Literature DB >> 32522027

Phenotyping issues for exploring electronic health records to design clinical trials.

Jill Schnall1, LingJiao Zhang1, Jinbo Chen1.   

Abstract

For utilizing electronic health records to help design and conduct clinical trials, an essential first step is to select eligible patients from electronic health records, that is, electronic health record phenotyping. We present two novel statistical methods that can be used in the context of electronic health record phenotyping. One mitigates the requirement for gold-standard control patients in developing phenotyping algorithms, and the other effectively corrects for bias in downstream analysis introduced by study samples contaminated by ineligible subjects.

Entities:  

Keywords:  Electronic health records; anchor variable; case contamination; phenotyping

Mesh:

Year:  2020        PMID: 32522027      PMCID: PMC7415575          DOI: 10.1177/1740774520931039

Source DB:  PubMed          Journal:  Clin Trials        ISSN: 1740-7745            Impact factor:   2.599


  3 in total

1.  Using Anchors to Estimate Clinical State without Labeled Data.

Authors:  Yoni Halpern; Youngduck Choi; Steven Horng; David Sontag
Journal:  AMIA Annu Symp Proc       Date:  2014-11-14

2.  A maximum likelihood approach to electronic health record phenotyping using positive and unlabeled patients.

Authors:  Lingjiao Zhang; Xiruo Ding; Yanyuan Ma; Naveen Muthu; Imran Ajmal; Jason H Moore; Daniel S Herman; Jinbo Chen
Journal:  J Am Med Inform Assoc       Date:  2020-01-01       Impact factor: 4.497

3.  Case contamination in electronic health records based case-control studies.

Authors:  Lu Wang; Jill Schnall; Aeron Small; Rebecca A Hubbard; Jason H Moore; Scott M Damrauer; Jinbo Chen
Journal:  Biometrics       Date:  2020-05-08       Impact factor: 2.571

  3 in total

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