{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,22]],"date-time":"2026-07-22T12:26:52Z","timestamp":1784723212519,"version":"3.55.0"},"reference-count":47,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2021,3,17]],"date-time":"2021-03-17T00:00:00Z","timestamp":1615939200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2021,3,17]],"date-time":"2021-03-17T00:00:00Z","timestamp":1615939200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000026","name":"National Institute on Drug Abuse","doi-asserted-by":"publisher","award":["R01 DA051464"],"award-info":[{"award-number":["R01 DA051464"]}],"id":[{"id":"10.13039\/100000026","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000026","name":"National Institute on Drug Abuse","doi-asserted-by":"publisher","award":["R01DA04171"],"award-info":[{"award-number":["R01DA04171"]}],"id":[{"id":"10.13039\/100000026","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000026","name":"National Institute on Drug Abuse","doi-asserted-by":"publisher","award":["UG1-DA-049467"],"award-info":[{"award-number":["UG1-DA-049467"]}],"id":[{"id":"10.13039\/100000026","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000027","name":"National Institute on Alcohol Abuse and Alcoholism","doi-asserted-by":"publisher","award":["K23 AA024503"],"award-info":[{"award-number":["K23 AA024503"]}],"id":[{"id":"10.13039\/100000027","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000092","name":"U.S. National Library of Medicine","doi-asserted-by":"publisher","award":["R01-LM-010090"],"award-info":[{"award-number":["R01-LM-010090"]}],"id":[{"id":"10.13039\/100000092","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000092","name":"U.S. National Library of Medicine","doi-asserted-by":"publisher","award":["R01-LM-012973"],"award-info":[{"award-number":["R01-LM-012973"]}],"id":[{"id":"10.13039\/100000092","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000133","name":"Agency for Healthcare Research and Quality","doi-asserted-by":"publisher","award":["K12-HS-026385"],"award-info":[{"award-number":["K12-HS-026385"]}],"id":[{"id":"10.13039\/100000133","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006108","name":"National Center for Advancing Translational Sciences","doi-asserted-by":"publisher","award":["UL1-TR-002398"],"award-info":[{"award-number":["UL1-TR-002398"]}],"id":[{"id":"10.13039\/100006108","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Addict Sci Clin Pract"],"published-print":{"date-parts":[[2021,12]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n                <jats:title>Background<\/jats:title>\n                <jats:p>Opioid misuse screening in hospitals is resource-intensive and rarely done. Many hospitalized patients are never offered opioid treatment. An automated approach leveraging routinely captured electronic health record (EHR) data may be easier for hospitals to institute. We previously derived and internally validated an opioid classifier in a separate hospital setting. The aim is to externally validate our previously published and open-source machine-learning classifier at a different hospital for identifying cases of opioid misuse.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Methods<\/jats:title>\n                <jats:p>An observational cohort of 56,227 adult hospitalizations was examined between October 2017 and December 2019 during a hospital-wide substance use screening program with manual screening. Manually completed Drug Abuse Screening Test served as the reference standard to validate a convolutional neural network (CNN) classifier with coded word embedding features from the clinical notes of the EHR. The opioid classifier utilized all notes in the EHR and sensitivity analysis was also performed on the first 24\u00a0h of notes. Calibration was performed to account for the lower prevalence than in the original cohort.