Literature DB >> 27256561

The Influence of the Degree of Rurality on EMR Adoption, by Physician Specialty.

Brian E Whitacre1.   

Abstract

OBJECTIVE: To explore the influence of varying degrees of remoteness on practice-level electronic medical record (EMR) adoption, including whether the effect differs across practice specialty. DATA SOURCES: Survey data on over 270,000 office-based physician practices (representing over 1,250,000 providers) collected by SK&A information services during 2012. STUDY
DESIGN: This study examined differences in EMR adoption by practices located across the nine-category rural-urban continuum. Logistic regressions and associated marginal effects are used to assess how much a move up or down the rural-urban continuum code impacts the likelihood of EMR adoption, after controlling for characteristics likely to affect EMR adoption such as practice size and specialty. PRINCIPAL
FINDINGS: Overall practice-level EMR adoption rates generally increase with the degree of rurality and range from 47 percent in the most urban counties to over 60 percent in the most rural. Moving from the most urban county to the most rural corresponded to a 7 percent increase in the likelihood of EMR adoption (p < .01).
CONCLUSIONS: EMR adoption rates do vary significantly across nonmetropolitan counties, and they generally increase as a practice becomes more rural. From a policy perspective, this suggests that urban practices may in fact be the lowest hanging remaining fruit for increasing EMR adoption rates. © Health Research and Educational Trust.

Keywords:  EMR adoption; Electronic medical records; rural

Mesh:

Year:  2016        PMID: 27256561      PMCID: PMC5346494          DOI: 10.1111/1475-6773.12510

Source DB:  PubMed          Journal:  Health Serv Res        ISSN: 0017-9124            Impact factor:   3.402


  17 in total

1.  The adoption and use of health information technology in rural areas: results of a national survey.

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2.  Medicare and Medicaid programs; electronic health record incentive program. Final rule.

Authors: 
Journal:  Fed Regist       Date:  2010-07-28

3.  Geographic variation in ambulatory electronic health record adoption: implications for underserved communities.

Authors:  Jennifer King; Michael F Furukawa; Melinda B Buntin
Journal:  Health Serv Res       Date:  2013-06-26       Impact factor: 3.402

4.  Clinical benefits of electronic health record use: national findings.

Authors:  Jennifer King; Vaishali Patel; Eric W Jamoom; Michael F Furukawa
Journal:  Health Serv Res       Date:  2013-12-21       Impact factor: 3.402

5.  The Health IT Regional Extension Center Program: evolution and lessons for health care transformation.

Authors:  Kimberly Lynch; Mat Kendall; Katherine Shanks; Ahmed Haque; Emily Jones; Maggie G Wanis; Michael Furukawa; Farzad Mostashari
Journal:  Health Serv Res       Date:  2013-12-21       Impact factor: 3.402

6.  The association between rural-urban continuum, maternal education and adverse birth outcomes in Québec, Canada.

Authors:  Nathalie Auger; Marie-Andrée Authier; Jérôme Martinez; Mark Daniel
Journal:  J Rural Health       Date:  2009       Impact factor: 4.333

Review 7.  The impact of the electronic medical record on structure, process, and outcomes within primary care: a systematic review of the evidence.

Authors:  Jayna M Holroyd-Leduc; Diane Lorenzetti; Sharon E Straus; Lindsay Sykes; Hude Quan
Journal:  J Am Med Inform Assoc       Date:  2011-06-09       Impact factor: 4.497

8.  Use and characteristics of electronic health record systems among office-based physician practices: United States, 2001-2013.

Authors:  Chun-Ju Hsiao; Esther Hing
Journal:  NCHS Data Brief       Date:  2014-01

9.  Colorectal cancer incidence and mortality in Texas 1990-1992: a comparison of rural classifications.

Authors:  Sarah Tropman Hawley; Shine Chang; David Risser; Qing Zhang
Journal:  J Rural Health       Date:  2002       Impact factor: 4.333

10.  Echocardiogram utilization among rural and urban veterans.

Authors:  Kingston Okrah; Mary Vaughan-Sarrazin; Peter Kaboli; Peter Cram
Journal:  J Rural Health       Date:  2011-05-25       Impact factor: 4.333

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  1 in total

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