Literature DB >> 32308879

Why Patient Portal Messages Indicate Risk of Readmission for Patients with Ischemic Heart Disease.

Lina Sulieman1, Zhijun Yin1, Bradley A Malin1.   

Abstract

Online portals enable patients to exchanging messages with healthcare providers. After discharge, patients message providers to ask questions and report problems. Care providers read and respond accordingly, which requires a non trivial amount of human effort and is unlikely to scale up as portals become more popular. Automatically detecting when a message indicates a worsening in a patient's condition can assist providers to identify patients at risk of readmission. We investigated the association between messages that patients, diagnosed with ischemic heart disease, sent after discharge and the risk of readmission. We studied 4,052 messages sent after discharge for 1,552 patients. We represented messages using inferred latent topics, linguistic features (e.g. emotions, activities), and clusters of medical terms. Our analysis indicates that mentioning medication dosage and additional procedures are associated with readmission. Moreover, patients who were readmitted rarely mentioned leisurely activities or described their insights about their health information. ©2019 AMIA - All rights reserved.

Entities:  

Year:  2020        PMID: 32308879      PMCID: PMC7153079     

Source DB:  PubMed          Journal:  AMIA Annu Symp Proc        ISSN: 1559-4076


  19 in total

1.  Predicting Negative Events: Using Post-discharge Data to Detect High-Risk Patients.

Authors:  Lina Sulieman; Daniel Fabbri; Fei Wang; Jianying Hu; Bradley A Malin
Journal:  AMIA Annu Symp Proc       Date:  2017-02-10

2.  #PrayForDad: Learning the Semantics Behind Why Social Media Users Disclose Health Information.

Authors:  Zhijun Yin; You Chen; Daniel Fabbri; Jimeng Sun; Bradley Malin
Journal:  Proc Int AAAI Conf Weblogs Soc Media       Date:  2016-05

3.  Rapid growth in surgeons' use of secure messaging in a patient portal.

Authors:  Jared A Shenson; Robert M Cronin; Sharon E Davis; Qingxia Chen; Gretchen Purcell Jackson
Journal:  Surg Endosc       Date:  2015-06-27       Impact factor: 4.584

4.  Classifying patient portal messages using Convolutional Neural Networks.

Authors:  Lina Sulieman; David Gilmore; Christi French; Robert M Cronin; Gretchen Purcell Jackson; Matthew Russell; Daniel Fabbri
Journal:  J Biomed Inform       Date:  2017-08-30       Impact factor: 6.317

5.  Medication safety messages for patients via the web portal: the MedCheck intervention.

Authors:  Saul N Weingart; Hope E Hamrick; Sharon Tutkus; Alexander Carbo; Daniel Z Sands; Anjala Tess; Roger B Davis; David W Bates; Russell S Phillips
Journal:  Int J Med Inform       Date:  2007-06-19       Impact factor: 4.046

6.  The therapy is making me sick: how online portal communications between breast cancer patients and physicians indicate medication discontinuation.

Authors:  Zhijun Yin; Morgan Harrell; Jeremy L Warner; Qingxia Chen; Daniel Fabbri; Bradley A Malin
Journal:  J Am Med Inform Assoc       Date:  2018-11-01       Impact factor: 4.497

Review 7.  The effect of patient portals on quality outcomes and its implications to meaningful use: a systematic review.

Authors:  Clemens Scott Kruse; Katy Bolton; Greg Freriks
Journal:  J Med Internet Res       Date:  2015-02-10       Impact factor: 5.428

8.  Evaluating user experiences of the secure messaging tool on the Veterans Affairs' patient portal system.

Authors:  Jolie N Haun; Jason D Lind; Stephanie L Shimada; Tracey L Martin; Robert M Gosline; Nicole Antinori; Max Stewart; Steven R Simon
Journal:  J Med Internet Res       Date:  2014-03-06       Impact factor: 5.428

9.  Characteristics of patient portals developed in the context of health information exchanges: early policy effects of incentives in the meaningful use program in the United States.

Authors:  Terese Otte-Trojel; Antoinette de Bont; Joris van de Klundert; Thomas G Rundall
Journal:  J Med Internet Res       Date:  2014-11-21       Impact factor: 5.428

10.  CLAMP - a toolkit for efficiently building customized clinical natural language processing pipelines.

Authors:  Ergin Soysal; Jingqi Wang; Min Jiang; Yonghui Wu; Serguei Pakhomov; Hongfang Liu; Hua Xu
Journal:  J Am Med Inform Assoc       Date:  2018-03-01       Impact factor: 4.497

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  2 in total

1.  Identifying Medication-Related Intents From a Bidirectional Text Messaging Platform for Hypertension Management Using an Unsupervised Learning Approach: Retrospective Observational Pilot Study.

Authors:  Anahita Davoudi; Natalie S Lee; Krisda Chaiyachati; Danielle Mowery; ThaiBinh Luong; Timothy Delaney; Elizabeth Asch
Journal:  J Med Internet Res       Date:  2022-06-29       Impact factor: 7.076

Review 2.  Quantifying Patient Portal Use: Systematic Review of Utilization Metrics.

Authors:  Terri Menser; Lauren L Beal; Jacob M Kolman; Stephen L Jones; Aroub Khleif
Journal:  J Med Internet Res       Date:  2021-02-25       Impact factor: 5.428

  2 in total

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