Development and validation of a machine learning algorithm to identify anaphylaxis in US administrative claims data

被引:0
|
作者
Beachler, Daniel C. [1 ]
Taylor, Devon H. [1 ]
Anthony, Mary S. [2 ]
Yin, Ruihua [1 ]
Li, Ling [1 ]
Saltus, Catherine W. [2 ]
Li, Lin [3 ]
Shaunik, Alka [3 ]
Walsh, Kathleen E. [4 ]
Lanes, Stephan [1 ]
Rothman, Kenneth J. [2 ]
Johannes, Catherine [2 ]
Aroda, Vanita [5 ]
Carr, Warner [6 ]
Goldberg, Pinkus [7 ]
Accardi, Andrew [8 ,9 ]
O'Shura, J. Shane [10 ]
Sharma, Kristen [3 ]
Juhaeri, Juhaeri [3 ]
Wu, Chuntao [3 ]
机构
[1] HealthCore Inc, Wilmington, DE USA
[2] RTI Hlth Solut, Res Triangle Pk, NC USA
[3] Sanofi, Bridgewater, NJ USA
[4] Cincinnati Childrens Hosp, Cincinnati, OH USA
[5] Harvard, Cambridge, MA USA
[6] Allergy & Asthma Associates Southern Calif, Mission Viejo, CA USA
[7] Allergy Partners Cent Indiana, Indianapolis, IN USA
[8] Scripps Hlth, Encinitas, CA USA
[9] SMHE, Encinitas, CA USA
[10] Lower Bucks Hosp, Bristol, PA USA
关键词
D O I
暂无
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
106
引用
收藏
页码:602 / 602
页数:1
相关论文
共 50 条
  • [31] Development and validation of a case definition to identify hemophilia in administrative data
    Ul Alam, Arafat
    Karkhaneh, Mohammad
    Wu, Cynthia
    Sun, Haowei Linda
    [J]. THROMBOSIS RESEARCH, 2021, 204 : 16 - 21
  • [32] Development of an Algorithm to Identify Multiple Sclerosis (MS) Disease Severity Based on Healthcare Costs in a US Administrative Claims Database
    Nicholas, Jacqueline
    Ontaneda, Daniel
    Carraro, Matthew
    Wu, Ning
    Jhaveri, Mehul
    Yang, Kun
    Jones, Daniel
    Livingston, Terrie
    [J]. NEUROLOGY, 2017, 88
  • [33] DEVELOPMENT OF A NOVEL ALGORITHM TO IDENTIFY INDIVIDUALS WITH POSSIBLE ADULT GROWTH HORMONE DEFICIENCY FROM A US ADMINISTRATIVE CLAIMS DATABASE
    Birkegard, C.
    Blevins, L. S.
    Clemmons, D. R.
    Fleseriu, M.
    Hoffman, A. R.
    Kerr, J. M.
    Sun, T.
    Tarp, J.
    Tritos, N. A.
    Yuen, K.
    [J]. VALUE IN HEALTH, 2020, 23 : S518 - S519
  • [34] Validation of Algorithms to Identify Bone Metastases Using Administrative Claims Data in a Japanese Hospital
    Hirano, Takahiro
    Saito, Naoko
    Wakabayashi, Ryozo
    Kuwatsuru, Ryohei
    [J]. DRUGS-REAL WORLD OUTCOMES, 2023, 10 (02) : 187 - 194
  • [35] Validation of Algorithms to Identify Bone Metastases Using Administrative Claims Data in a Japanese Hospital
    Takahiro Hirano
    Naoko Saito
    Ryozo Wakabayashi
    Ryohei Kuwatsuru
    [J]. Drugs - Real World Outcomes, 2023, 10 : 187 - 194
  • [36] Development and Validation of an Algorithm To Ascertain Non-Hospitalized Suicide Attempts Using Administrative Claims Data
    Beland, Sarah-Gabrielle
    Tournier, Marie
    Brabant, Marie-Josee
    Greenfield, Brian
    Lynd, Larry
    Moride, Yola
    [J]. PHARMACOEPIDEMIOLOGY AND DRUG SAFETY, 2013, 22 : 380 - 380
  • [37] Validation of Operational Definition to Identify Patients with Osteoporotic Hip Fractures in Administrative Claims Data
    Lee, Young-Kyun
    Yoo, Jun-Il
    Kim, Tae-Young
    Ha, Yong-Chan
    Koo, Kyung-Hoi
    Choi, Hangseok
    Lee, Seung-Mi
    Suh, Dong-Churl
    [J]. HEALTHCARE, 2022, 10 (09)
  • [38] Machine Learning Model to Identify Sepsis Patients in the Emergency Department: Algorithm Development and Validation
    Lin, Pei-Chen
    Chen, Kuo-Tai
    Chen, Huan-Chieh
    Islam, Md Mohaimenul
    Lin, Ming-Chin
    [J]. JOURNAL OF PERSONALIZED MEDICINE, 2021, 11 (11):
  • [39] Using machine learning to improve anaphylaxis case identification in medical claims data
    Kural, Kamil Can
    Mazo, Ilya
    Walderhaug, Mark
    Santana-Quintero, Luis
    Karagiannis, Konstantinos
    Thompson, Elaine E.
    Kelman, Jeffrey A.
    Goud, Ravi
    [J]. JAMIA OPEN, 2024, 7 (02)
  • [40] Using machine learning to improve anaphylaxis case identification in medical claims data
    Kural, Kamil Can
    Mazo, Ilya
    Walderhaug, Mark
    Santana-Quintero, Luis
    Karagiannis, Konstantinos
    Thompson, Elaine E.
    Kelman, Jeffrey A.
    Goud, Ravi
    [J]. JAMIA OPEN, 2023, 6 (04)