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>Manual screening for substance misuse was completed in 67.8% (n\u2009=\u200956,227) with 1.1% (n\u2009=\u2009628) identified with opioid misuse. The data for external validation included 2,482,900 notes with 67,969 unique clinical concept features. The opioid classifier had an AUC of 0.99 (95% CI 0.99\u20130.99) across the encounter and 0.98 (95% CI 0.98\u20130.99) using only the first 24\u00a0h of notes. In the calibrated classifier, the sensitivity and positive predictive value were 0.81 (95% CI 0.77\u20130.84) and 0.72 (95% CI 0.68\u20130.75). For the first 24\u00a0h, they were 0.75 (95% CI 0.71\u20130.78) and 0.61 (95% CI 0.57\u20130.64).<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusions<\/jats:title>\n                <jats:p>Our opioid misuse classifier had good discrimination during external validation. Our model may provide a comprehensive and automated approach to opioid misuse identification that augments current workflows and overcomes manual screening barriers.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/s13722-021-00229-7","type":"journal-article","created":{"date-parts":[[2021,3,17]],"date-time":"2021-03-17T13:02:32Z","timestamp":1615986152000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":32,"title":["External validation of an opioid misuse machine learning classifier in hospitalized adult patients"],"prefix":"10.1186","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6368-4652","authenticated-orcid":false,"given":"Majid","family":"Afshar","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Brihat","family":"Sharma","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sameer","family":"Bhalla","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hale M.","family":"Thompson","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dmitriy","family":"Dligach","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Randy A.","family":"Boley","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ekta","family":"Kishen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alan","family":"Simmons","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kathryn","family":"Perticone","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Niranjan S.","family":"Karnik","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,3,17]]},"reference":[{"key":"229_CR1","unstructured":"Weiss AJ, Elixhauser A, Barrett ML, Steiner CA, Bailey MK and O\u2019Malley L. Opioid-related inpatient stays and emergency department visits by state, 2009\u20132014: statistical brief# 219. 2017."},{"key":"229_CR2","doi-asserted-by":"publisher","first-page":"S108","DOI":"10.1037\/tra0000622","volume":"12","author":"M McCann Pineo","year":"2020","unstructured":"McCann Pineo M, Schwartz RM. Commentary on the coronavirus pandemic: anticipating a fourth wave in the opioid epidemic. Psychol Trauma. 2020;12:S108\u201310.","journal-title":"Psychol Trauma"},{"key":"229_CR3","volume-title":"Patient characteristics of opioid-related inpatient stays and emergency department visits nationally and by state, 2014: statistical brief# 224","author":"AJ Weiss","year":"2017","unstructured":"Weiss AJ, Bailey MK, O\u2019Malley L, Barrett ML, Elixhauser A, Steiner CA. Patient characteristics of opioid-related inpatient stays and emergency department visits nationally and by state, 2014: statistical brief# 224. Healthcare Cost and Utilization Project (HCUP) Statistical Briefs Rockville, MD: Agency for Healthcare Research and Quality; 2017."},{"key":"229_CR4","doi-asserted-by":"publisher","first-page":"64","DOI":"10.1016\/j.jsat.2016.07.004","volume":"69","author":"S Naeger","year":"2016","unstructured":"Naeger S, Mutter R, Ali MM, Mark T, Hughey L. Post-discharge treatment engagement among patients with an opioid-use disorder. J Subst Abuse Treat. 