{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T13:33:03Z","timestamp":1783949583706,"version":"3.55.0"},"reference-count":36,"publisher":"AACN Publishing","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,5,1]]},"abstract":"<jats:p>Unplanned readmissions after sepsis, rates of which range from 17.5% to 32%, pose substantial challenges for health care systems. Associated costs for sepsis surpass those for other critical conditions. Existing readmission risk models rely primarily on clinical indicators, which limits their predictive accuracy for patients with sepsis. This review explores how integrating social determinants of health into readmission models can enhance model precision and applicability for predicting 30-day readmission among sepsis survivors. Although socioeconomic status, neighborhood deprivation, and access to health care are known to influence postdischarge outcomes, these social determinants of health are underused in current risk algorithms. Evidence shows that incorporating social determinants of health into predictive models significantly improves model performance. Furthermore, failure to account for health disparities driven by social determinants of health in high-risk populations can exacerbate existing inequities in health care outcomes. The integration of social determinants of health into sepsis readmission risk models offers a promising avenue for improving prediction accuracy, reducing readmissions, and optimizing care for vulnerable populations. Future research should focus on refining these models and exploring postdischarge monitoring strategies to further mitigate the burden of sepsis readmissions.<\/jats:p>","DOI":"10.4037\/ajcc2025455","type":"journal-article","created":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T02:03:02Z","timestamp":1746064982000},"page":"230-235","source":"Crossref","is-referenced-by-count":6,"title":["Reducing Readmission for Sepsis by Improving Risk Prediction Algorithms"],"prefix":"10.4037","volume":"34","author":[{"given":"Valerie J.","family":"Renard","sequence":"first","affiliation":[{"name":"Valerie J. Renard is an acute care nurse practitioner, Department of Hospital Medicine, Duke University Health System, Durham, North Carolina, and a nurse practitioner and research scientist, Inpatient Research, Department of Medicine, Carilion Clinic, Roanoke, Virginia."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Parisa","family":"Farahani","sequence":"additional","affiliation":[{"name":"Parisa Farahani is a senior research associate, Inpatient Research, Department of Medicine, Carilion Clinic, Roanoke, Virginia, and a research scholar, Division of General Internal Medicine, Duke University, Durham, North Carolina."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Leanne M.","family":"Boehm","sequence":"additional","affiliation":[{"name":"Leanne M. Boehm is an assistant professor, School of Nursing, Vanderbilt University, Nashville, Tennessee."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marianna","family":"LaNoue","sequence":"additional","affiliation":[{"name":"Marianna LaNoue is a professor of statistics and measurement, School of Nursing, Vanderbilt University, Nashville, Tennessee."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Oluwatosin","family":"Akingbule","sequence":"additional","affiliation":[{"name":"Oluwatosin Akingbule is a postdoctoral research fellow, Department of Implementation Science, Wake Forest University School of Medicine, Winston Salem, North Carolina."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hanzhang","family":"Xu","sequence":"additional","affiliation":[{"name":"Hanzhang Xu is an associate professor, Department of Family Medicine and Community Health, Duke University, and an associate professor, School of Nursing, Duke University, Durham, North Carolina."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Amy L. B.","family":"Frazier","sequence":"additional","affiliation":[{"name":"Amy L. B. 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