Literature DB >> 32308875

Using Natural Language Processing to improve EHR Structured Data-based Surgical Site Infection Surveillance.

Jianlin Shi1, Siru Liu1, Liese C C Pruitt1, Carolyn L Luppens1, Jeffrey P Ferraro1,2, Adi V Gundlapalli1,3, Wendy W Chapman1, Brian T Bucher1.   

Abstract

Surgical Site Infection surveillance in healthcare systems is labor intensive and plagued by underreporting as current methodology relies heavily on manual chart review. The rapid adoption of electronic health records (EHRs) has the potential to allow the secondary use of EHR data for quality surveillance programs. This study aims to investigate the effectiveness of integrating natural language processing (NLP) outputs with structured EHR data to build machine learning models for SSI identification using real-world clinical data. We examined a set of models using structured data with and without NLP document-level, mention-level, and keyword features. The top-performing model was based on a Random Forest classifier enhanced with NLP document-level features achieving a 0.58 sensitivity, 0.97 specificity, 0.54 PPV, 0.98 NPV, and 0.52 F0.5 score. We further interrogated the feature contributions, analyzed the errors, and discussed future directions. ©2019 AMIA - All rights reserved.

Entities:  

Year:  2020        PMID： 32308875      PMCID： PMC7153106     

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


  14 in total

1.  Underlying reasons associated with hospital readmission following surgery in the United States.

Authors:  Ryan P Merkow; Mila H Ju; Jeanette W Chung; Bruce L Hall; Mark E Cohen; Mark V Williams; Thomas C Tsai; Clifford Y Ko; Karl Y Bilimoria
Journal:  JAMA       Date:  2015-02-03       Impact factor: 56.272

2.  Does surgical quality improve in the American College of Surgeons National Surgical Quality Improvement Program: an evaluation of all participating hospitals.

Authors:  Bruce L Hall; Barton H Hamilton; Karen Richards; Karl Y Bilimoria; Mark E Cohen; Clifford Y Ko
Journal:  Ann Surg       Date:  2009-09       Impact factor: 12.969

3.  Surveillance of surgical site infections by surgeons: biased underreporting or useful epidemiological data?

Authors:  R Rosenthal; W P Weber; W R Marti; H Misteli; S Reck; M Dangel; D Oertli; A F Widmer
Journal:  J Hosp Infect       Date:  2010-03-12       Impact factor: 3.926

4.  HITECH spurs EHR vendor competition and innovation, resulting in increased adoption.

Authors:  Seth Joseph; Max Sow; Michael F Furukawa; Steven Posnack; Mary Ann Chaffee
Journal:  Am J Manag Care       Date:  2014-09       Impact factor: 2.229

5.  Accelerating Chart Review Using Automated Methods on Electronic Health Record Data for Postoperative Complications.

Authors:  Zhen Hu; Genevieve B Melton; Nathan D Moeller; Elliot G Arsoniadis; Yan Wang; Mary R Kwaan; Eric H Jensen; Gyorgy J Simon
Journal:  AMIA Annu Symp Proc       Date:  2017-02-10

6.  Identifying surgical site infections in electronic health data using predictive models.

Authors:  Robert W Grundmeier; Rui Xiao; Rachael K Ross; Mark J Ramos; Dean J Karavite; Jeremy J Michel; Jeffrey S Gerber; Susan E Coffin
Journal:  J Am Med Inform Assoc       Date:  2018-09-01       Impact factor: 4.497

7.  From research to nationwide implementation: the impact of AHRQ's HAI prevention program.

Authors:  James B Battles; Stacy L Farr; Daniel A Weinberg
Journal:  Med Care       Date:  2014-02       Impact factor: 2.983

8.  A comparison of 2 surgical site infection monitoring systems.

Authors:  Mila H Ju; Clifford Y Ko; Bruce L Hall; Charles L Bosk; Karl Y Bilimoria; Elizabeth C Wick
Journal:  JAMA Surg       Date:  2015-01       Impact factor: 14.766

9.  Exploring the frontier of electronic health record surveillance: the case of postoperative complications.

Authors:  Fern FitzHenry; Harvey J Murff; Michael E Matheny; Nancy Gentry; Elliot M Fielstein; Steven H Brown; Ruth M Reeves; Dominik Aronsky; Peter L Elkin; Vincent P Messina; Theodore Speroff
Journal:  Med Care       Date:  2013-06       Impact factor: 2.983

10.  Knowledge Author: facilitating user-driven, domain content development to support clinical information extraction.

Authors:  William Scuba; Melissa Tharp; Danielle Mowery; Eugene Tseytlin; Yang Liu; Frank A Drews; Wendy W Chapman
Journal:  J Biomed Semantics       Date:  2016-06-23
View more
  4 in total

1.  A Deep Learning Approach to Estimate the Incidence of Infectious Disease Cases for Routinely Collected Ambulatory Records: The Example of Varicella-Zoster.

Authors:  Corrado Lanera; Ileana Baldi; Andrea Francavilla; Elisa Barbieri; Lara Tramontan; Antonio Scamarcia; Luigi Cantarutti; Carlo Giaquinto; Dario Gregori
Journal:  Int J Environ Res Public Health       Date:  2022-05-13       Impact factor: 4.614

2.  Standard Vocabularies to Improve Machine Learning Model Transferability With Electronic Health Record Data: Retrospective Cohort Study Using Health Care-Associated Infection.

Authors:  Amber C Kiser; Karen Eilbeck; Jeffrey P Ferraro; David E Skarda; Matthew H Samore; Brian Bucher
Journal:  JMIR Med Inform       Date:  2022-08-30

3.  Natural language processing for the surveillance of postoperative venous thromboembolism.

Authors:  Jianlin Shi; John F Hurdle; Stacy A Johnson; Jeffrey P Ferraro; David E Skarda; Samuel R G Finlayson; Matthew H Samore; Brian T Bucher
Journal:  Surgery       Date:  2021-06-03       Impact factor: 4.348

4.  Portable Automated Surveillance of Surgical Site Infections Using Natural Language Processing: Development and Validation.

Authors:  Brian T Bucher; Jianlin Shi; Jeffrey P Ferraro; David E Skarda; Matthew H Samore; John F Hurdle; Adi V Gundlapalli; Wendy W Chapman; Samuel R G Finlayson
Journal:  Ann Surg       Date:  2020-10       Impact factor: 13.787
  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.