IS BIGGER DATA BETTER? PREDICTING READMISSIONS IN ACUTE MYOCARDIAL INFARCTION ON ADMISSION VERSUS DISCHARGE WITH ELECTRONIC HEALTH RECORD DATA

被引:0
|
作者
Nguyen, Oanh K. [1 ]
Makam, Anil N. [1 ]
Clark, Christopher [2 ]
Zhang, Song [1 ]
Das, Sandeep R. [1 ]
Halm, Ethan [1 ]
机构
[1] UT Southwestern Med Ctr, Dallas, TX USA
[2] Parkland Hlth & Hosp Syst, Dallas, TX USA
关键词
D O I
暂无
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
引用
收藏
页码:S234 / S235
页数:2
相关论文
共 50 条
  • [1] Predicting 30-Day Readmissions With Preadmission Electronic Health Record Data
    Shadmi, Efrat
    Flaks-Manov, Natalie
    Hoshen, Moshe
    Goldman, Orit
    Bitterman, Haim
    Balicer, Ran D.
    MEDICAL CARE, 2015, 53 (03) : 283 - 289
  • [2] Using hospital Admission, Discharge & Transfer (ADT) data for predicting readmissions
    Saha, Pronojit
    Sircar, Reelina
    Bose, Arnab
    MACHINE LEARNING WITH APPLICATIONS, 2021, 5
  • [3] Predicting 30-Day Pneumonia Readmissions Using Electronic Health Record Data
    Makam, Anil N.
    Nguyen, Oanh Kieu
    Clark, Christopher
    Zhang, Song
    Xie, Bin
    Weinreich, Mark
    Mortensen, Eric M.
    Halm, Ethan A.
    JOURNAL OF HOSPITAL MEDICINE, 2017, 12 (04) : 209 - 216
  • [4] DEVELOPMENT AND VALIDATION OF AN ELECTRONIC HEALTH RECORD MODEL FOR PREDICTING 30-DAY READMISSIONS IN ACUTE MYOCARDIAL INFARCTION: THE AMI READMITS SCORE
    Nguyen, Oanh K.
    Makam, Anil N.
    Clark, Christopher
    Zhang, Song
    Das, Sandeep R.
    Halm, Ethan
    JOURNAL OF GENERAL INTERNAL MEDICINE, 2017, 32 : S159 - S160
  • [5] Predicting Hospitalizations From Electronic Health Record Data
    Morawski, Kyle
    Dvorkis, Yoni
    Monsen, Craig B.
    AMERICAN JOURNAL OF MANAGED CARE, 2020, 26 (01): : E7 - +
  • [6] PREDICTING BACTEREMIA USING ELECTRONIC HEALTH RECORD DATA
    Lonjers, Zachary
    Bhavani, Sivasubramanium
    Carey, Kyle
    Gilbert, Emily
    Afshar, Majid
    Churpek, Matthew
    CHEST, 2019, 156 (04) : 1607A - 1607A
  • [7] Assessment of Administrative Data to Identify Acute Myocardial Infarction in Electronic Health Records
    Mentz, Robert J.
    Newby, L. Kristin
    Neely, Ben
    Lucas, Joseph E.
    Pokorney, Sean D.
    Rao, Meena P.
    Jackson, Larry R., II
    Grau-Sepulveda, Maria V.
    Smerek, Michelle M.
    Barth, Pamela
    Nelson, Charlotte L.
    Pencina, Michael J.
    Shah, Bimal R.
    JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY, 2016, 67 (20) : 2441 - 2442
  • [8] Development and validation of a model predicting mild stroke severity on admission using electronic health record data
    Waddell, Kimberly J.
    Myers, Laura J.
    Perkins, Anthony J.
    Sico, Jason J.
    Sexson, Ali
    Burrone, Laura
    Taylor, Stanley
    Koo, Brian
    Daggy, Joanne K.
    Bravata, Dawn M.
    JOURNAL OF STROKE & CEREBROVASCULAR DISEASES, 2023, 32 (09):
  • [9] Topological Data Analysis of Electronic Health Record Features Predicts Major Cardiovascular Outcomes After Revascularization for Acute Myocardial Infarction
    Lopez, Javier E.
    Datta, Esha
    Ballal, Aditya
    Izu, Leighton T.
    CIRCULATION, 2022, 146
  • [10] Prediction of incident myocardial infarction using machine learning applied to harmonized electronic health record data
    Mandair, Divneet
    Tiwari, Premanand
    Simon, Steven
    Colborn, Kathryn L.
    Rosenberg, Michael A.
    BMC MEDICAL INFORMATICS AND DECISION MAKING, 2020, 20 (01)