{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T21:48:39Z","timestamp":1788472119938,"version":"build-2803163510"},"reference-count":27,"publisher":"Wiley","issue":"12","license":[{"start":{"date-parts":[[2020,8,28]],"date-time":"2020-08-28T00:00:00Z","timestamp":1598572800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/100007217","name":"Health Services Research and Development","doi-asserted-by":"publisher","award":["NRI 16\u2010344"],"award-info":[{"award-number":["NRI 16\u2010344"]}],"id":[{"id":"10.13039\/100007217","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000049","name":"National Institute on Aging","doi-asserted-by":"publisher","award":["P30AG021342"],"award-info":[{"award-number":["P30AG021342"]}],"id":[{"id":"10.13039\/100000049","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000027","name":"National Institute on Alcohol Abuse and Alcoholism","doi-asserted-by":"publisher","award":["U01 AA026224"],"award-info":[{"award-number":["U01 AA026224"]}],"id":[{"id":"10.13039\/100000027","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["agsjournals.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["J American Geriatrics Society"],"published-print":{"date-parts":[[2020,12]]},"abstract":"<jats:sec>\n                    <jats:title>BACKGROUND\/OBJECTIVES<\/jats:title>\n                    <jats:p>Due to high rates of multimorbidity, polypharmacy, and hazardous alcohol and opioid use, middle\u2010aged Veterans are at risk for serious falls (those prompting a visit with a healthcare provider), posing significant risk to their forthcoming geriatric health and quality of life. We developed and validated a predictive model of the 6\u2010month risk of serious falls among middle\u2010aged Veterans.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>DESIGN<\/jats:title>\n                    <jats:p>Cohort study.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>SETTING<\/jats:title>\n                    <jats:p>Veterans Health Administration (VA).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>PARTICIPANTS<\/jats:title>\n                    <jats:p>Veterans, aged 45 to 65\u2009years, who presented for care within the VA between 2012 and 2015 (N = 275,940).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>EXPOSURES<\/jats:title>\n                    <jats:p>\n                      The exposures of primary interest were substance use (including alcohol and prescription opioid use), multimorbidity, and polypharmacy. Hazardous alcohol use was defined as an Alcohol Use Disorders Identification Test \u2010 Consumption (AUDIT\u2010C) score\u2009of 3 or greater for women and 4 or greater for men. We used\n                      <jats:italic>International Classification of Diseases, Ninth Revision<\/jats:italic>\n                      (\n                      <jats:italic>ICD\u20109<\/jats:italic>\n                      ), codes to identify alcohol and illicit substance use disorders and identified prescription opioid use from pharmacy fill\u2010refill data. We included counts of chronic medications and of physical and mental health comorbidities.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>MEASUREMENTS<\/jats:title>\n                    <jats:p>We identified serious falls using external cause of injury codes and a machine\u2010learning algorithm that identified serious falls in radiology reports. We used multivariable logistic regression with general estimating equations to calculate risk. We used an integrated predictiveness curve to identify intervention thresholds.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>RESULTS<\/jats:title>\n                    <jats:p>\n                      Most of our sample (54%) was aged 60\u2009years or younger. Duration of follow\u2010up was up to 4\u2009years. Veterans who fell were more likely to be female (11% vs 7%) and White (72% vs 68%). They experienced 43,641 serious falls during follow\u2010up. We identified 16 key predictors of serious falls and five interaction terms. Model performance was enhanced by addition of opioid use, as evidenced by overall category\u2010free net reclassification improvement of 0.32 (\n                      <jats:italic>P<\/jats:italic>\n                      &lt;\u2009.001). Discrimination (C\u2010statistic = 0.76) and calibration were excellent for both development and validation data sets.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>CONCLUSION<\/jats:title>\n                    <jats:p>We developed and internally validated a model to predict 6\u2010month risk of serious falls among middle\u2010aged Veterans with excellent discrimination and calibration.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/jgs.16773","type":"journal-article","created":{"date-parts":[[2020,8,29]],"date-time":"2020-08-29T02:08:51Z","timestamp":1598666931000},"page":"2847-2854","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Serious Falls in Middle\u2010Aged Veterans: Development and Validation of a Predictive Risk Model"],"prefix":"10.1111","volume":"68","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1003-0276","authenticated-orcid":false,"given":"Julie A.","family":"Womack","sequence":"first","affiliation":[{"name":"VA Connecticut Healthcare System  West Haven"},{"name":"Yale School of Nursing  Orange Connecticut"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9649-517X","authenticated-orcid":false,"given":"Terrence E.","family":"Murphy","sequence":"additional","affiliation":[{"name":"Geriatrics Section, Department of Internal Medicine Yale School of Medicine  New Haven Connecticut"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Harini","family":"Bathulapalli","sequence":"additional","affiliation":[{"name":"VA Connecticut Healthcare System  West Haven"},{"name":"Yale Center for Analytic Services Yale School of Medicine  New Haven Connecticut"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alexandria","family":"Smith","sequence":"additional","affiliation":[{"name":"Yale School of Nursing  Orange Connecticut"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jonathan","family":"Bates","sequence":"additional","affiliation":[{"name":"VA Connecticut Healthcare System  West Haven"},{"name":"Yale Center for Medical Informatics Yale School of Medicine  New Haven Connecticut"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Samah","family":"Jarad","sequence":"additional","affiliation":[{"name":"Yale Center for Medical Informatics Yale School of Medicine  New Haven Connecticut"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nancy S.","family":"Redeker","sequence":"additional","affiliation":[{"name":"Yale School of Nursing  Orange Connecticut"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stephen L.","family":"Luther","sequence":"additional","affiliation":[{"name":"James A. Haley Veterans Hospital, Research Service  Tampa Florida"},{"name":"University of South Florida, College of Public Health  Tampa Florida"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6450-0368","authenticated-orcid":false,"given":"Thomas M.","family":"Gill","sequence":"additional","affiliation":[{"name":"Geriatrics Section, Department of Internal Medicine Yale School of Medicine  New Haven Connecticut"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cynthia A.","family":"Brandt","sequence":"additional","affiliation":[{"name":"VA Connecticut Healthcare System  West Haven"},{"name":"Yale Center for Medical Informatics Yale School of Medicine  New Haven Connecticut"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Amy C.","family":"Justice","sequence":"additional","affiliation":[{"name":"VA Connecticut Healthcare System  West Haven"},{"name":"Department of Internal Medicine Yale School of Medicine  New Haven Connecticut"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2020,8,28]]},"reference":[{"key":"e_1_2_6_2_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0201989"},{"key":"e_1_2_6_3_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0150939"},{"key":"e_1_2_6_4_1","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2458-5-86"},{"key":"e_1_2_6_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.amepre.2017.10.009"},{"issue":"1347","key":"e_1_2_6_6_1","first-page":"16","article-title":"Deaths and hospital admissions as a result of home injuries among young and middle\u2010aged New Zealand adults","volume":"124","author":"Kool B","year":"2011","journal-title":"N Z Med J"},{"key":"e_1_2_6_7_1","doi-asserted-by":"publisher","DOI":"10.2105\/AJPH.2005.083055"},{"key":"e_1_2_6_8_1","doi-asserted-by":"publisher","DOI":"10.1097\/QAI.0000000000002130"},{"key":"e_1_2_6_9_1","unstructured":"CDC. 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