{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T07:07:11Z","timestamp":1778828831221,"version":"3.51.4"},"reference-count":40,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2022,1,27]],"date-time":"2022-01-27T00:00:00Z","timestamp":1643241600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["shmpublications.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Journal of Hospital Medicine"],"published-print":{"date-parts":[[2022,2]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>Safety\u2010net hospitals (SNHs) treat more maternal patients with risk factors for postpartum readmission.<\/jats:p><\/jats:sec><jats:sec><jats:title>Objective<\/jats:title><jats:p>To assess how patient, hospital, and community characteristics explain the SNH\/non\u2010SNH disparity in postpartum readmission rates.<\/jats:p><\/jats:sec><jats:sec><jats:title>Design<\/jats:title><jats:p>A linear probability model assessed covariates associated with postpartum readmissions. Oaxaca\u2013Blinder decomposition estimates quantified the contribution of covariates to the SNH\/non\u2010SNH disparity in postpartum readmission rates.<\/jats:p><\/jats:sec><jats:sec><jats:title>Setting<\/jats:title><jats:p>Healthcare Cost and Utilization Project 2016\u20132018 State Inpatient Databases from 25 states.<\/jats:p><\/jats:sec><jats:sec><jats:title>Participants<\/jats:title><jats:p>3.5 million maternal delivery stays.<\/jats:p><\/jats:sec><jats:sec><jats:title>Measurements<\/jats:title><jats:p>The outcome was inpatient readmission within 42 days of delivery. SNHs had a share of Medicaid\/uninsured stays in the top quartile. A range of patient, hospital, and community characteristics was considered as covariates.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The unadjusted postpartum readmission rate was 4.2 per 1000 index deliveries higher at SNHs than at non\u2010SNHs (19.1 vs. 14.9, <jats:italic>p<\/jats:italic>\u2009&lt;\u2009.001). Adjustment reduced the risk difference to 0.65 per 1000 (95% confidence interval [CI]: \u20130.14, 1.44). Patient (66%), hospital (14%), and community (4%) characteristics explained 84% of the disparity. The single largest contributors to the disparity were race\/ethnicity (20%), hypertension (12%), hospital preterm delivery rate (10%), and preterm delivery (7%). Collectively, patient comorbidities explained 31% of the disparity.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>Higher postpartum readmission rates at SNHs versus non\u2010SNHs were largely due to differences in the patient mix rather than hospital factors. Hospital initiatives are needed to reduce the risk of postpartum readmissions among SNH patients. Improving factors that contribute to the disparity, including underlying health conditions and health inequities associated with race, requires enduring investments in public health.<\/jats:p><\/jats:sec>","DOI":"10.1002\/jhm.2769","type":"journal-article","created":{"date-parts":[[2022,1,27]],"date-time":"2022-01-27T05:28:44Z","timestamp":1643261324000},"page":"77-87","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Contributors to disparities in postpartum readmission rates between safety\u2010net and non\u2010safety\u2010net hospitals: A decomposition analysis"],"prefix":"10.1002","volume":"17","author":[{"given":"Lawrence D.","family":"Reid","sequence":"first","affiliation":[{"name":"Agency for Healthcare Research and Quality Rockville Maryland USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Audrey J.","family":"Weiss","sequence":"additional","affiliation":[{"name":"IBM Watson Health Santa Barbara California USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kathryn R.","family":"Fingar","sequence":"additional","affiliation":[{"name":"IBM Watson Health Santa Barbara California USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2022,1,27]]},"reference":[{"key":"e_1_2_8_2_1","unstructured":"BaileyMK WeissAJ BarrettML Joanna JiangH. 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