Published on in Vol 9, No 2 (2007):

Improving Information Technology Adoption and Implementation Through the Identification of Appropriate Benefits: Creating IMPROVE-IT

Improving Information Technology Adoption and Implementation Through the Identification of Appropriate Benefits: Creating IMPROVE-IT

Improving Information Technology Adoption and Implementation Through the Identification of Appropriate Benefits: Creating IMPROVE-IT

Authors of this article:

Kevin Leonard ;   Dean Sittig

Journals

  1. Dünnebeil S, Sunyaev A, Blohm I, Leimeister J, Krcmar H. Determinants of physicians’ technology acceptance for e-health in ambulatory care. International Journal of Medical Informatics 2012;81(11):746 View
  2. Otieno G, Hinako T, Motohiro A, Daisuke K, Keiko N. Measuring effectiveness of electronic medical records systems: Towards building a composite index for benchmarking hospitals. International Journal of Medical Informatics 2008;77(10):657 View
  3. Lau A. Hospital-Based Nurses’ Perceptions of the Adoption of Web 2.0 Tools for Knowledge Sharing, Learning, Social Interaction and the Production of Collective Intelligence. Journal of Medical Internet Research 2011;13(4):e92 View
  4. Archer N, Cocosila M. A Comparison of Physician Pre-Adoption and Adoption Views on Electronic Health Records in Canadian Medical Practices. Journal of Medical Internet Research 2011;13(3):e57 View
  5. Barnett M, Mehrotra A, Frolkis J, Spinks M, Steiger C, Hehir B, Greenberg J, Singh H. Implementation Science Workshop: Implementation of an Electronic Referral System in a Large Academic Medical Center. Journal of General Internal Medicine 2016;31(3):343 View
  6. McAlearney A, Song P, Robbins J, Hirsch A, Jorina M, Kowalczyk N, Chisolm D. Moving from Good to Great in Ambulatory Electronic Health Record Implementation. Journal for Healthcare Quality 2010;32(5):41 View
  7. Falkman G, Gustafsson M, Jontell M, Torgersson O. SOMWeb: A Semantic Web-Based System for Supporting Collaboration of Distributed Medical Communities of Practice. Journal of Medical Internet Research 2008;10(3):e25 View
  8. Kim Y, Delen D. Medical informatics research trend analysis: A text mining approach. Health Informatics Journal 2018;24(4):432 View
  9. Rajković P, Janković D, Milenković A, Kocić I. ANALYSIS OF THE LEVEL OF USE AND ACCEPTA NCE OF THE MEDICAL INFORMATION SYSTEM IN PRIMARY HEALTH CAR E. Acta Medica Medianae 2018;57(4):122 View
  10. Singh R, Mathiassen L, Switzer J, Adams R. Assimilation of Web-Based Urgent Stroke Evaluation: A Qualitative Study of Two Networks. JMIR Medical Informatics 2014;2(1):e6 View
  11. Flynn D, Gregory P, Makki H, Gabbay M. Expectations and experiences of eHealth in primary care: A qualitative practice-based investigation. International Journal of Medical Informatics 2009;78(9):588 View
  12. Scott I, Sullivan C, Staib A. Going digital: a checklist in preparing for hospital-wide electronic medical record implementation and digital transformation. Australian Health Review 2019;43(3):302 View
  13. Sittig D, Wright A, Osheroff J, Middleton B, Teich J, Ash J, Campbell E, Bates D. Grand challenges in clinical decision support. Journal of Biomedical Informatics 2008;41(2):387 View
  14. Rajković P, Aleksić D, Janković D, Milenković A, Petković I. Checking the potential shift to perceived usefulness—The analysis of users’ response to the updated electronic health record core features. International Journal of Medical Informatics 2018;115:80 View

Books/Policy Documents

  1. Tian R, Duffy V, Birk C, Abel S, Hultgren K. Digital Human Modeling. View