2016;69:64\u201371.","journal-title":"J Subst Abuse Treat"},{"key":"229_CR5","first-page":"1155","volume":"170","author":"PC Smith","year":"2010","unstructured":"Smith PC, Schmidt SM, Allensworth-Davies D, Saitz R. A single-question screening test for drug use in primary care. Arch Intern Med. 2010;170:1155\u201360.","journal-title":"Arch Intern Med"},{"key":"229_CR6","doi-asserted-by":"publisher","first-page":"299","DOI":"10.1007\/s11606-010-1509-4","volume":"26","author":"KA Bradley","year":"2011","unstructured":"Bradley KA, Lapham GT, Hawkins EJ, Achtmeyer CE, Williams EC, Thomas RM, Kivlahan DR. Quality concerns with routine alcohol screening in VA clinical settings. J Gen Intern Med. 2011;26:299\u2013306.","journal-title":"J Gen Intern Med"},{"key":"229_CR7","first-page":"431","volume":"12","author":"RG Wright","year":"2000","unstructured":"Wright RG, Rotheram-Borus MJ, Klosinski L, Ramos B, et al. Screening for transmission behaviors among HIV-infected adults. AIDS Educ Prev. 2000;12:431.","journal-title":"AIDS Educ Prev."},{"key":"229_CR8","doi-asserted-by":"publisher","first-page":"54","DOI":"10.1016\/j.jsat.2015.06.005","volume":"60","author":"C Barbosa","year":"2016","unstructured":"Barbosa C, Cowell AJ, Landwehr J, Dowd W, Bray JW. Cost of screening, brief intervention, and referral to treatment in health care settings. J Subst Abuse Treat. 2016;60:54\u201361.","journal-title":"J Subst Abuse Treat"},{"key":"229_CR9","doi-asserted-by":"publisher","first-page":"256","DOI":"10.1080\/10550490590949433","volume":"14","author":"BA Smothers","year":"2005","unstructured":"Smothers BA, Yahr HT. Alcohol use disorder and illicit drug use in admissions to general hospitals in the United States. Am J Addict. 2005;14:256\u201367.","journal-title":"Am J Addict"},{"key":"229_CR10","doi-asserted-by":"publisher","first-page":"1297","DOI":"10.1186\/1471-2458-14-1297","volume":"14","author":"S Boniface","year":"2014","unstructured":"Boniface S, Kneale J, Shelton N. Drinking pattern is more strongly associated with under-reporting of alcohol consumption than socio-demographic factors: evidence from a mixed-methods study. BMC Public Health. 2014;14:1297.","journal-title":"BMC Public Health"},{"key":"229_CR11","doi-asserted-by":"publisher","first-page":"214","DOI":"10.15265\/IY-2017-029","volume":"26","author":"G Gonzalez-Hernandez","year":"2017","unstructured":"Gonzalez-Hernandez G, Sarker A, O\u2019Connor K, Savova G. Capturing the patient\u2019s perspective: a review of advances in natural language processing of health-related text. Yearb Med Inform. 2017;26:214\u201327.","journal-title":"Yearb Med Inform"},{"key":"229_CR12","doi-asserted-by":"publisher","first-page":"1272","DOI":"10.1093\/jamia\/ocz072","volume":"26","author":"D Dligach","year":"2019","unstructured":"Dligach D, Afshar M, Miller T. Toward a clinical text encoder: pretraining for clinical natural language processing with applications to substance misuse. J Am Med Inform Assoc. 2019;26:1272\u20138.","journal-title":"J Am Med Inform Assoc"},{"key":"229_CR13","doi-asserted-by":"publisher","first-page":"254","DOI":"10.1093\/jamia\/ocy166","volume":"26","author":"M Afshar","year":"2019","unstructured":"Afshar M, Phillips A, Karnik N, Mueller J, To D, Gonzalez R, Price R, Cooper R, Joyce C, Dligach D. Natural language processing and machine learning to identify alcohol misuse from the electronic health record in trauma patients: development and internal validation. J Am Med Inform Assoc. 2019;26:254\u201361.","journal-title":"J Am Med Inform Assoc"},{"key":"229_CR14","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1016\/j.alcohol.2019.09.008","volume":"84","author":"D To","year":"2020","unstructured":"To D, Sharma B, Karnik N, Joyce C, Dligach D, Afshar M. Validation of an alcohol misuse classifier in hospitalized patients. Alcohol. 