Literature DB >> 19279318

Review: use of electronic medical records for health outcomes research: a literature review.

Bonnie B Dean1, Jessica Lam, Jaime L Natoli, Qiana Butler, Daniel Aguilar, Robert J Nordyke.   

Abstract

This review assessed the use of electronic medical record (EMR) systems in outcomes research. We systematically searched PubMed to identify articles published from January 2000 to January 2007 involving EMR use for outpatient-based outcomes research in the United States. EMR-based outcomes research studies (n = 126) have increased sixfold since 2000. Although chronic conditions were most common, EMRs were also used to study less common diseases, highlighting the EMRs' flexibility to examine large cohorts as well as identify patients with rare diseases. Traditional multi-variate modeling techniques were the most commonly used technique to address confounding and potential selection bias. Data validation was a component in a quarter of studies, and many evaluated the EMR's ability to achieve similar results previously achieved using other data sources. Investigators using EMR data should aim for consistent terminology, focus on adequately describing their methods, and consider appropriate statistical methods to control for confounding and treatment-selection bias.

Entities:  

Mesh:

Year:  2009        PMID: 19279318     DOI: 10.1177/1077558709332440

Source DB:  PubMed          Journal:  Med Care Res Rev        ISSN: 1077-5587            Impact factor:   3.929


  76 in total

1.  Patient-centered research from electronic medical records.

Authors:  Mikel Aickin
Journal:  Perm J       Date:  2011

2.  An analytical approach to characterize morbidity profile dissimilarity between distinct cohorts using electronic medical records.

Authors:  Jonathan S Schildcrout; Melissa A Basford; Jill M Pulley; Daniel R Masys; Dan M Roden; Deede Wang; Christopher G Chute; Iftikhar J Kullo; David Carrell; Peggy Peissig; Abel Kho; Joshua C Denny
Journal:  J Biomed Inform       Date:  2010-08-03       Impact factor: 6.317

3.  Substance abuse treatment programs' data management capacity: an exploratory study.

Authors:  Jennifer P Wisdom; James H Ford; Meg Wise; Deirdre Mackey; Carla A Green
Journal:  J Behav Health Serv Res       Date:  2011-04       Impact factor: 1.505

4.  Anonymization of longitudinal electronic medical records.

Authors:  Acar Tamersoy; Grigorios Loukides; Mehmet Ercan Nergiz; Yucel Saygin; Bradley Malin
Journal:  IEEE Trans Inf Technol Biomed       Date:  2012-01-27

5.  ODaCCI: Ontology-guided Data Curation for Multisite Clinical Research Data Integration in the NINDS Center for SUDEP Research.

Authors:  Licong Cui; Yan Huang; Shiqiang Tao; Samden D Lhatoo; Guo-Qiang Zhang
Journal:  AMIA Annu Symp Proc       Date:  2017-02-10

6.  Building a diabetes screening population data repository using electronic medical records.

Authors:  Wen-Jan Tuan; Ann M Sheehy; Maureen A Smith
Journal:  J Diabetes Sci Technol       Date:  2011-05-01

7.  Changing prescribing patterns of type 2 diabetes medications from 2002-2010: an electronic health record-based evaluation.

Authors:  Sanjeev N Mehta; Allison B Goldfine; Martin J Abrahamson; Richard DiVincenzo; Lori M B Laffel
Journal:  J Diabetes Sci Technol       Date:  2013-01-01

8.  Reviewing the Record: Medical Record Reviews for Medical Toxicology Research.

Authors:  Jaiva Larsen; Mark B Mycyk; Trevonne M Thompson
Journal:  J Med Toxicol       Date:  2018-07-31

9.  Prevalence of toddler, child and adolescent overweight and obesity derived from primary care electronic medical records: an observational study.

Authors:  Suzanne Biro; Dave Barber; Tyler Williamson; Rachael Morkem; Shahriar Khan; Ian Janssen
Journal:  CMAJ Open       Date:  2016-09-26

10.  Bandit solutions provide unified ethical models for randomized clinical trials and comparative effectiveness research.

Authors:  William H Press
Journal:  Proc Natl Acad Sci U S A       Date:  2009-12-14       Impact factor: 11.205

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