{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T07:02:06Z","timestamp":1771484526257,"version":"3.50.1"},"reference-count":35,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2022,4,29]],"date-time":"2022-04-29T00:00:00Z","timestamp":1651190400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2022,4,29]],"date-time":"2022-04-29T00:00:00Z","timestamp":1651190400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"Kaiser Foundation Hospitals, Inc"},{"name":"The Permanente Medical Group, Inc."},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R35GM128672"],"award-info":[{"award-number":["R35GM128672"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Health Serv Res"],"published-print":{"date-parts":[[2022,12]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n                <jats:title>Background<\/jats:title>\n                <jats:p>Increasing evidence suggests that social factors and problems with physical and cognitive function may contribute to patients\u2019 rehospitalization risk. Understanding a patient\u2019s readmission risk may help healthcare providers develop tailored treatment and post-discharge care plans to reduce readmission and mortality. This study aimed to evaluate whether including patient-reported data on social factors; cognitive status; and physical function improves on a predictive model based on electronic health record (EHR) data alone.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Methods<\/jats:title>\n                <jats:p>We conducted a prospective study of 1,547 hospitalized adult patients in 3 Kaiser Permanente Northern California hospitals. The main outcomes were non-elective rehospitalization or death within 30\u00a0days post-discharge. Exposures included patient-reported social factors and cognitive and physical function (obtained in a pre-discharge interview) and EHR\u2013derived data for comorbidity burden, acute physiology, care directives, prior utilization, and hospital length of stay. We performed bivariate comparisons using Chi-square, t-tests, and Wilcoxon rank-sum tests and assessed correlations between continuous variables using Spearman\u2019s rho statistic. For all models, the results reported were obtained after fivefold cross validation.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>The 1,547 adult patients interviewed were younger (age, <jats:italic>p<\/jats:italic>\u2009=\u20090.03) and sicker (COPS2, <jats:italic>p<\/jats:italic>\u2009&lt;\u20090.0001) than the rest of the hospitalized population. Of the 6 patient-reported social factors measured, 3 (not living with a spouse\/partner, transportation difficulties, health or disability-related limitations in daily activities) were significantly associated (<jats:italic>p<\/jats:italic>\u2009&lt;\u20090.05) with the main outcomes, while 3 (living situation concerns, problems with food availability, financial problems) were not. Patient-reported cognitive (<jats:italic>p<\/jats:italic>\u2009=\u20090.027) and physical function (<jats:italic>p<\/jats:italic>\u2009=\u20090.01) were significantly lower in patients with the main outcomes. None of the patient-reported variables, singly or in combination, improved predictive performance of a model that included acute physiology and longitudinal comorbidity burden (area under the receiver operator characteristic curve was 0.716 for both the EHR model and maximal performance of a random forest model including all predictors).<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusions<\/jats:title>\n                <jats:p>In this insured population, incorporating patient-reported social factors and measures of cognitive and physical function did not improve performance of an EHR-based model predicting 30-day non-elective rehospitalization or mortality. While incorporating patient-reported social and functional status data did not improve ability to predict these outcomes, such data may still be important for improving patient outcomes.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/s12913-022-07910-w","type":"journal-article","created":{"date-parts":[[2022,4,28]],"date-time":"2022-04-28T23:05:13Z","timestamp":1651187113000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Prospective evaluation of social risks, physical function, and cognitive function in prediction of non-elective rehospitalization and post-discharge mortality"],"prefix":"10.1186","volume":"22","author":[{"given":"Heather A.","family":"Clancy","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zheng","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nancy P.","family":"Gordon","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Patricia","family":"Kipnis","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vincent X.","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gabriel J.","family":"Escobar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,4,29]]},"reference":[{"issue":"1","key":"7910_CR1","doi-asserted-by":"publisher","first-page":"71","DOI":"10.1111\/j.1525-1497.2005.00278.x","volume":"21","author":"MB Kushel","year":"2006","unstructured":"Kushel MB, Gupta R, Gee L, Haas JS. 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All methods were performed in accordance with the relevant guidelines and regulations.Research staff approached eligible patients and described the study. Patients who agreed to participate confirmed their identity using an authentication process, provided informed consent, signed an authorization form for use and disclosure of their information, and signed an acknowledgment of receipt of the KPNC Research Participants\u2019 Bill of Rights. All signatures, including for the informed consent, were collected electronically via tablet.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare that they have no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"574"}}