbidities and complications, ADI was associated with increased risk of 30 days from the date of discharge readmissions among patients living in medium (OR = 2.15, p  = .02) or high (OR = 1.88, p  = .03) deprived areas compared to less-deprived neighborhoods, but not insurance status or DCI. Conclusions The ADI identified patients living in deprived communities with increased readmission risk. Our results show that block-group level ADI can potentially be used in risk adjustment, to identify high-risk patients and to design better care pathways that improve health outcomes.