Skip to main content

Main menu

  • Home
  • Articles
    • Current
    • Published Ahead of Print
    • Archive
    • Supplemental Issues
    • Collections - French
    • Collections - English
  • Info for
    • Authors & Reviewers
    • Submit a Manuscript
    • Advertisers
    • Careers & Locums
    • Subscribers
    • Permissions
  • About CFP
    • About CFP
    • About the CFPC
    • Editorial Advisory Board
    • Terms of Use
    • Contact Us
  • Feedback
    • Feedback
    • Rapid Responses
    • Most Read
    • Most Cited
    • Email Alerts
  • Blogs
    • Latest Blogs
    • Blog Guidelines
    • Directives pour les blogues
  • Mainpro+ Credits
    • About Mainpro+
    • Member Login
    • Instructions
  • Other Publications
    • http://www.cfpc.ca/Canadianfamilyphysician/
    • https://www.cfpc.ca/Login/
    • Careers and Locums

User menu

  • My alerts

Search

  • Advanced search
The College of Family Physicians of Canada
  • Other Publications
    • http://www.cfpc.ca/Canadianfamilyphysician/
    • https://www.cfpc.ca/Login/
    • Careers and Locums
  • My alerts
The College of Family Physicians of Canada

Advanced Search

  • Home
  • Articles
    • Current
    • Published Ahead of Print
    • Archive
    • Supplemental Issues
    • Collections - French
    • Collections - English
  • Info for
    • Authors & Reviewers
    • Submit a Manuscript
    • Advertisers
    • Careers & Locums
    • Subscribers
    • Permissions
  • About CFP
    • About CFP
    • About the CFPC
    • Editorial Advisory Board
    • Terms of Use
    • Contact Us
  • Feedback
    • Feedback
    • Rapid Responses
    • Most Read
    • Most Cited
    • Email Alerts
  • Blogs
    • Latest Blogs
    • Blog Guidelines
    • Directives pour les blogues
  • Mainpro+ Credits
    • About Mainpro+
    • Member Login
    • Instructions
  • RSS feeds
  • Follow cfp Template on Twitter
Research ArticleResearch

Predicting the use of electronic prescribing among early adopters in primary care

Claude Sicotte, Laurel Taylor and Robyn Tamblyn
Canadian Family Physician July 2013, 59 (7) e312-e321;
Claude Sicotte
Professor of Health Information Technology in the Department of Health Administration at the University of Montreal in Quebec.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: Claude.Sicotte@umontreal.ca
Laurel Taylor
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Robyn Tamblyn
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Article
  • Figures & Data
  • eLetters
  • Info & Metrics
  • PDF
Loading

Article Figures & Data

Figures

  • Tables
  • Figure 1
    • Download figure
    • Open in new tab
    Figure 1

    Multivariate model for predicting the use of electronic prescribing

Tables

  • Figures
    • View popup
    Table 1

    Descriptive statistics and linear regression model for predicting use of electronic prescribing

    PREDICTORSDESCRIPTIVE STATISTICS AND CORRELATIONSLINEAR REGRESSION MODEL TO PREDICT USAGE
    MEAN (SD)MINIMUMMAXIMUMCORRELATION WITH USAGEESTIMATE95% CIP VALUE
    Physicians’ perceptions and intentions
    Perceived usefulness*
      • Average score of usefulness†4.26 (0.51)350.080.03−0.06 to 0.12.57
    Perceived ease of use
      • MOXXI will be easy to use4.13 (0.69)250.190.05−0.02 to 0.12.14
    Social influence
      • Colleagues’ attitudes will be positive toward my use of MOXXI4.08 (0.61)350.110.03−0.04 to 0.11.40
    Intention to use
      • I will use MOXXI with most of my patients4.49 (0.62)25−0.020.00−0.08 to 0.07.90
    Physician characteristics
    Male sex‡NANANA0.190.07−0.02 to 0.16.15
    Practice experience
      • Graduation year1982 (7.55)19651999−0.17−0.004−0.010 to 0.002.18
    Physician typology§
      • PragmatistNANANA0.180.07−0.03 to 0.16.17
      • ReceptiveNANANA0.10−0.07−0.20 to 0.06.26
      • SeekerNANANA−0.150.05−0.08 to 0.17.44
    Previous computer experience
      • No. of hours per week of computer use5.67 (6.37)0300.450.010.01 to 0.02< .001
    Practice characteristics
    Continuity of care||0.57 (0.09)01−0.08−0.17−0.69 to 0.35.52
    Average medication use¶2.84 (0.83)150.300.070.01 to 0.12.02
    Practice size1840 (877)193880−0.170.000.00 to 0.00.20
    Practice volume#20.74 (7.26)242−0.170.00−0.01 to 0.00.19
    • MOXXI—medical office of the 21st century, NA—not applicable.

