Prediction of Readmission Following Sepsis Using Social Determinants of Health

Author:

Amrollahi Fatemeh1,Kennis Brent D.2,Shashikumar Supreeth Prajwal1,Malhotra Atul3,Taylor Stephanie Parks4,Ford James5,Rodriguez Arianna6,Weston Julia6,Maheshwary Romir6,Nemati Shamim1,Wardi Gabriel37,Meier Angela8

Affiliation:

1. Department of Biomedical Informatics, University of California San Diego, La Jolla, CA.

2. School of Medicine, University of California San Diego, La Jolla, CA.

3. Division of Pulmonary, Critical Care and Sleep Medicine, University of California at San Diego, La Jolla, CA.

4. Division of Hospital Medicine, University of Michigan, Ann Arbor, MI.

5. Department of Emergency Medicine, University of California, San Francisco, San Francisco, CA.

6. Department of Medicine, University of California San Diego, La Jolla, CA.

7. Department of Emergency Medicine, University of California San Diego, San Diego, CA.

8. Department of Anesthesiology, Division of Critical Care, University of California, San Diego, La Jolla, CA.

Abstract

OBJECTIVES: To determine the predictive value of social determinants of health (SDoH) variables on 30-day readmission following a sepsis hospitalization as compared with traditional clinical variables. DESIGN: Multicenter retrospective cohort study using patient-level data, including demographic, clinical, and survey data. SETTINGS: Thirty-five hospitals across the United States from 2017 to 2021. PATIENTS: Two hundred seventy-one thousand four hundred twenty-eight individuals in the AllofUs initiative, of which 8909 had an index sepsis hospitalization. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Unplanned 30-day readmission to the hospital. Multinomial logistic regression models were constructed to account for survival in determination of variables associate with 30-day readmission and are presented as adjusted odds rations (aORs). Of the 8909 sepsis patients in our cohort, 21% had an unplanned hospital readmission within 30 days. Median age (interquartile range) was 54 years (41–65 yr), 4762 (53.4%) were female, and there were self-reported 1612 (18.09%) Black, 2271 (25.49%) Hispanic, and 4642 (52.1%) White individuals. In multinomial logistic regression models accounting for survival, we identified that change to nonphysician provider type due to economic reasons (aOR, 2.55 [2.35–2.74]), delay of receiving medical care due to lack of transportation (aOR, 1.68 [1.62–1.74]), and inability to afford flow-up care (aOR, 1.59 [1.52–1.66]) were strongly and independently associated with a 30-day readmission when adjusting for survival. Patients who lived in a ZIP code with a high percentage of patients in poverty and without health insurance were also more likely to be readmitted within 30 days (aOR, 1.26 [1.22–1.29] and aOR, 1.28 [1.26–1.29], respectively). Finally, we found that having a primary care provider and health insurance were associated with low odds of an unplanned 30-day readmission. CONCLUSIONS: In this multicenter retrospective cohort, several SDoH variables were strongly associated with unplanned 30-day readmission. Models predicting readmission following sepsis hospitalization may benefit from the addition of SDoH factors to traditional clinical variables.

Funder

NIGMS

Publisher

Ovid Technologies (Wolters Kluwer Health)

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