2020;84:49\u201355.","journal-title":"Alcohol"},{"key":"229_CR15","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0219717","author":"B Sharma","year":"2020","unstructured":"Sharma B, Dligach D, Swope K, Salisbury-Afshar E, Karnik NS, Joyce C, Afshar M. Publicly available machine learning models for identifying opioid misuse from the clinical notes of hospitalized patients. BMC Med Inform Decision Making. 2020. https:\/\/doi.org\/10.1371\/journal.pone.0219717.","journal-title":"BMC Med Inform Decision Making."},{"key":"229_CR16","doi-asserted-by":"publisher","first-page":"460","DOI":"10.1097\/ADM.0000000000000520","volume":"13","author":"HM Thompson","year":"2019","unstructured":"Thompson HM, Hill K, Jadhav R, Webb TA, Pollack M, Karnik N. The substance use intervention team: a preliminary analysis of a population-level strategy to address the opioid crisis at an academic health center. J Addict Med. 2019;13:460\u20133.","journal-title":"J Addict Med"},{"key":"229_CR17","doi-asserted-by":"publisher","first-page":"189","DOI":"10.1016\/j.jsat.2006.08.002","volume":"32","author":"E Yudko","year":"2007","unstructured":"Yudko E, Lozhkina O, Fouts A. A comprehensive review of the psychometric properties of the Drug Abuse Screening Test. J Subst Abuse Treat. 2007;32:189\u201398.","journal-title":"J Subst Abuse Treat"},{"issue":"24","key":"229_CR18","doi-asserted-by":"publisher","first-page":"2647","DOI":"10.1001\/jama.2016.18533","volume":"316","author":"NR Desai","year":"2016","unstructured":"Desai NR, Ross JS, Kwon JY, et al. Association between hospital penalty status under the hospital readmission reduction program and readmission rates for target and nontarget conditions. JAMA. 2016;316(24):2647\u201356.","journal-title":"JAMA"},{"key":"229_CR19","doi-asserted-by":"publisher","first-page":"2301","DOI":"10.1001\/jama.2020.8020","volume":"323","author":"USPST Force","year":"2020","unstructured":"Force USPST, Krist AH, Davidson KW, Mangione CM, Barry MJ, Cabana M, Caughey AB, Curry SJ, Donahue K, Doubeni CA, Epling JW Jr, Kubik M, Ogedegbe G, Pbert L, Silverstein M, Simon MA, Tseng C-W, Wong JB. Screening for unhealthy drug use: US preventive services task force recommendation statement. JAMA. 2020;323:2301\u20139.","journal-title":"JAMA."},{"key":"229_CR20","unstructured":"Quality USDoH, Human Services Substance A, Mental Health Services Administration Center For Behavioral Health Statistics A, United States Department of H, Human Services. Substance A, Mental Health Services Administration. Center for Behavioral Health S and Quality. National Survey on Drug Use and Health, 2011. ICPSR Data Holdings. 2012."},{"key":"229_CR21","doi-asserted-by":"publisher","first-page":"507","DOI":"10.1136\/jamia.2009.001560","volume":"17","author":"GK Savova","year":"2010","unstructured":"Savova GK, Masanz JJ, Ogren PV, Zheng J, Sohn S, Kipper-Schuler KC, Chute CG. Mayo clinical Text Analysis and Knowledge Extraction System (cTAKES): architecture, component evaluation and applications. J Am Med Inform Assoc. 2010;17:507\u201313.","journal-title":"J Am Med Inform Assoc"},{"key":"229_CR22","doi-asserted-by":"publisher","first-page":"8","DOI":"10.1097\/00005650-199801000-00004","volume":"36","author":"A Elixhauser","year":"1998","unstructured":"Elixhauser A, Steiner C, Harris DR, Coffey RM. Comorbidity measures for use with administrative data. Med Care. 1998;36:8\u201327.","journal-title":"Med Care"},{"key":"229_CR23","doi-asserted-by":"publisher","first-page":"e0118432","DOI":"10.1371\/journal.pone.0118432","volume":"10","author":"T Saito","year":"2015","unstructured":"Saito T, Rehmsmeier M. The precision-recall plot is more informative than the ROC plot when evaluating binary classifiers on imbalanced datasets. PLoS ONE. 2015;10:e0118432.","journal-title":"PLoS ONE"},{"key":"229_CR24","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1097\/01.ede.0000147512.81966.ba","volume":"16","author":"EF Schisterman","year":"2005","unstructured":"Schisterman EF, Perkins NJ, Liu A, Bondell H. Optimal cut-point and its corresponding Youden Index to discriminate individuals using pooled blood samples. Epidemiology. 