    • ↵* Cronbach α = .90.

    • ↵† Average score of usefulness is average of scores of 9 questions coming from perceived usefulness: 1) electronic prescribing will be useful; 2) electronic prescribing will make work easier; 3) electronic prescribing will have a beneficial effect on quality of patient care; 4) electronic prescribing will increase my professional satisfaction; 5) electronic prescribing will have a beneficial communication with other health care professionals; 6) electronic prescribing will improve continuity of care; 7) electronic prescribing will increase my professional autonomy; 8) electronic prescribing will increase patients’ satisfaction; and 9) electronic prescribing will have a minimal effect on depersonalizing patient care.

    • ↵‡ Female sex was used as reference category.

    • ↵§ Traditionalist was used as reference category.

    • ↵|| Proportion of visits made to study physician for each patient in the practice in the 18 months before the study.

    • ↵¶ No. of medications was counted for each patient in the 18 months before the study.

    • ↵# Daily no. of patients seen based on the no. of patient visits during the 18 months before the study divided by the no. of days worked during that same period.

    • View popup
    Table 2

    Three multivariate models to predict use of electronic prescribing: A) Parameters of physicians’ perceptions and intentions; B) Parameters of practice characteristics; C) Parameters of physician characteristics.

    A) PHYSICIANS’ PERCEPTIONS AND INTENTIONS*PERCEIVED USEFULNESS + PERCEIVED EASE OF USE + SOCIAL INFLUENCE + BEHAVIOURAL INTENTION
    ESTIMATE95% CIP VALUE
    Intercept0.22−0.26 to 0.70.36
    Perceived usefulness
      • Average score of usefulness−0.02−0.14 to 0.09.72
    Perceived ease of use
      • MOXXI will be easy to use0.06−0.03 to 0.16.19
    Social influence
      • Colleagues’ attitudes will be positive toward my use of MOXXI0.01−0.09 to 0.10.85
    Behavioural intention
      • I will use MOXXI with most of my patients−0.03−0.11 to 0.05.50
    B) PRACTICE CHARACTERISTICS†PRACTICE VOLUME + CONTINUITY OF CARE + MEDICATION USE + PRACTICE SIZE
    ESTIMATE95% CIP VALUE
    Intercept0.20−0.17 to 0.57.28
    Practice volume‡0.00−0.01 to 0.01.34
    Continuity of care§−0.12−0.72 to 0.48.68
    Average medication use||0.080.01 to 0.14.02
    Practice size¶0.000.00 to 0.00.52
    C) PHYSICIAN CHARACTERISTICS#AGE + SEX + INFORMATION-ACQUISITION STYLE + COMPUTER EXPERIENCE
    ESTIMATE95% CIP VALUE
    Intercept0.07−0.55 to 0.68.83
    Practice experience
      • Graduation year−0.001−0.01 to 0.01.77
    Sex**
      • Male0.03−0.07 to 0.14.53
    Physician typology††
      • Pragmatist0.260.08 to 0.45.01
      • Seeker0.16−0.05 to 0.36.13
      • Receptive0.260.06 to 0.47.01
    Computer experience
      • Hours per week of computer use0.010.005 to 0.02.001
    • MOXXI—medical office of the 21st century.

