Improving EMR System Adoption in Canadian Medical Practice: A Research Model

Fewer than one in four Canadian doctors use electronic medical record (EMR) systems, although almost all have some form of computer for scheduling and billing purposes. As a result, patient clinical records are mostly on paper, and are scattered and often inaccessible in doctors’ offices, clinics, test centres, labs, and hospitals. To properly care for their patients, primary care practitioners must have access to all their relevant medical records. If these are in digital form, they can be stored and readily accessed on EMR systems. If they are not, there are often significant delays, duplication of effort, and even inaccuracy in diagnosing problems. Insufficient adoption of EMR systems is a highly complex problem that has not been addressed adequately in a comprehensive manner. There are many interdependent factors that influence adoption and these must be considered simultaneously. The objective of this proposed research is to develop and validate statistically a comprehensive theoretical model of EMR adoption through a national survey of users, to attempt to explain why medical practices in Canada have tended to be slow in adopting electronic medical records and related systems. This paper describes that model and its basis, including the methodology that will be used to analyze the data.

[1]  Wynne W. Chin,et al.  Structural equation modeling analysis with small samples using partial least squares , 1999 .

[2]  P. M. Podsakoff,et al.  Self-Reports in Organizational Research: Problems and Prospects , 1986 .

[3]  James Y. L. Thong,et al.  An Integrated Model of Information Systems Adoption in Small Businesses , 1999, J. Manag. Inf. Syst..

[4]  Michael F Furukawa,et al.  Physician Practice Revenues and Use of Information Technology in Patient Care , 2007, Medical care.

[5]  Ebrahim Randeree,et al.  Exploring Physician Adoption of EMRs: A Multi-Case Analysis , 2007, Journal of Medical Systems.

[6]  I. Ajzen,et al.  Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research , 1977 .

[7]  N. Bontis.  Intellectual capital: an exploratory study that develops measures and models , 1998 .

[8]  Fred D. Davis,et al.  A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies , 2000, Management Science.

[9]  Karim Keshavjee,et al.  Applying methodology to electronic medical record selection , 2003, Int. J. Medical Informatics.

[10]  Marc B. Sokol,et al.  Adaptation to difficult designs: Facilitating use of new technology , 1994 .

[11]  Wynne W. Chin.  The partial least squares approach for structural equation modeling. , 1998 .

[12]  Barry Bozeman,et al.  Risk Culture in Public and Private Organizations , 1998 .

[13]  S.-S. Liaw,et al.  Understanding user perceptions of World-wide web environments , 2002, J. Comput. Assist. Learn..

[14]  Paul Jen-Hwa Hu,et al.  Information Technology Acceptance by Individual Professionals: A Model Comparison Approach , 2001, Decis. Sci..

[15]  Peter A. Todd,et al.  Assessing IT usage: the role of prior experience , 1995 .

[16]  J. Hair.  Multivariate data analysis , 1972 .

[17]  J. Hulland,et al.  Managing An Organizational Learning System By Aligning Stocks and Flows , 2002 .

[18]  Sowmya R. Rao,et al.  Electronic health records in ambulatory care--a national survey of physicians. , 2008, The New England journal of medicine.

[19]  J. Sidorov.  It Ain't Necessarily So: The Electronic Health Record And The Unlikely Prospect Of Reducing Health Care Costs. , 2006, Health affairs.

[20]  J. Jacoby,et al.  The Components of Perceived Risk , 1972 .

[21]  Fred D. Davis,et al.  User Acceptance of Computer Technology: A Comparison of Two Theoretical Models , 1989 .

[22]  Eric W. Ford,et al.  Predicting the adoption of electronic health records by physicians: when will health care be paperless? , 2006, Journal of the American Medical Informatics Association : JAMIA.

[23]  E. Coiera.  Four rules for the reinvention of health care , 2004, BMJ : British Medical Journal.

[24]  Carol Cain,et al.  UpDa t e: C onference Re po rt The Adoption Gap: Health Information Technology In Small Physician Practices , 2005 .

[25]  Gordon B. Davis,et al.  User Acceptance of Information Technology: Toward a Unified View , 2003, MIS Q..

[26]  Arun Vishwanath,et al.  Article Health Informatics Journal ••••• , 2022 .

[27]  Fred D. Davis.  Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology , 1989, MIS Q..

[28]  W. Chismar,et al.  The interaction of institutionally triggered and technology-triggered social structure change: an investigation of computerized physician order entry , 2007 .

[29]  Andrew P. McAfee.  When Too Much IT Knowledge Is a Dangerous Thing , 2003 .

[30]  D. Sandy Staples,et al.  Toward Contextualized Theories of Trust: The Role of Trust in Global Virtual Teams , 2004, Inf. Syst. Res..

[31]  E. B. Andersen,et al.  Modern factor analysis , 1961 .

[32]  Kirk St. Amant,et al.  Internal Cultural Barriers to E-Commerce Implementation: A Case Study of How Ineffective Leadership Doomed XYZ's Online Transaction System , 2006 .

[33]  Tracey E. Rizzuto,et al.  A multidisciplinary meta-analysis of human barriers to technology implementation. , 2007 .

[34]  Detmar W. Straub,et al.  Information Technology Adoption Across Time: A Cross-Sectional Comparison of Pre-Adoption and Post-Adoption Beliefs , 1999, MIS Q..

[35]  D. Bates.  Physicians and ambulatory electronic health records. , 2005, Health affairs.

[36]  Karim Keshavjee,et al.  Best Practices in EMR Implementation: A Systematic Review , 2006, AMIA.

[37]  Jen-Her Wu,et al.  What drives mobile commerce?: An empirical evaluation of the revised technology acceptance model , 2005, Inf. Manag..

[38]  J Sweetland.  In the know. , 1990, Nursing times.

[39]  K. Grønhaug,et al.  Perceived Risk: Further Considerations for the Marketing Discipline , 1993 .

[40]  RICHARD W. POHL.  In the know. , 1998, Nursing standard (Royal College of Nursing (Great Britain) : 1987).

[41]  Rex B. Kline,et al.  Principles and Practice of Structural Equation Modeling , 1998 .

[42]  Paul van Schaik,et al.  The acceptance of a computerised decision-support system in primary care: A preliminary investigation , 2004, Behav. Inf. Technol..

[43]  Ted Roselius.  Consumer Rankings of Risk Reduction Methods , 1971 .

[44]  Karen Davis,et al.  Health information technology and physician perceptions of quality of care and satisfaction. , 2009, Health policy.

[45]  Nena Lim,et al.  Consumers' perceived risk: sources versus consequences , 2003, Electron. Commer. Res. Appl..

[46]  Izak Benbasat,et al.  Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation , 1991, Inf. Syst. Res..

[47]  Paul A. Pavlou,et al.  Predicting E-Services Adoption: A Perceived Risk Facets Perspective , 2002, Int. J. Hum. Comput. Stud..

[48]  Mun Y. Yi,et al.  Understanding information technology acceptance by individual professionals: Toward an integrative view , 2006, Inf. Manag..

[49]  James G. Anderson,et al.  Computerization of Primary Care in the United States , 2006, Int. J. Heal. Inf. Syst. Informatics.