2005;16:73\u201381.","journal-title":"Epidemiology"},{"key":"229_CR25","doi-asserted-by":"publisher","first-page":"W1","DOI":"10.7326\/M14-0698","volume":"162","author":"KGM Moons","year":"2015","unstructured":"Moons KGM, Altman DG, Reitsma JB, Ioannidis JPA, Macaskill P, Steyerberg EW, Vickers AJ, Ransohoff DF, Collins GS. Transparent reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): explanation and elaboration. Ann Intern Med. 2015;162:W1-73.","journal-title":"Ann Intern Med"},{"key":"229_CR26","doi-asserted-by":"publisher","first-page":"621","DOI":"10.1093\/jamia\/ocz228","volume":"27","author":"Y Huang","year":"2020","unstructured":"Huang Y, Li W, Macheret F, Gabriel RA, Ohno-Machado L. A tutorial on calibration measurements and calibration models for clinical prediction models. J Am Med Inform Assoc. 2020;27:621\u201333.","journal-title":"J Am Med Inform Assoc"},{"key":"229_CR27","doi-asserted-by":"publisher","first-page":"1624","DOI":"10.1001\/jama.2016.1464","volume":"315","author":"D Dowell","year":"2016","unstructured":"Dowell D, Haegerich TM, Chou R. CDC guideline for prescribing opioids for chronic pain\u2014United States, 2016. JAMA. 2016;315:1624.","journal-title":"JAMA"},{"key":"229_CR28","unstructured":"Weiss AJ, Elixhauser A. Overview of Hospital Stays in the United States, 2012: Statistical Brief #180 Healthcare Cost and Utilization Project (HCUP) Statistical Briefs Rockville (MD): Agency for Healthcare Research and Quality (US); 2014."},{"key":"229_CR29","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1002\/tera.1420400106","volume":"40","author":"Y Feldman","year":"1989","unstructured":"Feldman Y, Koren G, Mattice D, Shear H, Pellegrini E, MacLeod SM. Determinants of recall and recall bias in studying drug and chemical exposure in pregnancy. Teratology. 1989;40:37\u201345.","journal-title":"Teratology"},{"key":"229_CR30","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1007\/s10995-015-1799-6","volume":"20","author":"M Garg","year":"2016","unstructured":"Garg M, Garrison L, Leeman L, Hamidovic A, Borrego M, Rayburn WF, Bakhireva L. Validity of self-reported drug use information among pregnant women. Matern Child Health J. 2016;20:41\u20137.","journal-title":"Matern Child Health J"},{"key":"229_CR31","doi-asserted-by":"publisher","first-page":"2310","DOI":"10.1001\/jama.2019.21381","volume":"323","author":"CD Patnode","year":"2020","unstructured":"Patnode CD, Perdue LA, Rushkin M, Dana T, Blazina I, Bougatsos C, Grusing S, O\u2019Connor EA, Fu R, Chou R. Screening for unhealthy drug use: updated evidence report and systematic review for the us preventive services task force. JAMA. 2020;323:2310\u201328.","journal-title":"JAMA"},{"key":"229_CR32","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.jsat.2017.05.007","volume":"79","author":"P Trowbridge","year":"2017","unstructured":"Trowbridge P, Weinstein ZM, Kerensky T, Roy P, Regan D, Samet JH, Walley AY. Addiction consultation services\u2013linking hospitalized patients to outpatient addiction treatment. J Subst Abuse Treat. 2017;79:1\u20135.","journal-title":"J Subst Abuse Treat"},{"key":"229_CR33","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1001\/jamapsychiatry.2015.2132","volume":"73","author":"BF Grant","year":"2016","unstructured":"Grant BF, Saha TD, June Ruan W, Goldstein RB, Patricia Chou S, Jung J, Zhang H, Smith SM, Pickering RP, Huang B, Hasin DS. Epidemiology ofDSM-5drug use disorder. JAMA Psychiatry. 