Revisit Rates and Associated Costs After an Emergency Department Encounter

Autor: W. John Boscardin, Reena Duseja, Mitzi L. Dean, Naomi S. Bardach, Jinoos Yazdany, Grace A. Lin, Theodore H. Clay, R. Adams Dudley

Publikováno v: Annals of Internal Medicine. 162:750-756

Background Return visits to the emergency department (ED) or hospital after an index ED visit strain the health system, but information about rates and determinants of revisits is limited. Objective To describe revisit rates, variation in revisit rat

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3efb1f1281b5c0c2fcd9ea086d763b30
https://doi.org/10.7326/m14-1616

Thirty-Day Hospital Readmissions in Systemic Lupus Erythematosus: Predictors and Hospital- and State-Level Variation

Autor: R. Adams Dudley, Ben J. Marafino, Mitzi L. Dean, Naomi S. Bardach, Reena Duseja, Jinoos Yazdany, Michael M. Ward

Publikováno v: Arthritis & Rheumatology. 66:2828-2836

Objective Systemic lupus erythematosus (SLE) has one of the highest hospital readmission rates among chronic conditions. This study was undertaken to identify patient-level, hospital-level, and geographic predictors of 30-day hospital readmissions as

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::441331e993a009c98cf3101c13856c98
https://doi.org/10.1002/art.38768

Validation of Prediction Models for Critical Care Outcomes Using Natural Language Processing of Electronic Health Record Data

Autor: W. John Boscardin, Miran Park, Mitzi L. Dean, Dhruv S. Kazi, David C. Sing, R. Adams Dudley, Colette DeJong, Jason M Davies, Robert Thombley, Harold S. Luft, Ben J. Marafino

Publikováno v: JAMA Network Open. 1:e185097

Accurate prediction of outcomes among patients in intensive care units (ICUs) is important for clinical research and monitoring care quality. Most existing prediction models do not take full advantage of the electronic health record, using only the s

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fd141aeb374c0c355af4cbf9eb3b6fee
https://doi.org/10.1001/jamanetworkopen.2018.5097

Variation in ICU Risk-Adjusted Mortality

Autor: Nisha G. Trivedi, Michael W. Kuzniewicz, Mitzi L. Dean, Deborah J. Rennie, R. Adams Dudley, Rondall K. Lane, Pamela L. Kotler, Ted Clay, Eduard E. Vasilevskis

Publikováno v: Chest. 133:1319-1327

Background Federal and state agencies are considering ICU performance assessment and public reporting; however, an accurate method for measuring performance must be selected. In this study, we determine whether a substantial variation in ICU mortalit

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::a3a74613bdc457fb6ebf56c4fbd7d2ae
https://doi.org/10.1378/chest.07-3061

N-gram support vector machines for scalable procedure and diagnosis classification, with applications to clinical free text data from the intensive care unit

Autor: R. Adams Dudley, Naomi S. Bardach, Jason M Davies, Ben J. Marafino, Mitzi L. Dean

Publikováno v: Journal of the American Medical Informatics Association : JAMIA, vol 21, iss 5
Marafino, BJ; Davies, JM; Bardach, NS; Dean, ML; & Dudley, RA. (2014). N-gram support vector machines for scalable procedure and diagnosis classification, with applications to clinical free text data from the intensive care unit. Journal of the American Medical Informatics Association, 21(5), 871-875. doi: 10.1136/amiajnl-2014-002694. UCSF: Retrieved from: http://www.escholarship.org/uc/item/6pt5950p

Background Existing risk adjustment models for intensive care unit (ICU) outcomes rely on manual abstraction of patient-level predictors from medical charts. Developing an automated method for abstracting these data from free text might reduce cost a

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e5721d5acfd1fba318c84c24a4648f85
https://escholarship.org/uc/item/6pt5950p