    • ↵* R2 = 0.05; adjusted R2 = 0.02.

    • ↵† R2 = 0.12; adjusted R2 = 0.06.

    • ↵‡ Daily no. of patients seen based on the no. of patient visits during the 18 months before the study.

    • ↵§ Proportion of visits made to study physician for each patient in the practice in the 18 months before the study.

    • ↵|| No. of medications was counted for each patient in the 18 months before the study.

    • ↵¶ Unique patients that visited the study physician during the 18 months before study enrolment.

    • # R2 = 0.34; adjusted R2 = 0.27.

    • ↵** Female sex was reference category.

    • ↵†† Traditionalist was reference category.

    • View popup
    Table 3

    Exploratory multivariate model with all variables: Variables selected by stepwise procedure; R2 = 0.42; adjusted R2 = 0.37.

    VARIABLESMULTIPLE REGRESSION, WITH VARIABLES DETERMINED BY STEPWISE SELECTION PROCEDURE
    ESTIMATE95% CIP VALUE
    Intercept−0.22−0.44 to 0.01.06
    Hours per week of computer use0.010.005 to 0.02.001
    Medication use0.070.02 to 0.11.01
    Pragmatist versus others0.300.12 to 0.47.001
    Receptive versus others0.300.11 to 0.49.003
    Seeker versus others0.18−0.01 to 0.38.06
PreviousNext
Back to top

In this issue

Canadian Family Physician: 59 (7)
Canadian Family Physician
Vol. 59, Issue 7
1 Jul 2013
  • Table of Contents
  • About the Cover
  • Index by author
Print
Download PDF
Article Alerts
Sign In to Email Alerts with your Email Address
Email Article

Thank you for your interest in spreading the word on The College of Family Physicians of Canada.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
Predicting the use of electronic prescribing among early adopters in primary care
(Your Name) has sent you a message from The College of Family Physicians of Canada
(Your Name) thought you would like to see the The College of Family Physicians of Canada web site.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Citation Tools
Predicting the use of electronic prescribing among early adopters in primary care
Claude Sicotte, Laurel Taylor, Robyn Tamblyn
Canadian Family Physician Jul 2013, 59 (7) e312-e321;

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Respond to this article
Share
Predicting the use of electronic prescribing among early adopters in primary care
Claude Sicotte, Laurel Taylor, Robyn Tamblyn
Canadian Family Physician Jul 2013, 59 (7) e312-e321;
del.icio.us logo Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Jump to section

  • Article
    • Abstract
    • METHODS
    • RESULTS
    • DISCUSSION
    • Notes
    • Footnotes
    • References
  • Figures & Data
  • Info & Metrics
  • eLetters
  • PDF

Related Articles

  • No related articles found.
  • PubMed
  • Google Scholar

Cited By...

  • Connecting primary care clinics and community pharmacies through a nationwide electronic prescribing network: a qualitative study
  • Google Scholar

More in this TOC Section

  • First-trimester surgical abortion practice in Canada in 2012
  • Abdominal aortic aneurysm screening in an academic family practice
  • Focused practice in family medicine
Show more Research

Similar Articles

Subjects

  • Collection française
    • Résumés de recherche

Navigate

  • Home
  • Current Issue
  • Archive
  • Collections - English
  • Collections - Française

For Authors

  • Authors and Reviewers
  • Submit a Manuscript
  • Permissions
  • Terms of Use

General Information

  • About CFP
  • About the CFPC
  • Advertisers
  • Careers & Locums
  • Editorial Advisory Board
  • Subscribers

Journal Services

  • Email Alerts
  • Twitter
  • RSS Feeds

Copyright © 2023 by The College of Family Physicians of Canada

Powered by HighWire