The Role of Perceived Usefulness and Attitude on Electronic Health Record Acceptance

Information and communications technologies are a significant component of the healthcare domain and electronic health records play a major role within it. As a result, it is important that they are accepted en masse by healthcare professionals. How healthcare professionals perceive the usefulness of electronic health records and their attitudes towards them have been shown to have significant effects on their overall acceptance. This paper investigates the role of perceived usefulness and attitude on the intention to use electronic health records by future healthcare professionals using polynomial regression with response surface analysis. Results show that the relationship is more complex than predicted in prior research. The paper concludes that the predicting properties of the above determinants must be further investigated to clearly understand their role in predicting the intention to use electronic health records and in designing systems that are better adopted by healthcare professionals of the future.

[1]  Morten Hertzum,et al.  Incompatible Images: Asthmatics' Non-Use of an E-Health System for Asthma Self-Management , 2009 .

[2]  MehaouaAhmed,et al.  Detection of Faulty Measurements in WBANs using Gaussian Mixture Model and Ant Colony , 2014 .

[3]  Ib Johansen,et al.  Widespread adoption of information technology in primary care physician offices in Denmark: a case study. , 2010, Issue brief.

[4]  Ashish K. Jha,et al.  Electronic health records in small physician practices: availability, use, and perceived benefits , 2011, J. Am. Medical Informatics Assoc..

[5]  A Villers Ruiz,et al.  Statistical package for the social sciences (spss) , 1981 .

[6]  Denis J. Protti,et al.  Comparing the application of Health Information Technology in primary care in Denmark and Andalucía, Spain , 2009, Int. J. Medical Informatics.

[7]  Paul Jen-Hwa Hu,et al.  Investigating healthcare professionals' decisions to accept telemedicine technology: an empirical test of competing theories , 2002, Inf. Manag..

[8]  Paul Jen-Hwa Hu,et al.  Examining a Model of Information Technology Acceptance by Individual Professionals: An Exploratory Study , 2002, J. Manag. Inf. Syst..

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

[10]  Athina Lazakidou.  Wireless Technologies for Ambient Assisted Living and Healthcare: Systems and Applications , 2010 .

[11]  D. Blumenthal,et al.  The benefits of health information technology: a review of the recent literature shows predominantly positive results. , 2011, Health affairs.

[12]  Graham Pervan,et al.  ICT and OTs: A model of information and communication technology acceptance and utilisation by occupational therapists , 2007, Int. J. Medical Informatics.

[13]  J. Edwards.  Alternatives to difference scores: Polynomial regression analysis and response surface methodology. , 2002 .

[14]  M. C. Fitzgerald,et al.  eHealth: extending, enhancing, and evolving health care. , 2013, Annual review of biomedical engineering.

[15]  D. Gans,et al.  Medical groups' adoption of electronic health records and information systems. , 2005, Health affairs.

[16]  Yaning Liu,et al.  Detection of Faulty Measurements in WBANs using Gaussian Mixture Model and Ant Colony , 2014, Int. J. E Health Medical Commun..

[17]  W. Chismar,et al.  International Journal of Healthcare Information Systems and Informatics , 2018 .

[18]  D. Blumenthal,et al.  The "meaningful use" regulation for electronic health records. , 2010, The New England journal of medicine.

[19]  Rita Sood,et al.  Reforming Medical Curriculum in India in Recent Years: Conflicts of Political, Regulator, Educationist and Professional Natures and Strategies for their Resolution , 2012 .

[20]  Volkhard Klinger,et al.  Identification of Motion-Based Action Potentials in Neural Bundles , 2014 .

[21]  M. Sobel.  Asymptotic Confidence Intervals for Indirect Effects in Structural Equation Models , 1982 .

[22]  Fotis Kitsios,et al.  A Strategic Approach to e-health Interoperability Using e-government Frameworks , 2010 .

[23]  Martin Serrano,et al.  Pervasive Computing Support in the Transition towards Personalised Health Systems , 2011, Int. J. E Health Medical Commun..

[24]  Bernadette Dorizzi,et al.  Evidential Network-Based Multimodal Fusion for Fall Detection , 2013, Int. J. E Health Medical Commun..

[25]  Magid Igbaria,et al.  Personal Computing Acceptance Factors in Small Firms: A Structural Equation Model , 1997, MIS Q..

[26]  International Journal of Privacy and Health Information Management , 2022 .

[27]  W O Hackl,et al.  “Why the Hell Do We Need Electronic Health Records?” , 2010, Methods of Information in Medicine.

[28]  Nandan Parameswaran,et al.  Development of a Methodological Approach for Data Quality Ontology in Diabetes Management , 2014, Int. J. E Health Medical Commun..

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

[30]  Yasumitsu Tomioka.  Legal Interpretation of Face-to-Face Consultation in Telemedicine , 2012, Int. J. E Health Medical Commun..

[31]  Renato Iannella,et al.  The role of perceived usefulness and attitude on electronic health record acceptance , 2013 .

[32]  Kalpdrum Passi,et al.  A Decision Support System (DSS) for Colorectal Cancer Follow-Up Program via a Semantic Framework , 2015, Int. J. Heal. Inf. Syst. Informatics.

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

[34]  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.

[35]  Marla Lukofsky.  One Moment in Time: A Patient’s Story , 2013 .

[36]  Andjela Drincic,et al.  The relationship between physician practice characteristics and physician adoption of electronic health records. , 2010, Health care management review.

[37]  Eric D. Heggestad,et al.  Polynomial Regression with Response Surface Analysis: A Powerful Approach for Examining Moderation and Overcoming Limitations of Difference Scores , 2010 .

[38]  Richard J. Holden,et al.  The Technology Acceptance Model: Its past and its future in health care , 2010, J. Biomed. Informatics.

[39]  Sowmya R. Rao,et al.  Use of electronic health records in U.S. hospitals. , 2009, The New England journal of medicine.

[40]  John Ingham,et al.  Why do people use information technology? A critical review of the technology acceptance model , 2003, Inf. Manag..

[41]  A. Boonstra,et al.  Barriers to the acceptance of electronic medical records by physicians from systematic review to taxonomy and interventions , 2010, BMC health services research.

[42]  Dimitris Koutsouris,et al.  Magnetic Resonance Imaging and Magnetic Resonance Spectroscopy Cloud Computing Framework , 2012 .

[43]  M. Rigler,et al.  International Journal of User-Driven Healthcare , 2015 .

[44]  International Journal of Reliable and Quality E-Healthcare , .

[45]  Amy K. Yarbrough,et al.  Technology Acceptance among Physicians , 2007, Medical care research and review : MCRR.