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In IECV, data from each health system were first used to develop and internally validate a prediction model; each model was then externally validated using the other health system. Models were fit using penalised logistic regression, and accuracy was estimated using discrimination (concordance index), calibration curves and decision curves. Internal validation was performed using bootstrapping with bias\u2010corrected performance measures. Decision curve analysis was used to display potential cut points where the model provided net benefit for clinical decision\u2010making.<\/jats:p><\/jats:sec><jats:sec><jats:title>Main outcome measures<\/jats:title><jats:p>The outcome was postpartum readmission for either hypertension or pre\u2010eclampsia &lt;6\u2009weeks after delivery.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The postpartum readmission rate for hypertension and pre\u2010eclampsia overall was 0.9% (0.3% and 1.2% by site, respectively). The final model included six variables: age, parity, maximum postpartum diastolic blood pressure, birthweight, pre\u2010eclampsia before discharge and delivery mode (and interaction between pre\u2010eclampsia\u2009\u00d7\u2009delivery mode). Discrimination was adequate at both health systems on internal validation (<jats:italic>c<\/jats:italic>\u2010statistic South: 0.88; 95% confidence interval [CI] 0.87\u20130.89; Northeast: 0.74; 95% CI 0.74\u20130.74). In IECV, discrimination was inconsistent across sites, with improved discrimination for the Northeastern model on the Southern cohort (<jats:italic>c<\/jats:italic>\u2010statistic 0.61 and 0.86, respectively), but calibration was not adequate. Next, model updating was performed using the combined dataset to develop a new model. This final model had adequate discrimination (<jats:italic>c<\/jats:italic>\u2010statistic: 0.80, 95% CI 0.80\u20130.80), moderate calibration (intercept \u22120.153, slope 0.960, <jats:italic>E<\/jats:italic><jats:sub>max<\/jats:sub> 0.042) and provided superior net benefit at clinical decision\u2010making thresholds between 1% and 7% for interventions preventing readmission. An online calculator is provided <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"https:\/\/urldefense.com\/v3\/__https:\/duke-som.shinyapps.io\/preeclampsia_readmit\/__;!!AU3bcTlGKuA!DKO4i2VN_z5-4wEFMAeC1xiC9LdU-1Y-Q2WQrjQA6O3Rbbc4-AxjEWCtu1Hp1Bw5w3fI1LeKILzH1vwtwXvWRBw15iGXvlxLdQ$\">here<\/jats:ext-link>.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>Postpartum readmission for hypertension and pre\u2010eclampsia may be accurately predicted but further model validation is needed. Model updating using data from multiple sites will be needed before use across clinical settings.<\/jats:p><\/jats:sec>","DOI":"10.1111\/1471-0528.17572","type":"journal-article","created":{"date-parts":[[2023,6,15]],"date-time":"2023-06-15T04:21:10Z","timestamp":1686802870000},"page":"1531-1540","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Postpartum readmission for hypertension and pre\u2010eclampsia: development and validation of a predictive model"],"prefix":"10.1111","volume":"130","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8043-556X","authenticated-orcid":false,"given":"Kartik Kailas","family":"Venkatesh","sequence":"first","affiliation":[{"name":"Department of Obstetrics and Gynecology The Ohio State University  Columbus Ohio USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7196-817X","authenticated-orcid":false,"given":"J. Eric","family":"Jelovsek","sequence":"additional","affiliation":[{"name":"Department of Obstetrics and Gynecology Duke University  Durham North Carolina USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Matthew","family":"Hoffman","sequence":"additional","affiliation":[{"name":"Department of Obstetrics and Gynecology Christiana Care  Newark Delaware USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"A. 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