2016;73:39.","journal-title":"JAMA Psychiatry"},{"key":"229_CR34","doi-asserted-by":"publisher","first-page":"1204","DOI":"10.1093\/jamia\/ocx066","volume":"24","author":"C Canan","year":"2017","unstructured":"Canan C, Polinski JM, Alexander GC, Kowal MK, Brennan TA, Shrank WH. Automatable algorithms to identify nonmedical opioid use using electronic data: a systematic review. J Am Med Inform Assoc. 2017;24:1204\u201310.","journal-title":"J Am Med Inform Assoc"},{"key":"229_CR35","doi-asserted-by":"publisher","first-page":"380","DOI":"10.1016\/j.jpain.2015.01.011","volume":"16","author":"TR Hylan","year":"2015","unstructured":"Hylan TR, Von Korff M, Saunders K, Masters E, Palmer RE, Carrell D, Cronkite D, Mardekian J, Gross D. Automated prediction of risk for problem opioid use in a primary care setting. J Pain. 2015;16:380\u20137.","journal-title":"J Pain"},{"key":"229_CR36","doi-asserted-by":"publisher","first-page":"523","DOI":"10.1111\/j.1521-0391.2010.00084.x","volume":"19","author":"RC Smith","year":"2010","unstructured":"Smith RC, Frank C, Gardiner JC, Lamerato L, Rost KM. Pilot study of a preliminary criterion standard for prescription opioid misuse. Am J Addict. 2010;19:523\u20138.","journal-title":"Am J Addict"},{"key":"229_CR37","doi-asserted-by":"publisher","first-page":"e190968","DOI":"10.1001\/jamanetworkopen.2019.0968","volume":"2","author":"W-H Lo-Ciganic","year":"2019","unstructured":"Lo-Ciganic W-H, Huang JL, Zhang HH, Weiss JC, Wu Y, Kent Kwoh C, Donohue JM, Cochran G, Gordon AJ, Malone DC, Kuza CC, Gellad WF. Evaluation of machine-learning algorithms for predicting opioid overdose risk among medicare beneficiaries with opioid prescriptions. JAMA Network Open. 2019;2:e190968.","journal-title":"JAMA Network Open"},{"key":"229_CR38","doi-asserted-by":"publisher","first-page":"2087","DOI":"10.1001\/archinte.166.19.2087","volume":"166","author":"MD Sullivan","year":"2006","unstructured":"Sullivan MD, Edlund MJ, Zhang L, Un\u00fctzer J, Wells KB. Association between mental health disorders, problem drug use, and regular prescription opioid use. Arch Intern Med. 2006;166:2087\u201393.","journal-title":"Arch Intern Med"},{"key":"229_CR39","doi-asserted-by":"publisher","first-page":"355","DOI":"10.1016\/j.pain.2007.02.014","volume":"129","author":"MJ Edlund","year":"2007","unstructured":"Edlund MJ, Steffick D, Hudson T, Harris KM, Sullivan M. Risk factors for clinically recognized opioid abuse and dependence among veterans using opioids for chronic non-cancer pain. Pain. 2007;129:355\u201362.","journal-title":"Pain"},{"key":"229_CR40","doi-asserted-by":"publisher","first-page":"443","DOI":"10.1186\/1471-2458-12-443","volume":"12","author":"J McNeely","year":"2012","unstructured":"McNeely J, Gourevitch MN, Paone D, Shah S, Wright S, Heller D. Estimating the prevalence of illicit opioid use in New York City using multiple data sources. BMC Public Health. 2012;12:443.","journal-title":"BMC Public Health"},{"key":"229_CR41","unstructured":"Kassed CA, Levit KR and Hambrick MM. Hospitalizations Related to Drug Abuse, 2005: Statistical Brief #39 Healthcare Cost and Utilization Project (HCUP) Statistical Briefs Rockville (MD): Agency for Healthcare Research and Quality (US); 2007."},{"key":"229_CR42","doi-asserted-by":"publisher","DOI":"10.1016\/j.drugalcdep.2021.108568","author":"JR Langabeer","year":"2021","unstructured":"Langabeer JR, Stotts AL, Bobrow BJ, et al. Prevalence and charges of opioid-related visits to U.S. emergency departments. Drug Alcohol Depend. 2021. https:\/\/doi.org\/10.1016\/j.drugalcdep.2021.108568 (Online ahead of print).","journal-title":"Drug Alcohol Depend."},{"key":"229_CR43","doi-asserted-by":"publisher","first-page":"40","DOI":"10.1186\/1471-2288-14-40","volume":"14","author":"GS Collins","year":"2014","unstructured":"Collins GS, de Groot JA, Dutton S, Omar O, Shanyinde M, Tajar A, Voysey M, Wharton R, Yu L-M, Moons KG, Altman DG. External validation of multivariable prediction models: a systematic review of methodological conduct and reporting. BMC Med Res Methodol. 