Published on in Vol 9, No 2 (2017):

Safe Opioid Prescripting: A SMART on FHIR  Approach to Clinical Decision Support

Safe Opioid Prescripting: A SMART on FHIR Approach to Clinical Decision Support

Safe Opioid Prescripting: A SMART on FHIR Approach to Clinical Decision Support

The full text of this article is available as a PDF download by clicking here.

Journals

  1. Lee R, Hitt J, Hobika G, Nader N. The Case for the Anesthesiologist-Informaticist. JMIR Perioperative Medicine 2022;5(1):e32738 View
  2. Chin Y, Song W, Lien C, Yoon C, Wang W, Liu J, Nguyen P, Feng Y, Zhou L, Li Y, Bates D. Assessing the International Transferability of a Machine Learning Model for Detecting Medication Error in the General Internal Medicine Clinic: Multicenter Preliminary Validation Study. JMIR Medical Informatics 2021;9(1):e23454 View
  3. Taber P, Radloff C, Del Fiol G, Staes C, Kawamoto K. New Standards for Clinical Decision Support: A Survey of The State of Implementation. Yearbook of Medical Informatics 2021;30(01):159 View
  4. Colicchio T, Cimino J, Del Fiol G. Unintended Consequences of Nationwide Electronic Health Record Adoption: Challenges and Opportunities in the Post-Meaningful Use Era. Journal of Medical Internet Research 2019;21(6):e13313 View
  5. Bohn M, Fabiano G, Adeli K. Electronic tools in clinical laboratory diagnostics: key examples, limitations, and value in laboratory medicine. Journal of Laboratory Medicine 2021;45(6):319 View
  6. Matos A, Bankes D, Bain K, Ballinghoff T, Turgeon J. Opioids, Polypharmacy, and Drug Interactions: A Technological Paradigm Shift Is Needed to Ameliorate the Ongoing Opioid Epidemic. Pharmacy 2020;8(3):154 View
  7. Varshney U, Singh N, Bourgeois A, Dube S. Review, Assess, Classify, and Evaluate (RACE): a framework for studying m-health apps and its application for opioid apps. Journal of the American Medical Informatics Association 2022;29(3):520 View
  8. Koutitas G, Nolen K, Attal S, Ventouris A, Dolev Y, Van Den Broek H. Technical Feasibility of Implementing and Commercializing a Machine Learning Model for Rare Disease Prediction. IEEE Access 2023;11:84430 View
  9. Singh N, Dube S, Varshney U, Bourgeois A. A comprehensive mobile health intervention to prevent and manage the complexities of opioid use. International Journal of Medical Informatics 2022;164:104792 View
  10. Stagg B, Stein J, Medeiros F, Wirostko B, Crandall A, Hartnett M, Cummins M, Morris A, Hess R, Kawamoto K. Special Commentary: Using Clinical Decision Support Systems to Bring Predictive Models to the Glaucoma Clinic. Ophthalmology Glaucoma 2021;4(1):5 View
  11. Salloum R, Bilello L, Bian J, Diiulio J, Paz L, Gurka M, Gutierrez M, Hurley R, Jones R, Martinez-Wittinghan F, Marcial L, Masri G, McDonnell C, Militello L, Modave F, Nguyen K, Rhodes B, Siler K, Willis D, Harle C. Study protocol for a type III hybrid effectiveness-implementation trial to evaluate scaling interoperable clinical decision support for patient-centered chronic pain management in primary care. Implementation Science 2022;17(1) View
  12. Strasberg H, Rhodes B, Del Fiol G, Jenders R, Haug P, Kawamoto K. Contemporary clinical decision support standards using Health Level Seven International Fast Healthcare Interoperability Resources. Journal of the American Medical Informatics Association 2021;28(8):1796 View
  13. Singh N, Varshney U. Smart Interventions for Opioid Abuse. International Journal of Healthcare Information Systems and Informatics 2024;19(1):1 View
  14. Aapro M, Fogli S, Morlion B, Danesi R. Opioid metabolism and drug-drug interaction in cancer. The Oncologist 2024;29(11):931 View

Books/Policy Documents

  1. Lenert L. Clinical Decision Support and Beyond. View
  2. Casnoff C, Gamache R, Gaddis L. Portable Health Records in a Mobile Society. View