2014;14:40.","journal-title":"BMC Med Res Methodol"},{"key":"229_CR44","doi-asserted-by":"publisher","first-page":"333","DOI":"10.1093\/icvts\/ivy338","volume":"28","author":"S Siregar","year":"2019","unstructured":"Siregar S, Nieboer D, Versteegh MIM, Steyerberg EW, Takkenberg JJM. Methods for updating a risk prediction model for cardiac surgery: a statistical primer. Interact Cardiovasc Thorac Surg. 2019;28:333\u20138.","journal-title":"Interact Cardiovasc Thorac Surg"},{"key":"229_CR45","doi-asserted-by":"publisher","first-page":"1364","DOI":"10.1093\/jamia\/ocz068","volume":"26","author":"M Afshar","year":"2019","unstructured":"Afshar M, Dligach D, Sharma B, Cai X, Boyda J, Birch S, Valdez D, Zelisko S, Joyce C, Modave F, et al. Development and application of a high throughput natural language processing architecture to convert all clinical documents in a clinical data warehouse into standardized medical vocabularies. J Am Med Inform Assoc. 2019;26:1364\u20139.","journal-title":"J Am Med Inform Assoc."},{"key":"229_CR46","unstructured":"National Institute on Drug Abuse (June 22, 2018). Screening and Assessment Tools Chart. https:\/\/www.drugabuse.gov\/nidamed-medical-health-professionals\/screening-tools-resources\/chart-screening-tools. Accessed 8 Feb 2021"},{"issue":"2","key":"229_CR47","doi-asserted-by":"publisher","first-page":"93","DOI":"10.1002\/mpr.168","volume":"13","author":"RC Kessler","year":"2004","unstructured":"Kessler RC, Usun BT. The World Mental Health (WMH) Survey Initiative version of the World Health Organization (WHO) Composite International Diagnostic Interview (CIDI). Int J Methods Psychiatr Res. 2004;13(2):93\u2013121.","journal-title":"Int J Methods Psychiatr Res"}],"container-title":["Addiction Science &amp; Clinical Practice"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s13722-021-00229-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1186\/s13722-021-00229-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/s13722-021-00229-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,3,17]],"date-time":"2021-03-17T13:09:40Z","timestamp":1615986580000},"score":1,"resource":{"primary":{"URL":"https:\/\/ascpjournal.biomedcentral.com\/articles\/10.1186\/s13722-021-00229-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,3,17]]},"references-count":47,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2021,12]]}},"alternative-id":["229"],"URL":"https:\/\/doi.org\/10.1186\/s13722-021-00229-7","relation":{},"ISSN":["1940-0640"],"issn-type":[{"value":"1940-0640","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,3,17]]},"assertion":[{"value":"3 November 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 March 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 March 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The study was approved by the Rush University Chicago Institutional Review Board.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to particpate"}},{"value":"Need for patient consent was waived by the IRB and deemed unnecessary according to national regulations. However, the minimal data underlying the results of this study are only available upon request due to ethical and legal restrictions imposed by the Rush University Chicago Institutional Review Board. The data derives from the institution\u2019s electronic health record (EHR) and contains patients\u2019 protected health information (PHI). Data are available from Rush University Chicago for researchers who meet the criteria for access to confidential data and have a data usage agreement with the health system.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare they have no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"19"}}